image-match/python/py/Lib/site-packages/triton/backends/nvidia/include/cuda.h

/*
 * Copyright 1993-2023 NVIDIA Corporation.  All rights reserved.
 *
 * NOTICE TO LICENSEE:
 *
 * This source code and/or documentation ("Licensed Deliverables") are
 * subject to NVIDIA intellectual property rights under U.S. and
 * international Copyright laws.
 *
 * These Licensed Deliverables contained herein is PROPRIETARY and
 * CONFIDENTIAL to NVIDIA and is being provided under the terms and
 * conditions of a form of NVIDIA software license agreement by and
 * between NVIDIA and Licensee ("License Agreement") or electronically
 * accepted by Licensee.  Notwithstanding any terms or conditions to
 * the contrary in the License Agreement, reproduction or disclosure
 * of the Licensed Deliverables to any third party without the express
 * written consent of NVIDIA is prohibited.
 *
 * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
 * LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE
 * SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE.  IT IS
 * PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND.
 * NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED
 * DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY,
 * NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE.
 * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE
 * LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY
 * SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY
 * DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS,
 * WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS
 * ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE
 * OF THESE LICENSED DELIVERABLES.
 *
 * U.S. Government End Users.  These Licensed Deliverables are a
 * "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT
 * 1995), consisting of "commercial computer software" and "commercial
 * computer software documentation" as such terms are used in 48
 * C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government
 * only as a commercial end item.  Consistent with 48 C.F.R.12.212 and
 * 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all
 * U.S. Government End Users acquire the Licensed Deliverables with
 * only those rights set forth herein.
 *
 * Any use of the Licensed Deliverables in individual and commercial
 * software must include, in the user documentation and internal
 * comments to the code, the above Disclaimer and U.S. Government End
 * Users Notice.
 */

#ifndef __cuda_cuda_h__
#define __cuda_cuda_h__




#include <stdlib.h>
#ifdef _MSC_VER
typedef unsigned __int32 cuuint32_t;
typedef unsigned __int64 cuuint64_t;
#else
#include <stdint.h>
typedef uint32_t cuuint32_t;
typedef uint64_t cuuint64_t;
#endif

#if defined(__CUDA_API_VERSION_INTERNAL) || defined(__DOXYGEN_ONLY__) || defined(CUDA_ENABLE_DEPRECATED)
#define __CUDA_DEPRECATED
#elif defined(_MSC_VER)
#define __CUDA_DEPRECATED __declspec(deprecated)
#elif defined(__GNUC__)
#define __CUDA_DEPRECATED __attribute__((deprecated))
#else
#define __CUDA_DEPRECATED
#endif

#if defined(CUDA_FORCE_API_VERSION)
#error "CUDA_FORCE_API_VERSION is no longer supported."
#endif

#if defined(__CUDA_API_VERSION_INTERNAL) || defined(CUDA_API_PER_THREAD_DEFAULT_STREAM)
    #define __CUDA_API_PER_THREAD_DEFAULT_STREAM
    #define __CUDA_API_PTDS(api) api ## _ptds
    #define __CUDA_API_PTSZ(api) api ## _ptsz
#else
    #define __CUDA_API_PTDS(api) api
    #define __CUDA_API_PTSZ(api) api
#endif

#define cuDeviceTotalMem                    cuDeviceTotalMem_v2
#define cuCtxCreate                         cuCtxCreate_v2
#define cuCtxCreate_v3                      cuCtxCreate_v3
#define cuCtxCreate_v4                      cuCtxCreate_v4
#define cuModuleGetGlobal                   cuModuleGetGlobal_v2
#define cuMemGetInfo                        cuMemGetInfo_v2
#define cuMemAlloc                          cuMemAlloc_v2
#define cuMemAllocPitch                     cuMemAllocPitch_v2
#define cuMemFree                           cuMemFree_v2
#define cuMemGetAddressRange                cuMemGetAddressRange_v2
#define cuMemAllocHost                      cuMemAllocHost_v2
#define cuMemHostGetDevicePointer           cuMemHostGetDevicePointer_v2
#define cuMemcpyHtoD                        __CUDA_API_PTDS(cuMemcpyHtoD_v2)
#define cuMemcpyDtoH                        __CUDA_API_PTDS(cuMemcpyDtoH_v2)
#define cuMemcpyDtoD                        __CUDA_API_PTDS(cuMemcpyDtoD_v2)
#define cuMemcpyDtoA                        __CUDA_API_PTDS(cuMemcpyDtoA_v2)
#define cuMemcpyAtoD                        __CUDA_API_PTDS(cuMemcpyAtoD_v2)
#define cuMemcpyHtoA                        __CUDA_API_PTDS(cuMemcpyHtoA_v2)
#define cuMemcpyAtoH                        __CUDA_API_PTDS(cuMemcpyAtoH_v2)
#define cuMemcpyAtoA                        __CUDA_API_PTDS(cuMemcpyAtoA_v2)
#define cuMemcpyHtoAAsync                   __CUDA_API_PTSZ(cuMemcpyHtoAAsync_v2)
#define cuMemcpyAtoHAsync                   __CUDA_API_PTSZ(cuMemcpyAtoHAsync_v2)
#define cuMemcpy2D                          __CUDA_API_PTDS(cuMemcpy2D_v2)
#define cuMemcpy2DUnaligned                 __CUDA_API_PTDS(cuMemcpy2DUnaligned_v2)
#define cuMemcpy3D                          __CUDA_API_PTDS(cuMemcpy3D_v2)
#define cuMemcpyHtoDAsync                   __CUDA_API_PTSZ(cuMemcpyHtoDAsync_v2)
#define cuMemcpyDtoHAsync                   __CUDA_API_PTSZ(cuMemcpyDtoHAsync_v2)
#define cuMemcpyDtoDAsync                   __CUDA_API_PTSZ(cuMemcpyDtoDAsync_v2)
#define cuMemcpy2DAsync                     __CUDA_API_PTSZ(cuMemcpy2DAsync_v2)
#define cuMemcpy3DAsync                     __CUDA_API_PTSZ(cuMemcpy3DAsync_v2)
#define cuMemcpyBatchAsync                  __CUDA_API_PTSZ(cuMemcpyBatchAsync)
#define cuMemcpy3DBatchAsync                __CUDA_API_PTSZ(cuMemcpy3DBatchAsync)
#define cuMemsetD8                          __CUDA_API_PTDS(cuMemsetD8_v2)
#define cuMemsetD16                         __CUDA_API_PTDS(cuMemsetD16_v2)
#define cuMemsetD32                         __CUDA_API_PTDS(cuMemsetD32_v2)
#define cuMemsetD2D8                        __CUDA_API_PTDS(cuMemsetD2D8_v2)
#define cuMemsetD2D16                       __CUDA_API_PTDS(cuMemsetD2D16_v2)
#define cuMemsetD2D32                       __CUDA_API_PTDS(cuMemsetD2D32_v2)
#define cuArrayCreate                       cuArrayCreate_v2
#define cuArrayGetDescriptor                cuArrayGetDescriptor_v2
#define cuArray3DCreate                     cuArray3DCreate_v2
#define cuArray3DGetDescriptor              cuArray3DGetDescriptor_v2
#define cuTexRefSetAddress                  cuTexRefSetAddress_v2
#define cuTexRefGetAddress                  cuTexRefGetAddress_v2
#define cuGraphicsResourceGetMappedPointer  cuGraphicsResourceGetMappedPointer_v2
#define cuCtxDestroy                        cuCtxDestroy_v2
#define cuCtxPopCurrent                     cuCtxPopCurrent_v2
#define cuCtxPushCurrent                    cuCtxPushCurrent_v2
#define cuStreamDestroy                     cuStreamDestroy_v2
#define cuEventDestroy                      cuEventDestroy_v2
#define cuTexRefSetAddress2D                cuTexRefSetAddress2D_v3
#define cuLinkCreate                        cuLinkCreate_v2
#define cuLinkAddData                       cuLinkAddData_v2
#define cuLinkAddFile                       cuLinkAddFile_v2
#define cuMemHostRegister                   cuMemHostRegister_v2
#define cuGraphicsResourceSetMapFlags       cuGraphicsResourceSetMapFlags_v2
#define cuStreamBeginCapture                __CUDA_API_PTSZ(cuStreamBeginCapture_v2)
#define cuDevicePrimaryCtxRelease           cuDevicePrimaryCtxRelease_v2
#define cuDevicePrimaryCtxReset             cuDevicePrimaryCtxReset_v2
#define cuDevicePrimaryCtxSetFlags          cuDevicePrimaryCtxSetFlags_v2
#define cuDeviceGetUuid_v2                  cuDeviceGetUuid_v2
#define cuIpcOpenMemHandle                  cuIpcOpenMemHandle_v2

#define cuGraphInstantiate                  cuGraphInstantiateWithFlags

#define cuGraphExecUpdate                   cuGraphExecUpdate_v2 
#define cuGetProcAddress                    cuGetProcAddress_v2
#define cuGraphAddKernelNode                cuGraphAddKernelNode_v2
#define cuGraphKernelNodeGetParams          cuGraphKernelNodeGetParams_v2
#define cuGraphKernelNodeSetParams          cuGraphKernelNodeSetParams_v2
#define cuGraphExecKernelNodeSetParams      cuGraphExecKernelNodeSetParams_v2

#define cuStreamWriteValue32                __CUDA_API_PTSZ(cuStreamWriteValue32_v2)
#define cuStreamWaitValue32                 __CUDA_API_PTSZ(cuStreamWaitValue32_v2)
#define cuStreamWriteValue64                __CUDA_API_PTSZ(cuStreamWriteValue64_v2)
#define cuStreamWaitValue64                 __CUDA_API_PTSZ(cuStreamWaitValue64_v2)
#define cuStreamBatchMemOp                  __CUDA_API_PTSZ(cuStreamBatchMemOp_v2)
#define cuStreamGetCaptureInfo              __CUDA_API_PTSZ(cuStreamGetCaptureInfo_v2)
#define cuStreamGetCaptureInfo_v2           __CUDA_API_PTSZ(cuStreamGetCaptureInfo_v2)

#if defined(__CUDA_API_PER_THREAD_DEFAULT_STREAM)
    #define cuMemcpy                            __CUDA_API_PTDS(cuMemcpy)
    #define cuMemcpyAsync                       __CUDA_API_PTSZ(cuMemcpyAsync)
    #define cuMemcpyPeer                        __CUDA_API_PTDS(cuMemcpyPeer)
    #define cuMemcpyPeerAsync                   __CUDA_API_PTSZ(cuMemcpyPeerAsync)
    #define cuMemcpy3DPeer                      __CUDA_API_PTDS(cuMemcpy3DPeer)
    #define cuMemcpy3DPeerAsync                 __CUDA_API_PTSZ(cuMemcpy3DPeerAsync)
    #define cuMemPrefetchAsync                  __CUDA_API_PTSZ(cuMemPrefetchAsync)
    #define cuMemPrefetchAsync_v2               __CUDA_API_PTSZ(cuMemPrefetchAsync_v2)

    #define cuMemsetD8Async                     __CUDA_API_PTSZ(cuMemsetD8Async)
    #define cuMemsetD16Async                    __CUDA_API_PTSZ(cuMemsetD16Async)
    #define cuMemsetD32Async                    __CUDA_API_PTSZ(cuMemsetD32Async)
    #define cuMemsetD2D8Async                   __CUDA_API_PTSZ(cuMemsetD2D8Async)
    #define cuMemsetD2D16Async                  __CUDA_API_PTSZ(cuMemsetD2D16Async)
    #define cuMemsetD2D32Async                  __CUDA_API_PTSZ(cuMemsetD2D32Async)

    #define cuStreamGetPriority                 __CUDA_API_PTSZ(cuStreamGetPriority)
    #define cuStreamGetId                       __CUDA_API_PTSZ(cuStreamGetId)
    #define cuStreamGetFlags                    __CUDA_API_PTSZ(cuStreamGetFlags)
    #define cuStreamGetDevice                   __CUDA_API_PTSZ(cuStreamGetDevice)
    #define cuStreamGetCtx                      __CUDA_API_PTSZ(cuStreamGetCtx)
    #define cuStreamGetCtx_v2                   __CUDA_API_PTSZ(cuStreamGetCtx_v2)
    #define cuStreamWaitEvent                   __CUDA_API_PTSZ(cuStreamWaitEvent)
    #define cuStreamEndCapture                  __CUDA_API_PTSZ(cuStreamEndCapture)
    #define cuStreamIsCapturing                 __CUDA_API_PTSZ(cuStreamIsCapturing)
    #define cuStreamGetCaptureInfo_v3           __CUDA_API_PTSZ(cuStreamGetCaptureInfo_v3)
    #define cuStreamUpdateCaptureDependencies   __CUDA_API_PTSZ(cuStreamUpdateCaptureDependencies)
    #define cuStreamUpdateCaptureDependencies_v2 __CUDA_API_PTSZ(cuStreamUpdateCaptureDependencies_v2)
    #define cuStreamAddCallback                 __CUDA_API_PTSZ(cuStreamAddCallback)
    #define cuStreamAttachMemAsync              __CUDA_API_PTSZ(cuStreamAttachMemAsync)
    #define cuStreamQuery                       __CUDA_API_PTSZ(cuStreamQuery)
    #define cuStreamSynchronize                 __CUDA_API_PTSZ(cuStreamSynchronize)
    #define cuEventRecord                       __CUDA_API_PTSZ(cuEventRecord)
    #define cuEventRecordWithFlags              __CUDA_API_PTSZ(cuEventRecordWithFlags)
    #define cuLaunchKernel                      __CUDA_API_PTSZ(cuLaunchKernel)
    #define cuLaunchKernelEx                    __CUDA_API_PTSZ(cuLaunchKernelEx)
    #define cuLaunchHostFunc                    __CUDA_API_PTSZ(cuLaunchHostFunc)
    #define cuGraphicsMapResources              __CUDA_API_PTSZ(cuGraphicsMapResources)
    #define cuGraphicsUnmapResources            __CUDA_API_PTSZ(cuGraphicsUnmapResources)


    #define cuLaunchCooperativeKernel           __CUDA_API_PTSZ(cuLaunchCooperativeKernel)

    #define cuSignalExternalSemaphoresAsync     __CUDA_API_PTSZ(cuSignalExternalSemaphoresAsync)
    #define cuWaitExternalSemaphoresAsync       __CUDA_API_PTSZ(cuWaitExternalSemaphoresAsync)

    #define cuGraphInstantiateWithParams        __CUDA_API_PTSZ(cuGraphInstantiateWithParams)
    #define cuGraphUpload                       __CUDA_API_PTSZ(cuGraphUpload)
    #define cuGraphLaunch                       __CUDA_API_PTSZ(cuGraphLaunch)
    #define cuStreamCopyAttributes              __CUDA_API_PTSZ(cuStreamCopyAttributes)
    #define cuStreamGetAttribute                __CUDA_API_PTSZ(cuStreamGetAttribute)
    #define cuStreamSetAttribute                __CUDA_API_PTSZ(cuStreamSetAttribute)
    #define cuMemMapArrayAsync                  __CUDA_API_PTSZ(cuMemMapArrayAsync)

    #define cuMemFreeAsync                      __CUDA_API_PTSZ(cuMemFreeAsync)
    #define cuMemAllocAsync                     __CUDA_API_PTSZ(cuMemAllocAsync)
    #define cuMemAllocFromPoolAsync             __CUDA_API_PTSZ(cuMemAllocFromPoolAsync)

    #define cuStreamBeginCaptureToGraph         __CUDA_API_PTSZ(cuStreamBeginCaptureToGraph)

#endif

#define cuMemBatchDecompressAsync               __CUDA_API_PTSZ(cuMemBatchDecompressAsync)

/**
 * \file cuda.h
 * \brief Header file for the CUDA Toolkit application programming interface.
 *
 * \file cudaGL.h
 * \brief Header file for the OpenGL interoperability functions of the
 * low-level CUDA driver application programming interface.
 *
 * \file cudaD3D9.h
 * \brief Header file for the Direct3D 9 interoperability functions of the
 * low-level CUDA driver application programming interface.
 */

/**
 * \defgroup CUDA_TYPES Data types used by CUDA driver
 * @{
 */

/**
 * CUDA API version number
 */
#define CUDA_VERSION 12080

#ifdef __cplusplus
extern "C" {
#endif

/**
 * CUDA device pointer
 * CUdeviceptr is defined as an unsigned integer type whose size matches the size of a pointer on the target platform.
 */
#if defined(_WIN64) || defined(__LP64__)
typedef unsigned long long CUdeviceptr_v2;
#else
typedef unsigned int CUdeviceptr_v2;
#endif
typedef CUdeviceptr_v2 CUdeviceptr;                          /**< CUDA device pointer */

typedef int CUdevice_v1;                                     /**< CUDA device */
typedef CUdevice_v1 CUdevice;                                /**< CUDA device */
typedef struct CUctx_st *CUcontext;                          /**< A regular context handle */
typedef struct CUmod_st *CUmodule;                           /**< CUDA module */
typedef struct CUfunc_st *CUfunction;                        /**< CUDA function */
typedef struct CUlib_st *CUlibrary;                          /**< CUDA library */
typedef struct CUkern_st *CUkernel;                          /**< CUDA kernel */
typedef struct CUarray_st *CUarray;                          /**< CUDA array */
typedef struct CUmipmappedArray_st *CUmipmappedArray;        /**< CUDA mipmapped array */
typedef struct CUtexref_st *CUtexref;                        /**< CUDA texture reference */
typedef struct CUsurfref_st *CUsurfref;                      /**< CUDA surface reference */
typedef struct CUevent_st *CUevent;                          /**< CUDA event */
typedef struct CUstream_st *CUstream;                        /**< CUDA stream */
typedef struct CUgraphicsResource_st *CUgraphicsResource;    /**< CUDA graphics interop resource */
typedef unsigned long long CUtexObject_v1;                   /**< An opaque value that represents a CUDA texture object */
typedef CUtexObject_v1 CUtexObject;                          /**< An opaque value that represents a CUDA texture object */
typedef unsigned long long CUsurfObject_v1;                  /**< An opaque value that represents a CUDA surface object */
typedef CUsurfObject_v1 CUsurfObject;                        /**< An opaque value that represents a CUDA surface object */ 
typedef struct CUextMemory_st *CUexternalMemory;             /**< CUDA external memory */
typedef struct CUextSemaphore_st *CUexternalSemaphore;       /**< CUDA external semaphore */
typedef struct CUgraph_st *CUgraph;                          /**< CUDA graph */
typedef struct CUgraphNode_st *CUgraphNode;                  /**< CUDA graph node */
typedef struct CUgraphExec_st *CUgraphExec;                  /**< CUDA executable graph */
typedef struct CUmemPoolHandle_st *CUmemoryPool;             /**< CUDA memory pool */
typedef struct CUuserObject_st *CUuserObject;                /**< CUDA user object for graphs */
typedef cuuint64_t CUgraphConditionalHandle; /**< CUDA graph conditional handle */
typedef struct CUgraphDeviceUpdatableNode_st *CUgraphDeviceNode; /**< CUDA graph device node handle */
typedef struct CUasyncCallbackEntry_st *CUasyncCallbackHandle;            /**< CUDA async notification callback handle */
/*!
 * \typedef typedef struct CUgreenCtx_st* CUgreenCtx
 * A green context handle. This handle can be used safely from only one CPU thread at a time.
 * Created via ::cuGreenCtxCreate
 */
typedef struct CUgreenCtx_st *CUgreenCtx;

#ifndef CU_UUID_HAS_BEEN_DEFINED
#define CU_UUID_HAS_BEEN_DEFINED
typedef struct CUuuid_st {                                /**< CUDA definition of UUID */
    char bytes[16];
} CUuuid;
#endif

/**
 * CUDA IPC handle size
 */
#define CU_IPC_HANDLE_SIZE 64

/**
 * Fabric handle - An opaque handle representing a memory allocation
 * that can be exported to processes in same or different nodes. For IPC
 * between processes on different nodes they must be connected via the
 * NVSwitch fabric.
 */
typedef struct CUmemFabricHandle_st {
    unsigned char data[CU_IPC_HANDLE_SIZE];
} CUmemFabricHandle_v1;
typedef CUmemFabricHandle_v1 CUmemFabricHandle;

/**
 * CUDA IPC event handle
 */
typedef struct CUipcEventHandle_st {
    char reserved[CU_IPC_HANDLE_SIZE];
} CUipcEventHandle_v1;
typedef CUipcEventHandle_v1 CUipcEventHandle;

/**
 * CUDA IPC mem handle
 */
typedef struct CUipcMemHandle_st {
    char reserved[CU_IPC_HANDLE_SIZE];
} CUipcMemHandle_v1;
typedef CUipcMemHandle_v1 CUipcMemHandle;

/**
 * CUDA Ipc Mem Flags
 */
typedef enum CUipcMem_flags_enum {
    CU_IPC_MEM_LAZY_ENABLE_PEER_ACCESS = 0x1 /**< Automatically enable peer access between remote devices as needed */
} CUipcMem_flags;


/**
 * CUDA Mem Attach Flags
 */
typedef enum CUmemAttach_flags_enum {
    CU_MEM_ATTACH_GLOBAL = 0x1, /**< Memory can be accessed by any stream on any device */
    CU_MEM_ATTACH_HOST   = 0x2, /**< Memory cannot be accessed by any stream on any device */
    CU_MEM_ATTACH_SINGLE = 0x4  /**< Memory can only be accessed by a single stream on the associated device */
} CUmemAttach_flags;

/**
 * Context creation flags
 */
typedef enum CUctx_flags_enum {
    CU_CTX_SCHED_AUTO          = 0x00, /**< Automatic scheduling */
    CU_CTX_SCHED_SPIN          = 0x01, /**< Set spin as default scheduling */
    CU_CTX_SCHED_YIELD         = 0x02, /**< Set yield as default scheduling */
    CU_CTX_SCHED_BLOCKING_SYNC = 0x04, /**< Set blocking synchronization as default scheduling */
    CU_CTX_BLOCKING_SYNC       = 0x04, /**< Set blocking synchronization as default scheduling
                                         *  \deprecated This flag was deprecated as of CUDA 4.0
                                         *  and was replaced with ::CU_CTX_SCHED_BLOCKING_SYNC. */
    CU_CTX_SCHED_MASK          = 0x07,
    CU_CTX_MAP_HOST            = 0x08, /**< \deprecated This flag was deprecated as of CUDA 11.0 
                                         *  and it no longer has any effect. All contexts 
                                         *  as of CUDA 3.2 behave as though the flag is enabled. */
    CU_CTX_LMEM_RESIZE_TO_MAX  = 0x10, /**< Keep local memory allocation after launch */
    CU_CTX_COREDUMP_ENABLE     = 0x20, /**< Trigger coredumps from exceptions in this context */
    CU_CTX_USER_COREDUMP_ENABLE= 0x40, /**< Enable user pipe to trigger coredumps in this context */
    CU_CTX_SYNC_MEMOPS         = 0x80, /**< Ensure synchronous memory operations on this context will synchronize */
    CU_CTX_FLAGS_MASK          = 0xFF
} CUctx_flags;

/**
 * Event sched flags
 */
typedef enum CUevent_sched_flags_enum {
    CU_EVENT_SCHED_AUTO = 0x00, /**< Automatic scheduling */
    CU_EVENT_SCHED_SPIN = 0x01, /**< Set spin as default scheduling */
    CU_EVENT_SCHED_YIELD = 0x02, /**< Set yield as default scheduling */
    CU_EVENT_SCHED_BLOCKING_SYNC = 0x04, /**< Set blocking synchronization as default scheduling */
} CUevent_sched_flags;

/**
 * NVCL event scheduling flags
 */
typedef enum cl_event_flags_enum {
    NVCL_EVENT_SCHED_AUTO = 0x00, /**< Automatic scheduling */
    NVCL_EVENT_SCHED_SPIN = 0x01, /**< Set spin as default scheduling */
    NVCL_EVENT_SCHED_YIELD = 0x02, /**< Set yield as default scheduling */
    NVCL_EVENT_SCHED_BLOCKING_SYNC = 0x04, /**< Set blocking synchronization as default scheduling */
} cl_event_flags;

/**
 * NVCL context scheduling flags
 */
typedef enum cl_context_flags_enum {
    NVCL_CTX_SCHED_AUTO = 0x00, /**< Automatic scheduling */
    NVCL_CTX_SCHED_SPIN = 0x01, /**< Set spin as default scheduling */
    NVCL_CTX_SCHED_YIELD = 0x02, /**< Set yield as default scheduling */
    NVCL_CTX_SCHED_BLOCKING_SYNC = 0x04, /**< Set blocking synchronization as default scheduling */
} cl_context_flags;


/**
 * Stream creation flags
 */
typedef enum CUstream_flags_enum {
    CU_STREAM_DEFAULT             = 0x0, /**< Default stream flag */
    CU_STREAM_NON_BLOCKING        = 0x1  /**< Stream does not synchronize with stream 0 (the NULL stream) */
} CUstream_flags;

/**
 * Legacy stream handle
 *
 * Stream handle that can be passed as a CUstream to use an implicit stream
 * with legacy synchronization behavior.
 *
 * See details of the \link_sync_behavior
 */
#define CU_STREAM_LEGACY     ((CUstream)0x1)

/**
 * Per-thread stream handle
 *
 * Stream handle that can be passed as a CUstream to use an implicit stream
 * with per-thread synchronization behavior.
 *
 * See details of the \link_sync_behavior
 */
#define CU_STREAM_PER_THREAD ((CUstream)0x2)

/**
 * Event creation flags
 */
typedef enum CUevent_flags_enum {
    CU_EVENT_DEFAULT        = 0x0, /**< Default event flag */
    CU_EVENT_BLOCKING_SYNC  = 0x1, /**< Event uses blocking synchronization */
    CU_EVENT_DISABLE_TIMING = 0x2, /**< Event will not record timing data */
    CU_EVENT_INTERPROCESS   = 0x4  /**< Event is suitable for interprocess use. CU_EVENT_DISABLE_TIMING must be set */
} CUevent_flags;

/**
 * Event record flags
 */
typedef enum CUevent_record_flags_enum {
    CU_EVENT_RECORD_DEFAULT  = 0x0, /**< Default event record flag */
    CU_EVENT_RECORD_EXTERNAL = 0x1  /**< When using stream capture, create an event record node
                                      *  instead of the default behavior.  This flag is invalid
                                      *  when used outside of capture. */
} CUevent_record_flags;

/**
 * Event wait flags
 */
typedef enum CUevent_wait_flags_enum {
    CU_EVENT_WAIT_DEFAULT  = 0x0, /**< Default event wait flag */
    CU_EVENT_WAIT_EXTERNAL = 0x1  /**< When using stream capture, create an event wait node
                                    *  instead of the default behavior.  This flag is invalid
                                    *  when used outside of capture.*/
} CUevent_wait_flags;

/**
 * Flags for ::cuStreamWaitValue32 and ::cuStreamWaitValue64
 */
typedef enum CUstreamWaitValue_flags_enum {
    CU_STREAM_WAIT_VALUE_GEQ   = 0x0,   /**< Wait until (int32_t)(*addr - value) >= 0 (or int64_t for 64 bit
                                             values). Note this is a cyclic comparison which ignores wraparound.
                                             (Default behavior.) */
    CU_STREAM_WAIT_VALUE_EQ    = 0x1,   /**< Wait until *addr == value. */
    CU_STREAM_WAIT_VALUE_AND   = 0x2,   /**< Wait until (*addr & value) != 0. */
    CU_STREAM_WAIT_VALUE_NOR   = 0x3,   /**< Wait until ~(*addr | value) != 0. Support for this operation can be
                                             queried with ::cuDeviceGetAttribute() and
                                             ::CU_DEVICE_ATTRIBUTE_CAN_USE_STREAM_WAIT_VALUE_NOR.*/
    CU_STREAM_WAIT_VALUE_FLUSH = 1<<30  /**< Follow the wait operation with a flush of outstanding remote writes. This
                                             means that, if a remote write operation is guaranteed to have reached the
                                             device before the wait can be satisfied, that write is guaranteed to be
                                             visible to downstream device work. The device is permitted to reorder
                                             remote writes internally. For example, this flag would be required if
                                             two remote writes arrive in a defined order, the wait is satisfied by the
                                             second write, and downstream work needs to observe the first write.
                                             Support for this operation is restricted to selected platforms and can be
                                             queried with ::CU_DEVICE_ATTRIBUTE_CAN_FLUSH_REMOTE_WRITES.*/
} CUstreamWaitValue_flags;

/**
 * Flags for ::cuStreamWriteValue32
 */
typedef enum CUstreamWriteValue_flags_enum {
    CU_STREAM_WRITE_VALUE_DEFAULT           = 0x0, /**< Default behavior */
    CU_STREAM_WRITE_VALUE_NO_MEMORY_BARRIER = 0x1  /**< Permits the write to be reordered with writes which were issued
                                                        before it, as a performance optimization. Normally,
                                                        ::cuStreamWriteValue32 will provide a memory fence before the
                                                        write, which has similar semantics to
                                                        __threadfence_system() but is scoped to the stream
                                                        rather than a CUDA thread.
                                                        This flag is not supported in the v2 API. */
} CUstreamWriteValue_flags;

/**
 * Operations for ::cuStreamBatchMemOp
 */
typedef enum CUstreamBatchMemOpType_enum {
    CU_STREAM_MEM_OP_WAIT_VALUE_32  = 1,     /**< Represents a ::cuStreamWaitValue32 operation */
    CU_STREAM_MEM_OP_WRITE_VALUE_32 = 2,     /**< Represents a ::cuStreamWriteValue32 operation */
    CU_STREAM_MEM_OP_WAIT_VALUE_64  = 4,     /**< Represents a ::cuStreamWaitValue64 operation */
    CU_STREAM_MEM_OP_WRITE_VALUE_64 = 5,     /**< Represents a ::cuStreamWriteValue64 operation */
    CU_STREAM_MEM_OP_BARRIER = 6,            /**< Insert a memory barrier of the specified type */ 
    CU_STREAM_MEM_OP_FLUSH_REMOTE_WRITES = 3 /**< This has the same effect as ::CU_STREAM_WAIT_VALUE_FLUSH, but as a
                                                  standalone operation. */
} CUstreamBatchMemOpType;

/**
 * Flags for ::cuStreamMemoryBarrier
 */
typedef enum CUstreamMemoryBarrier_flags_enum {
    CU_STREAM_MEMORY_BARRIER_TYPE_SYS = 0x0, /**< System-wide memory barrier. */
    CU_STREAM_MEMORY_BARRIER_TYPE_GPU = 0x1 /**< Limit memory barrier scope to the GPU. */
} CUstreamMemoryBarrier_flags;

/**
 * Per-operation parameters for ::cuStreamBatchMemOp
 */
typedef union CUstreamBatchMemOpParams_union {
    CUstreamBatchMemOpType operation;
    struct CUstreamMemOpWaitValueParams_st {
        CUstreamBatchMemOpType operation;
        CUdeviceptr address;
        union {
            cuuint32_t value;
            cuuint64_t value64;
        };
        unsigned int flags;
        CUdeviceptr alias; /**< For driver internal use. Initial value is unimportant. */
    } waitValue;
    struct CUstreamMemOpWriteValueParams_st {
        CUstreamBatchMemOpType operation;
        CUdeviceptr address;
        union {
            cuuint32_t value;
            cuuint64_t value64;
        };
        unsigned int flags;
        CUdeviceptr alias; /**< For driver internal use. Initial value is unimportant. */
    } writeValue;
    struct CUstreamMemOpFlushRemoteWritesParams_st {
        CUstreamBatchMemOpType operation;
        unsigned int flags;
    } flushRemoteWrites;
    struct CUstreamMemOpMemoryBarrierParams_st { /**< Only supported in the _v2 API */
        CUstreamBatchMemOpType operation;
        unsigned int flags;
    } memoryBarrier;
    cuuint64_t pad[6];
} CUstreamBatchMemOpParams_v1;
typedef CUstreamBatchMemOpParams_v1 CUstreamBatchMemOpParams;

typedef struct CUDA_BATCH_MEM_OP_NODE_PARAMS_v1_st {
    CUcontext ctx;
    unsigned int count;
    CUstreamBatchMemOpParams *paramArray;
    unsigned int flags;
} CUDA_BATCH_MEM_OP_NODE_PARAMS_v1;
typedef CUDA_BATCH_MEM_OP_NODE_PARAMS_v1 CUDA_BATCH_MEM_OP_NODE_PARAMS;

/**
 * Batch memory operation node parameters
 */
typedef struct CUDA_BATCH_MEM_OP_NODE_PARAMS_v2_st {
    CUcontext ctx;                        /**< Context to use for the operations. */
    unsigned int count;                   /**< Number of operations in paramArray. */
    CUstreamBatchMemOpParams *paramArray; /**< Array of batch memory operations. */
    unsigned int flags;                   /**< Flags to control the node. */
} CUDA_BATCH_MEM_OP_NODE_PARAMS_v2;

/**
 * Occupancy calculator flag
 */
typedef enum CUoccupancy_flags_enum {
    CU_OCCUPANCY_DEFAULT                  = 0x0, /**< Default behavior */
    CU_OCCUPANCY_DISABLE_CACHING_OVERRIDE = 0x1  /**< Assume global caching is enabled and cannot be automatically turned off */
} CUoccupancy_flags;

/**
 * Flags for ::cuStreamUpdateCaptureDependencies
 */
typedef enum CUstreamUpdateCaptureDependencies_flags_enum {
    CU_STREAM_ADD_CAPTURE_DEPENDENCIES = 0x0, /**< Add new nodes to the dependency set */
    CU_STREAM_SET_CAPTURE_DEPENDENCIES = 0x1  /**< Replace the dependency set with the new nodes */
} CUstreamUpdateCaptureDependencies_flags;

/**
* Types of async notification that can be sent
*/
typedef enum CUasyncNotificationType_enum {
    CU_ASYNC_NOTIFICATION_TYPE_OVER_BUDGET = 0x1
} CUasyncNotificationType;

/**
* Information passed to the user via the async notification callback
*/
typedef struct CUasyncNotificationInfo_st {
    CUasyncNotificationType type;
    union {
        struct {
            unsigned long long bytesOverBudget;
        } overBudget;
    } info;
} CUasyncNotificationInfo;

/**
 * CUDA async notification callback
 * \param info Information describing what actions to take as a result of this trim notification.
 * \param userData Pointer to user defined data provided at registration.
 * \param callback The callback handle associated with this specific callback.
 */
typedef void (*CUasyncCallback)(CUasyncNotificationInfo *info, void *userData, CUasyncCallbackHandle callback);

/**
 * Array formats
 */
typedef enum CUarray_format_enum {
    CU_AD_FORMAT_UNSIGNED_INT8            = 0x01, /**< Unsigned 8-bit integers */
    CU_AD_FORMAT_UNSIGNED_INT16           = 0x02, /**< Unsigned 16-bit integers */
    CU_AD_FORMAT_UNSIGNED_INT32           = 0x03, /**< Unsigned 32-bit integers */
    CU_AD_FORMAT_SIGNED_INT8              = 0x08, /**< Signed 8-bit integers */
    CU_AD_FORMAT_SIGNED_INT16             = 0x09, /**< Signed 16-bit integers */
    CU_AD_FORMAT_SIGNED_INT32             = 0x0a, /**< Signed 32-bit integers */
    CU_AD_FORMAT_HALF                     = 0x10, /**< 16-bit floating point */
    CU_AD_FORMAT_FLOAT                    = 0x20, /**< 32-bit floating point */
    CU_AD_FORMAT_NV12                     = 0xb0, /**< 8-bit YUV planar format, with 4:2:0 sampling */
    CU_AD_FORMAT_UNORM_INT8X1             = 0xc0, /**< 1 channel unsigned 8-bit normalized integer */
    CU_AD_FORMAT_UNORM_INT8X2             = 0xc1, /**< 2 channel unsigned 8-bit normalized integer */
    CU_AD_FORMAT_UNORM_INT8X4             = 0xc2, /**< 4 channel unsigned 8-bit normalized integer */
    CU_AD_FORMAT_UNORM_INT16X1            = 0xc3, /**< 1 channel unsigned 16-bit normalized integer */
    CU_AD_FORMAT_UNORM_INT16X2            = 0xc4, /**< 2 channel unsigned 16-bit normalized integer */
    CU_AD_FORMAT_UNORM_INT16X4            = 0xc5, /**< 4 channel unsigned 16-bit normalized integer */
    CU_AD_FORMAT_SNORM_INT8X1             = 0xc6, /**< 1 channel signed 8-bit normalized integer */
    CU_AD_FORMAT_SNORM_INT8X2             = 0xc7, /**< 2 channel signed 8-bit normalized integer */
    CU_AD_FORMAT_SNORM_INT8X4             = 0xc8, /**< 4 channel signed 8-bit normalized integer */
    CU_AD_FORMAT_SNORM_INT16X1            = 0xc9, /**< 1 channel signed 16-bit normalized integer */
    CU_AD_FORMAT_SNORM_INT16X2            = 0xca, /**< 2 channel signed 16-bit normalized integer */
    CU_AD_FORMAT_SNORM_INT16X4            = 0xcb, /**< 4 channel signed 16-bit normalized integer */
    CU_AD_FORMAT_BC1_UNORM                = 0x91, /**< 4 channel unsigned normalized block-compressed (BC1 compression) format */
    CU_AD_FORMAT_BC1_UNORM_SRGB           = 0x92, /**< 4 channel unsigned normalized block-compressed (BC1 compression) format with sRGB encoding*/
    CU_AD_FORMAT_BC2_UNORM                = 0x93, /**< 4 channel unsigned normalized block-compressed (BC2 compression) format */
    CU_AD_FORMAT_BC2_UNORM_SRGB           = 0x94, /**< 4 channel unsigned normalized block-compressed (BC2 compression) format with sRGB encoding*/
    CU_AD_FORMAT_BC3_UNORM                = 0x95, /**< 4 channel unsigned normalized block-compressed (BC3 compression) format */
    CU_AD_FORMAT_BC3_UNORM_SRGB           = 0x96, /**< 4 channel unsigned normalized block-compressed (BC3 compression) format with sRGB encoding*/
    CU_AD_FORMAT_BC4_UNORM                = 0x97, /**< 1 channel unsigned normalized block-compressed (BC4 compression) format */
    CU_AD_FORMAT_BC4_SNORM                = 0x98, /**< 1 channel signed normalized block-compressed (BC4 compression) format */
    CU_AD_FORMAT_BC5_UNORM                = 0x99, /**< 2 channel unsigned normalized block-compressed (BC5 compression) format */
    CU_AD_FORMAT_BC5_SNORM                = 0x9a, /**< 2 channel signed normalized block-compressed (BC5 compression) format */
    CU_AD_FORMAT_BC6H_UF16                = 0x9b, /**< 3 channel unsigned half-float block-compressed (BC6H compression) format */
    CU_AD_FORMAT_BC6H_SF16                = 0x9c, /**< 3 channel signed half-float block-compressed (BC6H compression) format */
    CU_AD_FORMAT_BC7_UNORM                = 0x9d, /**< 4 channel unsigned normalized block-compressed (BC7 compression) format */
    CU_AD_FORMAT_BC7_UNORM_SRGB           = 0x9e, /**< 4 channel unsigned normalized block-compressed (BC7 compression) format with sRGB encoding */
    CU_AD_FORMAT_P010                     = 0x9f, /**< 10-bit YUV planar format, with 4:2:0 sampling */
    CU_AD_FORMAT_P016                     = 0xa1, /**< 16-bit YUV planar format, with 4:2:0 sampling */
    CU_AD_FORMAT_NV16                     = 0xa2, /**< 8-bit YUV planar format, with 4:2:2 sampling */
    CU_AD_FORMAT_P210                     = 0xa3, /**< 10-bit YUV planar format, with 4:2:2 sampling */
    CU_AD_FORMAT_P216                     = 0xa4, /**< 16-bit YUV planar format, with 4:2:2 sampling */
    CU_AD_FORMAT_YUY2                     = 0xa5, /**< 2 channel, 8-bit YUV packed planar format, with 4:2:2 sampling */
    CU_AD_FORMAT_Y210                     = 0xa6, /**< 2 channel, 10-bit YUV packed planar format, with 4:2:2 sampling */
    CU_AD_FORMAT_Y216                     = 0xa7, /**< 2 channel, 16-bit YUV packed planar format, with 4:2:2 sampling */
    CU_AD_FORMAT_AYUV                     = 0xa8, /**< 4 channel, 8-bit YUV packed planar format, with 4:4:4 sampling */
    CU_AD_FORMAT_Y410                     = 0xa9, /**< 10-bit YUV packed planar format, with 4:4:4 sampling */
    CU_AD_FORMAT_Y416                     = 0xb1, /**< 4 channel, 12-bit YUV packed planar format, with 4:4:4 sampling */
    CU_AD_FORMAT_Y444_PLANAR8             = 0xb2, /**< 3 channel 8-bit YUV planar format, with 4:4:4 sampling */
    CU_AD_FORMAT_Y444_PLANAR10            = 0xb3, /**< 3 channel 10-bit YUV planar format, with 4:4:4 sampling */
    CU_AD_FORMAT_YUV444_8bit_SemiPlanar   = 0xb4, /**< 3 channel 8-bit YUV semi-planar format, with 4:4:4 sampling */
    CU_AD_FORMAT_YUV444_16bit_SemiPlanar  = 0xb5, /**< 3 channel 16-bit YUV semi-planar format, with 4:4:4 sampling */
    CU_AD_FORMAT_UNORM_INT_101010_2       = 0x50, /**< 4 channel unorm R10G10B10A2 RGB format */
    CU_AD_FORMAT_MAX                      = 0x7FFFFFFF
} CUarray_format;

/**
 * Texture reference addressing modes
 */
typedef enum CUaddress_mode_enum {
    CU_TR_ADDRESS_MODE_WRAP   = 0, /**< Wrapping address mode */
    CU_TR_ADDRESS_MODE_CLAMP  = 1, /**< Clamp to edge address mode */
    CU_TR_ADDRESS_MODE_MIRROR = 2, /**< Mirror address mode */
    CU_TR_ADDRESS_MODE_BORDER = 3  /**< Border address mode */
} CUaddress_mode;

/**
 * Texture reference filtering modes
 */
typedef enum CUfilter_mode_enum {
    CU_TR_FILTER_MODE_POINT  = 0, /**< Point filter mode */
    CU_TR_FILTER_MODE_LINEAR = 1  /**< Linear filter mode */
} CUfilter_mode;

/**
 * Device properties
 */
typedef enum CUdevice_attribute_enum {
    CU_DEVICE_ATTRIBUTE_MAX_THREADS_PER_BLOCK = 1,                          /**< Maximum number of threads per block */
    CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_X = 2,                                /**< Maximum block dimension X */
    CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_Y = 3,                                /**< Maximum block dimension Y */
    CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_Z = 4,                                /**< Maximum block dimension Z */
    CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_X = 5,                                 /**< Maximum grid dimension X */
    CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_Y = 6,                                 /**< Maximum grid dimension Y */
    CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_Z = 7,                                 /**< Maximum grid dimension Z */
    CU_DEVICE_ATTRIBUTE_MAX_SHARED_MEMORY_PER_BLOCK = 8,                    /**< Maximum shared memory available per block in bytes */
    CU_DEVICE_ATTRIBUTE_SHARED_MEMORY_PER_BLOCK = 8,                        /**< Deprecated, use CU_DEVICE_ATTRIBUTE_MAX_SHARED_MEMORY_PER_BLOCK */
    CU_DEVICE_ATTRIBUTE_TOTAL_CONSTANT_MEMORY = 9,                          /**< Memory available on device for __constant__ variables in a CUDA C kernel in bytes */
    CU_DEVICE_ATTRIBUTE_WARP_SIZE = 10,                                     /**< Warp size in threads */
    CU_DEVICE_ATTRIBUTE_MAX_PITCH = 11,                                     /**< Maximum pitch in bytes allowed by memory copies */
    CU_DEVICE_ATTRIBUTE_MAX_REGISTERS_PER_BLOCK = 12,                       /**< Maximum number of 32-bit registers available per block */
    CU_DEVICE_ATTRIBUTE_REGISTERS_PER_BLOCK = 12,                           /**< Deprecated, use CU_DEVICE_ATTRIBUTE_MAX_REGISTERS_PER_BLOCK */
    CU_DEVICE_ATTRIBUTE_CLOCK_RATE = 13,                                    /**< Typical clock frequency in kilohertz */
    CU_DEVICE_ATTRIBUTE_TEXTURE_ALIGNMENT = 14,                             /**< Alignment requirement for textures */
    CU_DEVICE_ATTRIBUTE_GPU_OVERLAP = 15,                                   /**< Device can possibly copy memory and execute a kernel concurrently. Deprecated. Use instead CU_DEVICE_ATTRIBUTE_ASYNC_ENGINE_COUNT. */
    CU_DEVICE_ATTRIBUTE_MULTIPROCESSOR_COUNT = 16,                          /**< Number of multiprocessors on device */
    CU_DEVICE_ATTRIBUTE_KERNEL_EXEC_TIMEOUT = 17,                           /**< Specifies whether there is a run time limit on kernels */
    CU_DEVICE_ATTRIBUTE_INTEGRATED = 18,                                    /**< Device is integrated with host memory */
    CU_DEVICE_ATTRIBUTE_CAN_MAP_HOST_MEMORY = 19,                           /**< Device can map host memory into CUDA address space */
    CU_DEVICE_ATTRIBUTE_COMPUTE_MODE = 20,                                  /**< Compute mode (See ::CUcomputemode for details) */
    CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE1D_WIDTH = 21,                       /**< Maximum 1D texture width */
    CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_WIDTH = 22,                       /**< Maximum 2D texture width */
    CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_HEIGHT = 23,                      /**< Maximum 2D texture height */
    CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE3D_WIDTH = 24,                       /**< Maximum 3D texture width */
    CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE3D_HEIGHT = 25,                      /**< Maximum 3D texture height */
    CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE3D_DEPTH = 26,                       /**< Maximum 3D texture depth */
    CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_LAYERED_WIDTH = 27,               /**< Maximum 2D layered texture width */
    CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_LAYERED_HEIGHT = 28,              /**< Maximum 2D layered texture height */
    CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_LAYERED_LAYERS = 29,              /**< Maximum layers in a 2D layered texture */
    CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_ARRAY_WIDTH = 27,                 /**< Deprecated, use CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_LAYERED_WIDTH */
    CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_ARRAY_HEIGHT = 28,                /**< Deprecated, use CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_LAYERED_HEIGHT */
    CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_ARRAY_NUMSLICES = 29,             /**< Deprecated, use CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_LAYERED_LAYERS */
    CU_DEVICE_ATTRIBUTE_SURFACE_ALIGNMENT = 30,                             /**< Alignment requirement for surfaces */
    CU_DEVICE_ATTRIBUTE_CONCURRENT_KERNELS = 31,                            /**< Device can possibly execute multiple kernels concurrently */
    CU_DEVICE_ATTRIBUTE_ECC_ENABLED = 32,                                   /**< Device has ECC support enabled */
    CU_DEVICE_ATTRIBUTE_PCI_BUS_ID = 33,                                    /**< PCI bus ID of the device */
    CU_DEVICE_ATTRIBUTE_PCI_DEVICE_ID = 34,                                 /**< PCI device ID of the device */
    CU_DEVICE_ATTRIBUTE_TCC_DRIVER = 35,                                    /**< Device is using TCC driver model */
    CU_DEVICE_ATTRIBUTE_MEMORY_CLOCK_RATE = 36,                             /**< Peak memory clock frequency in kilohertz */
    CU_DEVICE_ATTRIBUTE_GLOBAL_MEMORY_BUS_WIDTH = 37,                       /**< Global memory bus width in bits */
    CU_DEVICE_ATTRIBUTE_L2_CACHE_SIZE = 38,                                 /**< Size of L2 cache in bytes */
    CU_DEVICE_ATTRIBUTE_MAX_THREADS_PER_MULTIPROCESSOR = 39,                /**< Maximum resident threads per multiprocessor */
    CU_DEVICE_ATTRIBUTE_ASYNC_ENGINE_COUNT = 40,                            /**< Number of asynchronous engines */
    CU_DEVICE_ATTRIBUTE_UNIFIED_ADDRESSING = 41,                            /**< Device shares a unified address space with the host */
    CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE1D_LAYERED_WIDTH = 42,               /**< Maximum 1D layered texture width */
    CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE1D_LAYERED_LAYERS = 43,              /**< Maximum layers in a 1D layered texture */
    CU_DEVICE_ATTRIBUTE_CAN_TEX2D_GATHER = 44,                              /**< Deprecated, do not use. */
    CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_GATHER_WIDTH = 45,                /**< Maximum 2D texture width if CUDA_ARRAY3D_TEXTURE_GATHER is set */
    CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_GATHER_HEIGHT = 46,               /**< Maximum 2D texture height if CUDA_ARRAY3D_TEXTURE_GATHER is set */
    CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE3D_WIDTH_ALTERNATE = 47,             /**< Alternate maximum 3D texture width */
    CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE3D_HEIGHT_ALTERNATE = 48,            /**< Alternate maximum 3D texture height */
    CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE3D_DEPTH_ALTERNATE = 49,             /**< Alternate maximum 3D texture depth */
    CU_DEVICE_ATTRIBUTE_PCI_DOMAIN_ID = 50,                                 /**< PCI domain ID of the device */
    CU_DEVICE_ATTRIBUTE_TEXTURE_PITCH_ALIGNMENT = 51,                       /**< Pitch alignment requirement for textures */
    CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURECUBEMAP_WIDTH = 52,                  /**< Maximum cubemap texture width/height */
    CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURECUBEMAP_LAYERED_WIDTH = 53,          /**< Maximum cubemap layered texture width/height */
    CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURECUBEMAP_LAYERED_LAYERS = 54,         /**< Maximum layers in a cubemap layered texture */
    CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACE1D_WIDTH = 55,                       /**< Maximum 1D surface width */
    CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACE2D_WIDTH = 56,                       /**< Maximum 2D surface width */
    CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACE2D_HEIGHT = 57,                      /**< Maximum 2D surface height */
    CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACE3D_WIDTH = 58,                       /**< Maximum 3D surface width */
    CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACE3D_HEIGHT = 59,                      /**< Maximum 3D surface height */
    CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACE3D_DEPTH = 60,                       /**< Maximum 3D surface depth */
    CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACE1D_LAYERED_WIDTH = 61,               /**< Maximum 1D layered surface width */
    CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACE1D_LAYERED_LAYERS = 62,              /**< Maximum layers in a 1D layered surface */
    CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACE2D_LAYERED_WIDTH = 63,               /**< Maximum 2D layered surface width */
    CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACE2D_LAYERED_HEIGHT = 64,              /**< Maximum 2D layered surface height */
    CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACE2D_LAYERED_LAYERS = 65,              /**< Maximum layers in a 2D layered surface */
    CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACECUBEMAP_WIDTH = 66,                  /**< Maximum cubemap surface width */
    CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACECUBEMAP_LAYERED_WIDTH = 67,          /**< Maximum cubemap layered surface width */
    CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACECUBEMAP_LAYERED_LAYERS = 68,         /**< Maximum layers in a cubemap layered surface */
    CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE1D_LINEAR_WIDTH = 69,                /**< Deprecated, do not use. Use cudaDeviceGetTexture1DLinearMaxWidth() or cuDeviceGetTexture1DLinearMaxWidth() instead. */
    CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_LINEAR_WIDTH = 70,                /**< Maximum 2D linear texture width */
    CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_LINEAR_HEIGHT = 71,               /**< Maximum 2D linear texture height */
    CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_LINEAR_PITCH = 72,                /**< Maximum 2D linear texture pitch in bytes */
    CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_MIPMAPPED_WIDTH = 73,             /**< Maximum mipmapped 2D texture width */
    CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_MIPMAPPED_HEIGHT = 74,            /**< Maximum mipmapped 2D texture height */
    CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MAJOR = 75,                      /**< Major compute capability version number */
    CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MINOR = 76,                      /**< Minor compute capability version number */
    CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE1D_MIPMAPPED_WIDTH = 77,             /**< Maximum mipmapped 1D texture width */
    CU_DEVICE_ATTRIBUTE_STREAM_PRIORITIES_SUPPORTED = 78,                   /**< Device supports stream priorities */
    CU_DEVICE_ATTRIBUTE_GLOBAL_L1_CACHE_SUPPORTED = 79,                     /**< Device supports caching globals in L1 */
    CU_DEVICE_ATTRIBUTE_LOCAL_L1_CACHE_SUPPORTED = 80,                      /**< Device supports caching locals in L1 */
    CU_DEVICE_ATTRIBUTE_MAX_SHARED_MEMORY_PER_MULTIPROCESSOR = 81,          /**< Maximum shared memory available per multiprocessor in bytes */
    CU_DEVICE_ATTRIBUTE_MAX_REGISTERS_PER_MULTIPROCESSOR = 82,              /**< Maximum number of 32-bit registers available per multiprocessor */
    CU_DEVICE_ATTRIBUTE_MANAGED_MEMORY = 83,                                /**< Device can allocate managed memory on this system */
    CU_DEVICE_ATTRIBUTE_MULTI_GPU_BOARD = 84,                               /**< Device is on a multi-GPU board */
    CU_DEVICE_ATTRIBUTE_MULTI_GPU_BOARD_GROUP_ID = 85,                      /**< Unique id for a group of devices on the same multi-GPU board */
    CU_DEVICE_ATTRIBUTE_HOST_NATIVE_ATOMIC_SUPPORTED = 86,                  /**< Link between the device and the host supports native atomic operations (this is a placeholder attribute, and is not supported on any current hardware)*/
    CU_DEVICE_ATTRIBUTE_SINGLE_TO_DOUBLE_PRECISION_PERF_RATIO = 87,         /**< Ratio of single precision performance (in floating-point operations per second) to double precision performance */
    CU_DEVICE_ATTRIBUTE_PAGEABLE_MEMORY_ACCESS = 88,                        /**< Device supports coherently accessing pageable memory without calling cudaHostRegister on it */
    CU_DEVICE_ATTRIBUTE_CONCURRENT_MANAGED_ACCESS = 89,                     /**< Device can coherently access managed memory concurrently with the CPU */
    CU_DEVICE_ATTRIBUTE_COMPUTE_PREEMPTION_SUPPORTED = 90,                  /**< Device supports compute preemption. */
    CU_DEVICE_ATTRIBUTE_CAN_USE_HOST_POINTER_FOR_REGISTERED_MEM = 91,       /**< Device can access host registered memory at the same virtual address as the CPU */
    CU_DEVICE_ATTRIBUTE_CAN_USE_STREAM_MEM_OPS_V1 = 92,                     /**< Deprecated, along with v1 MemOps API, ::cuStreamBatchMemOp and related APIs are supported. */
    CU_DEVICE_ATTRIBUTE_CAN_USE_64_BIT_STREAM_MEM_OPS_V1 = 93,              /**< Deprecated, along with v1 MemOps API, 64-bit operations are supported in ::cuStreamBatchMemOp and related APIs. */
    CU_DEVICE_ATTRIBUTE_CAN_USE_STREAM_WAIT_VALUE_NOR_V1 = 94,              /**< Deprecated, along with v1 MemOps API, ::CU_STREAM_WAIT_VALUE_NOR is supported. */
    CU_DEVICE_ATTRIBUTE_COOPERATIVE_LAUNCH = 95,                            /**< Device supports launching cooperative kernels via ::cuLaunchCooperativeKernel */
    CU_DEVICE_ATTRIBUTE_COOPERATIVE_MULTI_DEVICE_LAUNCH = 96,               /**< Deprecated, ::cuLaunchCooperativeKernelMultiDevice is deprecated. */
    CU_DEVICE_ATTRIBUTE_MAX_SHARED_MEMORY_PER_BLOCK_OPTIN = 97,             /**< Maximum optin shared memory per block */
    CU_DEVICE_ATTRIBUTE_CAN_FLUSH_REMOTE_WRITES = 98,                       /**< The ::CU_STREAM_WAIT_VALUE_FLUSH flag and the ::CU_STREAM_MEM_OP_FLUSH_REMOTE_WRITES MemOp are supported on the device. See \ref CUDA_MEMOP for additional details. */
    CU_DEVICE_ATTRIBUTE_HOST_REGISTER_SUPPORTED = 99,                       /**< Device supports host memory registration via ::cudaHostRegister. */
    CU_DEVICE_ATTRIBUTE_PAGEABLE_MEMORY_ACCESS_USES_HOST_PAGE_TABLES = 100, /**< Device accesses pageable memory via the host's page tables. */
    CU_DEVICE_ATTRIBUTE_DIRECT_MANAGED_MEM_ACCESS_FROM_HOST = 101,          /**< The host can directly access managed memory on the device without migration. */
    CU_DEVICE_ATTRIBUTE_VIRTUAL_ADDRESS_MANAGEMENT_SUPPORTED = 102,         /**< Deprecated, Use CU_DEVICE_ATTRIBUTE_VIRTUAL_MEMORY_MANAGEMENT_SUPPORTED*/
    CU_DEVICE_ATTRIBUTE_VIRTUAL_MEMORY_MANAGEMENT_SUPPORTED = 102,         /**< Device supports virtual memory management APIs like ::cuMemAddressReserve, ::cuMemCreate, ::cuMemMap and related APIs */
    CU_DEVICE_ATTRIBUTE_HANDLE_TYPE_POSIX_FILE_DESCRIPTOR_SUPPORTED = 103,  /**< Device supports exporting memory to a posix file descriptor with ::cuMemExportToShareableHandle, if requested via ::cuMemCreate */
    CU_DEVICE_ATTRIBUTE_HANDLE_TYPE_WIN32_HANDLE_SUPPORTED = 104,           /**< Device supports exporting memory to a Win32 NT handle with ::cuMemExportToShareableHandle, if requested via ::cuMemCreate */
    CU_DEVICE_ATTRIBUTE_HANDLE_TYPE_WIN32_KMT_HANDLE_SUPPORTED = 105,       /**< Device supports exporting memory to a Win32 KMT handle with ::cuMemExportToShareableHandle, if requested via ::cuMemCreate */
    CU_DEVICE_ATTRIBUTE_MAX_BLOCKS_PER_MULTIPROCESSOR = 106,                /**< Maximum number of blocks per multiprocessor */
    CU_DEVICE_ATTRIBUTE_GENERIC_COMPRESSION_SUPPORTED = 107,                /**< Device supports compression of memory */
    CU_DEVICE_ATTRIBUTE_MAX_PERSISTING_L2_CACHE_SIZE = 108,                 /**< Maximum L2 persisting lines capacity setting in bytes. */
    CU_DEVICE_ATTRIBUTE_MAX_ACCESS_POLICY_WINDOW_SIZE = 109,                /**< Maximum value of CUaccessPolicyWindow::num_bytes. */
    CU_DEVICE_ATTRIBUTE_GPU_DIRECT_RDMA_WITH_CUDA_VMM_SUPPORTED = 110,      /**< Device supports specifying the GPUDirect RDMA flag with ::cuMemCreate */
    CU_DEVICE_ATTRIBUTE_RESERVED_SHARED_MEMORY_PER_BLOCK = 111,             /**< Shared memory reserved by CUDA driver per block in bytes */
    CU_DEVICE_ATTRIBUTE_SPARSE_CUDA_ARRAY_SUPPORTED = 112,                  /**< Device supports sparse CUDA arrays and sparse CUDA mipmapped arrays */
    CU_DEVICE_ATTRIBUTE_READ_ONLY_HOST_REGISTER_SUPPORTED = 113,            /**< Device supports using the ::cuMemHostRegister flag ::CU_MEMHOSTERGISTER_READ_ONLY to register memory that must be mapped as read-only to the GPU */
    CU_DEVICE_ATTRIBUTE_TIMELINE_SEMAPHORE_INTEROP_SUPPORTED = 114,         /**< External timeline semaphore interop is supported on the device */
    CU_DEVICE_ATTRIBUTE_MEMORY_POOLS_SUPPORTED = 115,                       /**< Device supports using the ::cuMemAllocAsync and ::cuMemPool family of APIs */
    CU_DEVICE_ATTRIBUTE_GPU_DIRECT_RDMA_SUPPORTED = 116,                    /**< Device supports GPUDirect RDMA APIs, like nvidia_p2p_get_pages (see https://docs.nvidia.com/cuda/gpudirect-rdma for more information) */
    CU_DEVICE_ATTRIBUTE_GPU_DIRECT_RDMA_FLUSH_WRITES_OPTIONS = 117,         /**< The returned attribute shall be interpreted as a bitmask, where the individual bits are described by the ::CUflushGPUDirectRDMAWritesOptions enum */
    CU_DEVICE_ATTRIBUTE_GPU_DIRECT_RDMA_WRITES_ORDERING = 118,              /**< GPUDirect RDMA writes to the device do not need to be flushed for consumers within the scope indicated by the returned attribute. See ::CUGPUDirectRDMAWritesOrdering for the numerical values returned here. */
    CU_DEVICE_ATTRIBUTE_MEMPOOL_SUPPORTED_HANDLE_TYPES = 119,               /**< Handle types supported with mempool based IPC */
    CU_DEVICE_ATTRIBUTE_CLUSTER_LAUNCH = 120,                               /**< Indicates device supports cluster launch */
    CU_DEVICE_ATTRIBUTE_DEFERRED_MAPPING_CUDA_ARRAY_SUPPORTED = 121,        /**< Device supports deferred mapping CUDA arrays and CUDA mipmapped arrays */
    CU_DEVICE_ATTRIBUTE_CAN_USE_64_BIT_STREAM_MEM_OPS = 122,                /**< 64-bit operations are supported in ::cuStreamBatchMemOp and related MemOp APIs. */
    CU_DEVICE_ATTRIBUTE_CAN_USE_STREAM_WAIT_VALUE_NOR = 123,                /**< ::CU_STREAM_WAIT_VALUE_NOR is supported by MemOp APIs. */
    CU_DEVICE_ATTRIBUTE_DMA_BUF_SUPPORTED = 124,                            /**< Device supports buffer sharing with dma_buf mechanism. */ 
    CU_DEVICE_ATTRIBUTE_IPC_EVENT_SUPPORTED = 125,                          /**< Device supports IPC Events. */ 
    CU_DEVICE_ATTRIBUTE_MEM_SYNC_DOMAIN_COUNT = 126,                        /**< Number of memory domains the device supports. */
    CU_DEVICE_ATTRIBUTE_TENSOR_MAP_ACCESS_SUPPORTED = 127,                  /**< Device supports accessing memory using Tensor Map. */
    CU_DEVICE_ATTRIBUTE_HANDLE_TYPE_FABRIC_SUPPORTED = 128,                 /**< Device supports exporting memory to a fabric handle with cuMemExportToShareableHandle() or requested with cuMemCreate() */
    CU_DEVICE_ATTRIBUTE_UNIFIED_FUNCTION_POINTERS = 129,                    /**< Device supports unified function pointers. */
    CU_DEVICE_ATTRIBUTE_NUMA_CONFIG = 130,                                  /**< NUMA configuration of a device: value is of type ::CUdeviceNumaConfig enum */
    CU_DEVICE_ATTRIBUTE_NUMA_ID = 131,                                      /**< NUMA node ID of the GPU memory */
    CU_DEVICE_ATTRIBUTE_MULTICAST_SUPPORTED = 132,                          /**< Device supports switch multicast and reduction operations. */
    CU_DEVICE_ATTRIBUTE_MPS_ENABLED = 133,                                  /**< Indicates if contexts created on this device will be shared via MPS */
    CU_DEVICE_ATTRIBUTE_HOST_NUMA_ID = 134,                                 /**< NUMA ID of the host node closest to the device. Returns -1 when system does not support NUMA. */
    CU_DEVICE_ATTRIBUTE_D3D12_CIG_SUPPORTED = 135,                          /**< Device supports CIG with D3D12. */
    CU_DEVICE_ATTRIBUTE_MEM_DECOMPRESS_ALGORITHM_MASK = 136,                /**< The returned valued shall be interpreted as a bitmask, where the individual bits are described by the ::CUmemDecompressAlgorithm enum. */
    CU_DEVICE_ATTRIBUTE_MEM_DECOMPRESS_MAXIMUM_LENGTH = 137,                /**< The returned valued is the maximum length in bytes of a single decompress operation that is allowed. */
    CU_DEVICE_ATTRIBUTE_GPU_PCI_DEVICE_ID    = 139, /**< The combined 16-bit PCI device ID and 16-bit PCI vendor ID. */
    CU_DEVICE_ATTRIBUTE_GPU_PCI_SUBSYSTEM_ID = 140, /**< The combined 16-bit PCI subsystem ID and 16-bit PCI subsystem vendor ID. */
    CU_DEVICE_ATTRIBUTE_HOST_NUMA_MULTINODE_IPC_SUPPORTED = 143,             /**< Device supports HOST_NUMA location IPC between nodes in a multi-node system. */
    CU_DEVICE_ATTRIBUTE_MAX
} CUdevice_attribute;

/**
 * Legacy device properties
 */
typedef struct CUdevprop_st {
    int maxThreadsPerBlock;     /**< Maximum number of threads per block */
    int maxThreadsDim[3];       /**< Maximum size of each dimension of a block */
    int maxGridSize[3];         /**< Maximum size of each dimension of a grid */
    int sharedMemPerBlock;      /**< Shared memory available per block in bytes */
    int totalConstantMemory;    /**< Constant memory available on device in bytes */
    int SIMDWidth;              /**< Warp size in threads */
    int memPitch;               /**< Maximum pitch in bytes allowed by memory copies */
    int regsPerBlock;           /**< 32-bit registers available per block */
    int clockRate;              /**< Clock frequency in kilohertz */
    int textureAlign;           /**< Alignment requirement for textures */
} CUdevprop_v1;
typedef CUdevprop_v1 CUdevprop;

/**
 * Pointer information
 */
typedef enum CUpointer_attribute_enum {
    CU_POINTER_ATTRIBUTE_CONTEXT = 1,                     /**< The ::CUcontext on which a pointer was allocated or registered */
    CU_POINTER_ATTRIBUTE_MEMORY_TYPE = 2,                 /**< The ::CUmemorytype describing the physical location of a pointer */
    CU_POINTER_ATTRIBUTE_DEVICE_POINTER = 3,              /**< The address at which a pointer's memory may be accessed on the device */
    CU_POINTER_ATTRIBUTE_HOST_POINTER = 4,                /**< The address at which a pointer's memory may be accessed on the host */
    CU_POINTER_ATTRIBUTE_P2P_TOKENS = 5,                  /**< A pair of tokens for use with the nv-p2p.h Linux kernel interface */
    CU_POINTER_ATTRIBUTE_SYNC_MEMOPS = 6,                 /**< Synchronize every synchronous memory operation initiated on this region */
    CU_POINTER_ATTRIBUTE_BUFFER_ID = 7,                   /**< A process-wide unique ID for an allocated memory region*/
    CU_POINTER_ATTRIBUTE_IS_MANAGED = 8,                  /**< Indicates if the pointer points to managed memory */
    CU_POINTER_ATTRIBUTE_DEVICE_ORDINAL = 9,              /**< A device ordinal of a device on which a pointer was allocated or registered */
    CU_POINTER_ATTRIBUTE_IS_LEGACY_CUDA_IPC_CAPABLE = 10, /**< 1 if this pointer maps to an allocation that is suitable for ::cudaIpcGetMemHandle, 0 otherwise **/
    CU_POINTER_ATTRIBUTE_RANGE_START_ADDR = 11,           /**< Starting address for this requested pointer */
    CU_POINTER_ATTRIBUTE_RANGE_SIZE = 12,                 /**< Size of the address range for this requested pointer */
    CU_POINTER_ATTRIBUTE_MAPPED = 13,                     /**< 1 if this pointer is in a valid address range that is mapped to a backing allocation, 0 otherwise **/
    CU_POINTER_ATTRIBUTE_ALLOWED_HANDLE_TYPES = 14,       /**< Bitmask of allowed ::CUmemAllocationHandleType for this allocation **/
    CU_POINTER_ATTRIBUTE_IS_GPU_DIRECT_RDMA_CAPABLE = 15, /**< 1 if the memory this pointer is referencing can be used with the GPUDirect RDMA API **/
    CU_POINTER_ATTRIBUTE_ACCESS_FLAGS = 16,               /**< Returns the access flags the device associated with the current context has on the corresponding memory referenced by the pointer given */
    CU_POINTER_ATTRIBUTE_MEMPOOL_HANDLE = 17,             /**< Returns the mempool handle for the allocation if it was allocated from a mempool. Otherwise returns NULL. **/
    CU_POINTER_ATTRIBUTE_MAPPING_SIZE = 18,               /**< Size of the actual underlying mapping that the pointer belongs to **/
    CU_POINTER_ATTRIBUTE_MAPPING_BASE_ADDR = 19,          /**< The start address of the mapping that the pointer belongs to **/
    CU_POINTER_ATTRIBUTE_MEMORY_BLOCK_ID = 20             /**< A process-wide unique id corresponding to the physical allocation the pointer belongs to **/
  , CU_POINTER_ATTRIBUTE_IS_HW_DECOMPRESS_CAPABLE = 21    /**< Returns in \p *data a boolean that indicates whether the pointer points to memory that is capable to be used for hardware accelerated decompression. */
} CUpointer_attribute;

/**
 * Function properties
 */
typedef enum CUfunction_attribute_enum {
    /**
     * The maximum number of threads per block, beyond which a launch of the
     * function would fail. This number depends on both the function and the
     * device on which the function is currently loaded.
     */
    CU_FUNC_ATTRIBUTE_MAX_THREADS_PER_BLOCK = 0,

    /**
     * The size in bytes of statically-allocated shared memory required by
     * this function. This does not include dynamically-allocated shared
     * memory requested by the user at runtime.
     */
    CU_FUNC_ATTRIBUTE_SHARED_SIZE_BYTES = 1,

    /**
     * The size in bytes of user-allocated constant memory required by this
     * function.
     */
    CU_FUNC_ATTRIBUTE_CONST_SIZE_BYTES = 2,

    /**
     * The size in bytes of local memory used by each thread of this function.
     */
    CU_FUNC_ATTRIBUTE_LOCAL_SIZE_BYTES = 3,

    /**
     * The number of registers used by each thread of this function.
     */
    CU_FUNC_ATTRIBUTE_NUM_REGS = 4,

    /**
     * The PTX virtual architecture version for which the function was
     * compiled. This value is the major PTX version * 10 + the minor PTX
     * version, so a PTX version 1.3 function would return the value 13.
     * Note that this may return the undefined value of 0 for cubins
     * compiled prior to CUDA 3.0.
     */
    CU_FUNC_ATTRIBUTE_PTX_VERSION = 5,

    /**
     * The binary architecture version for which the function was compiled.
     * This value is the major binary version * 10 + the minor binary version,
     * so a binary version 1.3 function would return the value 13. Note that
     * this will return a value of 10 for legacy cubins that do not have a
     * properly-encoded binary architecture version.
     */
    CU_FUNC_ATTRIBUTE_BINARY_VERSION = 6,

    /**
     * The attribute to indicate whether the function has been compiled with
     * user specified option "-Xptxas --dlcm=ca" set .
     */
    CU_FUNC_ATTRIBUTE_CACHE_MODE_CA = 7,

    /**
     * The maximum size in bytes of dynamically-allocated shared memory that can be used by
     * this function. If the user-specified dynamic shared memory size is larger than this
     * value, the launch will fail.
     * See ::cuFuncSetAttribute, ::cuKernelSetAttribute
     */
    CU_FUNC_ATTRIBUTE_MAX_DYNAMIC_SHARED_SIZE_BYTES = 8,

    /**
     * On devices where the L1 cache and shared memory use the same hardware resources, 
     * this sets the shared memory carveout preference, in percent of the total shared memory.
     * Refer to ::CU_DEVICE_ATTRIBUTE_MAX_SHARED_MEMORY_PER_MULTIPROCESSOR.
     * This is only a hint, and the driver can choose a different ratio if required to execute the function.
     * See ::cuFuncSetAttribute, ::cuKernelSetAttribute
     */
    CU_FUNC_ATTRIBUTE_PREFERRED_SHARED_MEMORY_CARVEOUT = 9,

    /**
     * If this attribute is set, the kernel must launch with a valid cluster
     * size specified.
     * See ::cuFuncSetAttribute, ::cuKernelSetAttribute
     */
    CU_FUNC_ATTRIBUTE_CLUSTER_SIZE_MUST_BE_SET = 10,

    /**
     * The required cluster width in blocks. The values must either all be 0 or
     * all be positive. The validity of the cluster dimensions is otherwise
     * checked at launch time.
     *
     * If the value is set during compile time, it cannot be set at runtime.
     * Setting it at runtime will return CUDA_ERROR_NOT_PERMITTED.
     * See ::cuFuncSetAttribute, ::cuKernelSetAttribute
     */
    CU_FUNC_ATTRIBUTE_REQUIRED_CLUSTER_WIDTH = 11,

    /**
     * The required cluster height in blocks. The values must either all be 0 or
     * all be positive. The validity of the cluster dimensions is otherwise
     * checked at launch time.
     *
     * If the value is set during compile time, it cannot be set at runtime.
     * Setting it at runtime should return CUDA_ERROR_NOT_PERMITTED.
     * See ::cuFuncSetAttribute, ::cuKernelSetAttribute
     */
    CU_FUNC_ATTRIBUTE_REQUIRED_CLUSTER_HEIGHT = 12,

    /**
     * The required cluster depth in blocks. The values must either all be 0 or
     * all be positive. The validity of the cluster dimensions is otherwise
     * checked at launch time.
     *
     * If the value is set during compile time, it cannot be set at runtime.
     * Setting it at runtime should return CUDA_ERROR_NOT_PERMITTED.
     * See ::cuFuncSetAttribute, ::cuKernelSetAttribute
     */
    CU_FUNC_ATTRIBUTE_REQUIRED_CLUSTER_DEPTH = 13,

    /**
     * Whether the function can be launched with non-portable cluster size. 1 is
     * allowed, 0 is disallowed. A non-portable cluster size may only function
     * on the specific SKUs the program is tested on. The launch might fail if
     * the program is run on a different hardware platform.
     *
     * CUDA API provides cudaOccupancyMaxActiveClusters to assist with checking
     * whether the desired size can be launched on the current device.
     *
     * Portable Cluster Size
     *
     * A portable cluster size is guaranteed to be functional on all compute
     * capabilities higher than the target compute capability. The portable
     * cluster size for sm_90 is 8 blocks per cluster. This value may increase
     * for future compute capabilities.
     *
     * The specific hardware unit may support higher cluster sizes that’s not
     * guaranteed to be portable.
     * See ::cuFuncSetAttribute, ::cuKernelSetAttribute
     */
    CU_FUNC_ATTRIBUTE_NON_PORTABLE_CLUSTER_SIZE_ALLOWED = 14,

    /**
     * The block scheduling policy of a function. The value type is
     * CUclusterSchedulingPolicy / cudaClusterSchedulingPolicy.
     * See ::cuFuncSetAttribute, ::cuKernelSetAttribute
     */
    CU_FUNC_ATTRIBUTE_CLUSTER_SCHEDULING_POLICY_PREFERENCE = 15,

    CU_FUNC_ATTRIBUTE_MAX
} CUfunction_attribute;

/**
 * Function cache configurations
 */
typedef enum CUfunc_cache_enum {
    CU_FUNC_CACHE_PREFER_NONE    = 0x00, /**< no preference for shared memory or L1 (default) */
    CU_FUNC_CACHE_PREFER_SHARED  = 0x01, /**< prefer larger shared memory and smaller L1 cache */
    CU_FUNC_CACHE_PREFER_L1      = 0x02, /**< prefer larger L1 cache and smaller shared memory */
    CU_FUNC_CACHE_PREFER_EQUAL   = 0x03  /**< prefer equal sized L1 cache and shared memory */
} CUfunc_cache;

/**
 * \deprecated
 *
 * Shared memory configurations
 */
typedef enum CUsharedconfig_enum {
    CU_SHARED_MEM_CONFIG_DEFAULT_BANK_SIZE    = 0x00, /**< set default shared memory bank size */
    CU_SHARED_MEM_CONFIG_FOUR_BYTE_BANK_SIZE  = 0x01, /**< set shared memory bank width to four bytes */
    CU_SHARED_MEM_CONFIG_EIGHT_BYTE_BANK_SIZE = 0x02  /**< set shared memory bank width to eight bytes */
} CUsharedconfig;

/**
 * Shared memory carveout configurations. These may be passed to ::cuFuncSetAttribute or ::cuKernelSetAttribute
 */
typedef enum CUshared_carveout_enum {
    CU_SHAREDMEM_CARVEOUT_DEFAULT       = -1,  /**< No preference for shared memory or L1 (default) */
    CU_SHAREDMEM_CARVEOUT_MAX_SHARED    = 100, /**< Prefer maximum available shared memory, minimum L1 cache */
    CU_SHAREDMEM_CARVEOUT_MAX_L1        = 0    /**< Prefer maximum available L1 cache, minimum shared memory */
} CUshared_carveout;

/**
 * Memory types
 */
typedef enum CUmemorytype_enum {
    CU_MEMORYTYPE_HOST    = 0x01,    /**< Host memory */
    CU_MEMORYTYPE_DEVICE  = 0x02,    /**< Device memory */
    CU_MEMORYTYPE_ARRAY   = 0x03,    /**< Array memory */
    CU_MEMORYTYPE_UNIFIED = 0x04     /**< Unified device or host memory */
} CUmemorytype;

/**
 * Compute Modes
 */
typedef enum CUcomputemode_enum {
    CU_COMPUTEMODE_DEFAULT           = 0, /**< Default compute mode (Multiple contexts allowed per device) */
    CU_COMPUTEMODE_PROHIBITED        = 2, /**< Compute-prohibited mode (No contexts can be created on this device at this time) */
    CU_COMPUTEMODE_EXCLUSIVE_PROCESS = 3  /**< Compute-exclusive-process mode (Only one context used by a single process can be present on this device at a time) */
} CUcomputemode;

/**
 * Memory advise values
 */
typedef enum CUmem_advise_enum {
    CU_MEM_ADVISE_SET_READ_MOSTLY          = 1, /**< Data will mostly be read and only occasionally be written to */
    CU_MEM_ADVISE_UNSET_READ_MOSTLY        = 2, /**< Undo the effect of ::CU_MEM_ADVISE_SET_READ_MOSTLY */
    CU_MEM_ADVISE_SET_PREFERRED_LOCATION   = 3, /**< Set the preferred location for the data as the specified device */
    CU_MEM_ADVISE_UNSET_PREFERRED_LOCATION = 4, /**< Clear the preferred location for the data */
    CU_MEM_ADVISE_SET_ACCESSED_BY          = 5, /**< Data will be accessed by the specified device, so prevent page faults as much as possible */
    CU_MEM_ADVISE_UNSET_ACCESSED_BY        = 6  /**< Let the Unified Memory subsystem decide on the page faulting policy for the specified device */
} CUmem_advise;

typedef enum CUmem_range_attribute_enum {
    CU_MEM_RANGE_ATTRIBUTE_READ_MOSTLY                 = 1, /**< Whether the range will mostly be read and only occasionally be written to */
    CU_MEM_RANGE_ATTRIBUTE_PREFERRED_LOCATION          = 2, /**< The preferred location of the range */
    CU_MEM_RANGE_ATTRIBUTE_ACCESSED_BY                 = 3, /**< Memory range has ::CU_MEM_ADVISE_SET_ACCESSED_BY set for specified device */
    CU_MEM_RANGE_ATTRIBUTE_LAST_PREFETCH_LOCATION      = 4  /**< The last location to which the range was prefetched */
    , CU_MEM_RANGE_ATTRIBUTE_PREFERRED_LOCATION_TYPE     = 5 /**< The preferred location type of the range */
    , CU_MEM_RANGE_ATTRIBUTE_PREFERRED_LOCATION_ID       = 6 /**< The preferred location id of the range */
    , CU_MEM_RANGE_ATTRIBUTE_LAST_PREFETCH_LOCATION_TYPE = 7 /**< The last location type to which the range was prefetched */
    , CU_MEM_RANGE_ATTRIBUTE_LAST_PREFETCH_LOCATION_ID   = 8 /**< The last location id to which the range was prefetched */
} CUmem_range_attribute;

/**
 * Online compiler and linker options
 */
typedef enum CUjit_option_enum
{
    /**
     * Max number of registers that a thread may use.\n
     * Option type: unsigned int\n
     * Applies to: compiler only
     */
    CU_JIT_MAX_REGISTERS = 0,

    /**
     * IN: Specifies minimum number of threads per block to target compilation
     * for\n
     * OUT: Returns the number of threads the compiler actually targeted.
     * This restricts the resource utilization of the compiler (e.g. max
     * registers) such that a block with the given number of threads should be
     * able to launch based on register limitations. Note, this option does not
     * currently take into account any other resource limitations, such as
     * shared memory utilization.\n
     * Cannot be combined with ::CU_JIT_TARGET.\n
     * Option type: unsigned int\n
     * Applies to: compiler only
     */
    CU_JIT_THREADS_PER_BLOCK = 1,

    /**
     * Overwrites the option value with the total wall clock time, in
     * milliseconds, spent in the compiler and linker\n
     * Option type: float\n
     * Applies to: compiler and linker
     */
    CU_JIT_WALL_TIME = 2,

    /**
     * Pointer to a buffer in which to print any log messages
     * that are informational in nature (the buffer size is specified via
     * option ::CU_JIT_INFO_LOG_BUFFER_SIZE_BYTES)\n
     * Option type: char *\n
     * Applies to: compiler and linker
     */
    CU_JIT_INFO_LOG_BUFFER = 3,

    /**
     * IN: Log buffer size in bytes.  Log messages will be capped at this size
     * (including null terminator)\n
     * OUT: Amount of log buffer filled with messages\n
     * Option type: unsigned int\n
     * Applies to: compiler and linker
     */
    CU_JIT_INFO_LOG_BUFFER_SIZE_BYTES = 4,

    /**
     * Pointer to a buffer in which to print any log messages that
     * reflect errors (the buffer size is specified via option
     * ::CU_JIT_ERROR_LOG_BUFFER_SIZE_BYTES)\n
     * Option type: char *\n
     * Applies to: compiler and linker
     */
    CU_JIT_ERROR_LOG_BUFFER = 5,

    /**
     * IN: Log buffer size in bytes.  Log messages will be capped at this size
     * (including null terminator)\n
     * OUT: Amount of log buffer filled with messages\n
     * Option type: unsigned int\n
     * Applies to: compiler and linker
     */
    CU_JIT_ERROR_LOG_BUFFER_SIZE_BYTES = 6,

    /**
     * Level of optimizations to apply to generated code (0 - 4), with 4
     * being the default and highest level of optimizations.\n
     * Option type: unsigned int\n
     * Applies to: compiler only
     */
    CU_JIT_OPTIMIZATION_LEVEL = 7,

    /**
     * No option value required. Determines the target based on the current
     * attached context (default)\n
     * Option type: No option value needed\n
     * Applies to: compiler and linker
     */
    CU_JIT_TARGET_FROM_CUCONTEXT = 8,

    /**
     * Target is chosen based on supplied ::CUjit_target.  Cannot be
     * combined with ::CU_JIT_THREADS_PER_BLOCK.\n
     * Option type: unsigned int for enumerated type ::CUjit_target\n
     * Applies to: compiler and linker
     */
    CU_JIT_TARGET = 9,

    /**
     * Specifies choice of fallback strategy if matching cubin is not found.
     * Choice is based on supplied ::CUjit_fallback.  This option cannot be
     * used with cuLink* APIs as the linker requires exact matches.\n
     * Option type: unsigned int for enumerated type ::CUjit_fallback\n
     * Applies to: compiler only
     */
    CU_JIT_FALLBACK_STRATEGY = 10,

    /**
     * Specifies whether to create debug information in output (-g)
     * (0: false, default)\n
     * Option type: int\n
     * Applies to: compiler and linker
     */
    CU_JIT_GENERATE_DEBUG_INFO = 11,

    /**
     * Generate verbose log messages (0: false, default)\n
     * Option type: int\n
     * Applies to: compiler and linker
     */
    CU_JIT_LOG_VERBOSE = 12,

    /**
     * Generate line number information (-lineinfo) (0: false, default)\n
     * Option type: int\n
     * Applies to: compiler only
     */
    CU_JIT_GENERATE_LINE_INFO = 13,

    /**
     * Specifies whether to enable caching explicitly (-dlcm) \n
     * Choice is based on supplied ::CUjit_cacheMode_enum.\n
     * Option type: unsigned int for enumerated type ::CUjit_cacheMode_enum\n
     * Applies to: compiler only
     */
    CU_JIT_CACHE_MODE = 14,

    /**
     * \deprecated
     * This jit option is deprecated and should not be used.
     */
    CU_JIT_NEW_SM3X_OPT = 15,

    /**
     * This jit option is used for internal purpose only.
     */
    CU_JIT_FAST_COMPILE = 16,

    /**
     * Array of device symbol names that will be relocated to the corresponding
     * host addresses stored in ::CU_JIT_GLOBAL_SYMBOL_ADDRESSES.\n
     * Must contain ::CU_JIT_GLOBAL_SYMBOL_COUNT entries.\n
     * When loading a device module, driver will relocate all encountered
     * unresolved symbols to the host addresses.\n
     * It is only allowed to register symbols that correspond to unresolved
     * global variables.\n
     * It is illegal to register the same device symbol at multiple addresses.\n
     * Option type: const char **\n
     * Applies to: dynamic linker only
     */
    CU_JIT_GLOBAL_SYMBOL_NAMES = 17,

    /**
     * Array of host addresses that will be used to relocate corresponding
     * device symbols stored in ::CU_JIT_GLOBAL_SYMBOL_NAMES.\n
     * Must contain ::CU_JIT_GLOBAL_SYMBOL_COUNT entries.\n
     * Option type: void **\n
     * Applies to: dynamic linker only
     */
    CU_JIT_GLOBAL_SYMBOL_ADDRESSES = 18,

    /**
     * Number of entries in ::CU_JIT_GLOBAL_SYMBOL_NAMES and
     * ::CU_JIT_GLOBAL_SYMBOL_ADDRESSES arrays.\n
     * Option type: unsigned int\n
     * Applies to: dynamic linker only
     */
    CU_JIT_GLOBAL_SYMBOL_COUNT = 19,

    /**
     * \deprecated
     * Enable link-time optimization (-dlto) for device code (Disabled by default).\n
     * This option is not supported on 32-bit platforms.\n
     * Option type: int\n
     * Applies to: compiler and linker
     *
     * Only valid with LTO-IR compiled with toolkits prior to CUDA 12.0
     */
    CU_JIT_LTO = 20,

    /**
     * \deprecated
     * Control single-precision denormals (-ftz) support (0: false, default).
     * 1 : flushes denormal values to zero
     * 0 : preserves denormal values
     * Option type: int\n
     * Applies to: link-time optimization specified with CU_JIT_LTO
     *
     * Only valid with LTO-IR compiled with toolkits prior to CUDA 12.0
     */
    CU_JIT_FTZ = 21,

    /**
     * \deprecated
     * Control single-precision floating-point division and reciprocals
     * (-prec-div) support (1: true, default).
     * 1 : Enables the IEEE round-to-nearest mode
     * 0 : Enables the fast approximation mode
     * Option type: int\n
     * Applies to: link-time optimization specified with CU_JIT_LTO
     *
     * Only valid with LTO-IR compiled with toolkits prior to CUDA 12.0
     */
    CU_JIT_PREC_DIV = 22,

    /**
     * \deprecated
     * Control single-precision floating-point square root
     * (-prec-sqrt) support (1: true, default).
     * 1 : Enables the IEEE round-to-nearest mode
     * 0 : Enables the fast approximation mode
     * Option type: int\n
     * Applies to: link-time optimization specified with CU_JIT_LTO
     *
     * Only valid with LTO-IR compiled with toolkits prior to CUDA 12.0
     */
    CU_JIT_PREC_SQRT = 23,

    /**
     * \deprecated
     * Enable/Disable the contraction of floating-point multiplies
     * and adds/subtracts into floating-point multiply-add (-fma)
     * operations (1: Enable, default; 0: Disable).
     * Option type: int\n
     * Applies to: link-time optimization specified with CU_JIT_LTO
     *
     * Only valid with LTO-IR compiled with toolkits prior to CUDA 12.0
     */
    CU_JIT_FMA = 24,

    /**
     * \deprecated
     * Array of kernel names that should be preserved at link time while others
     * can be removed.\n
     * Must contain ::CU_JIT_REFERENCED_KERNEL_COUNT entries.\n
     * Note that kernel names can be mangled by the compiler in which case the
     * mangled name needs to be specified.\n
     * Wildcard "*" can be used to represent zero or more characters instead of
     * specifying the full or mangled name.\n
     * It is important to note that the wildcard "*" is also added implicitly.
     * For example, specifying "foo" will match "foobaz", "barfoo", "barfoobaz" and
     * thus preserve all kernels with those names. This can be avoided by providing
     * a more specific name like "barfoobaz".\n
     * Option type: const char **\n
     * Applies to: dynamic linker only
     *
     * Only valid with LTO-IR compiled with toolkits prior to CUDA 12.0
     */
    CU_JIT_REFERENCED_KERNEL_NAMES = 25,

    /**
     * \deprecated
     * Number of entries in ::CU_JIT_REFERENCED_KERNEL_NAMES array.\n
     * Option type: unsigned int\n
     * Applies to: dynamic linker only
     *
     * Only valid with LTO-IR compiled with toolkits prior to CUDA 12.0
     */
    CU_JIT_REFERENCED_KERNEL_COUNT = 26,

    /**
     * \deprecated
     * Array of variable names (__device__ and/or __constant__) that should be
     * preserved at link time while others can be removed.\n
     * Must contain ::CU_JIT_REFERENCED_VARIABLE_COUNT entries.\n
     * Note that variable names can be mangled by the compiler in which case the
     * mangled name needs to be specified.\n
     * Wildcard "*" can be used to represent zero or more characters instead of
     * specifying the full or mangled name.\n
     * It is important to note that the wildcard "*" is also added implicitly.
     * For example, specifying "foo" will match "foobaz", "barfoo", "barfoobaz" and
     * thus preserve all variables with those names. This can be avoided by providing
     * a more specific name like "barfoobaz".\n
     * Option type: const char **\n
     * Applies to: link-time optimization specified with CU_JIT_LTO
     *
     * Only valid with LTO-IR compiled with toolkits prior to CUDA 12.0
     */
    CU_JIT_REFERENCED_VARIABLE_NAMES = 27,

    /**
     * \deprecated
     * Number of entries in ::CU_JIT_REFERENCED_VARIABLE_NAMES array.\n
     * Option type: unsigned int\n
     * Applies to: link-time optimization specified with CU_JIT_LTO
     *
     * Only valid with LTO-IR compiled with toolkits prior to CUDA 12.0
     */
    CU_JIT_REFERENCED_VARIABLE_COUNT = 28,

    /**
     * \deprecated
     * This option serves as a hint to enable the JIT compiler/linker
     * to remove constant (__constant__) and device (__device__) variables
     * unreferenced in device code (Disabled by default).\n
     * Note that host references to constant and device variables using APIs like
     * ::cuModuleGetGlobal() with this option specified may result in undefined behavior unless
     * the variables are explicitly specified using ::CU_JIT_REFERENCED_VARIABLE_NAMES.\n
     * Option type: int\n
     * Applies to: link-time optimization specified with CU_JIT_LTO
     *
     * Only valid with LTO-IR compiled with toolkits prior to CUDA 12.0
     */
    CU_JIT_OPTIMIZE_UNUSED_DEVICE_VARIABLES = 29,

    /**
     * Generate position independent code (0: false)\n
     * Option type: int\n
     * Applies to: compiler only
     */
    CU_JIT_POSITION_INDEPENDENT_CODE = 30,

    /**
     * This option hints to the JIT compiler the minimum number of CTAs from the
     * kernel’s grid to be mapped to a SM. This option is ignored when used together
     * with ::CU_JIT_MAX_REGISTERS or ::CU_JIT_THREADS_PER_BLOCK.
     * Optimizations based on this option need ::CU_JIT_MAX_THREADS_PER_BLOCK to
     * be specified as well. For kernels already using PTX directive .minnctapersm,
     * this option will be ignored by default. Use ::CU_JIT_OVERRIDE_DIRECTIVE_VALUES
     * to let this option take precedence over the PTX directive.
     * Option type: unsigned int\n
     * Applies to: compiler only
    */
    CU_JIT_MIN_CTA_PER_SM = 31,

     /**
     * Maximum number threads in a thread block, computed as the product of
     * the maximum extent specifed for each dimension of the block. This limit
     * is guaranteed not to be exeeded in any invocation of the kernel. Exceeding
     * the the maximum number of threads results in runtime error or kernel launch
     * failure. For kernels already using PTX directive .maxntid, this option will
     * be ignored by default. Use ::CU_JIT_OVERRIDE_DIRECTIVE_VALUES to let this
     * option take precedence over the PTX directive.
     * Option type: int\n
     * Applies to: compiler only
    */
    CU_JIT_MAX_THREADS_PER_BLOCK = 32,

    /**
     * This option lets the values specified using ::CU_JIT_MAX_REGISTERS,
     * ::CU_JIT_THREADS_PER_BLOCK, ::CU_JIT_MAX_THREADS_PER_BLOCK and
     * ::CU_JIT_MIN_CTA_PER_SM take precedence over any PTX directives.
     * (0: Disable, default; 1: Enable)
     * Option type: int\n
     * Applies to: compiler only
    */
    CU_JIT_OVERRIDE_DIRECTIVE_VALUES = 33,
    CU_JIT_NUM_OPTIONS

} CUjit_option;

/*
 * Indicates that compute device class supports accelerated features.
 */
#define CU_COMPUTE_ACCELERATED_TARGET_BASE   0x10000

/**
 * Online compilation targets
 */
typedef enum CUjit_target_enum
{
    CU_TARGET_COMPUTE_30 = 30, /**< Compute device class 3.0 */
    CU_TARGET_COMPUTE_32 = 32, /**< Compute device class 3.2 */
    CU_TARGET_COMPUTE_35 = 35, /**< Compute device class 3.5 */
    CU_TARGET_COMPUTE_37 = 37, /**< Compute device class 3.7 */
    CU_TARGET_COMPUTE_50 = 50, /**< Compute device class 5.0 */
    CU_TARGET_COMPUTE_52 = 52, /**< Compute device class 5.2 */
    CU_TARGET_COMPUTE_53 = 53, /**< Compute device class 5.3 */
    CU_TARGET_COMPUTE_60 = 60, /**< Compute device class 6.0.*/
    CU_TARGET_COMPUTE_61 = 61, /**< Compute device class 6.1.*/
    CU_TARGET_COMPUTE_62 = 62, /**< Compute device class 6.2.*/
    CU_TARGET_COMPUTE_70 = 70, /**< Compute device class 7.0.*/
    CU_TARGET_COMPUTE_72 = 72, /**< Compute device class 7.2.*/
    CU_TARGET_COMPUTE_75 = 75, /**< Compute device class 7.5.*/
    CU_TARGET_COMPUTE_80 = 80, /**< Compute device class 8.0.*/
    CU_TARGET_COMPUTE_86 = 86, /**< Compute device class 8.6.*/
    CU_TARGET_COMPUTE_87 = 87, /**< Compute device class 8.7.*/
    CU_TARGET_COMPUTE_89 = 89, /**< Compute device class 8.9.*/
    CU_TARGET_COMPUTE_90 = 90, /**< Compute device class 9.0.*/
    CU_TARGET_COMPUTE_100 = 100, /**< Compute device class 10.0.*/
    CU_TARGET_COMPUTE_101 = 101,       /**< Compute device class 10.1.*/
    CU_TARGET_COMPUTE_120 = 120, /**< Compute device class 12.0.*/

    /**< Compute device class 9.0. with accelerated features.*/
    CU_TARGET_COMPUTE_90A = CU_COMPUTE_ACCELERATED_TARGET_BASE + CU_TARGET_COMPUTE_90,
    /**< Compute device class 10.0. with accelerated features.*/
    CU_TARGET_COMPUTE_100A = CU_COMPUTE_ACCELERATED_TARGET_BASE + CU_TARGET_COMPUTE_100,
    /**< Compute device class 10.1 with accelerated features.*/
    CU_TARGET_COMPUTE_101A = CU_COMPUTE_ACCELERATED_TARGET_BASE + CU_TARGET_COMPUTE_101,
    /**< Compute device class 12.0. with accelerated features.*/
    CU_TARGET_COMPUTE_120A = CU_COMPUTE_ACCELERATED_TARGET_BASE + CU_TARGET_COMPUTE_120,
} CUjit_target;

/**
 * Cubin matching fallback strategies
 */
typedef enum CUjit_fallback_enum
{
    CU_PREFER_PTX = 0,  /**< Prefer to compile ptx if exact binary match not found */

    CU_PREFER_BINARY    /**< Prefer to fall back to compatible binary code if exact match not found */

} CUjit_fallback;

/**
 * Caching modes for dlcm
 */
typedef enum CUjit_cacheMode_enum
{
    CU_JIT_CACHE_OPTION_NONE = 0, /**< Compile with no -dlcm flag specified */
    CU_JIT_CACHE_OPTION_CG,       /**< Compile with L1 cache disabled */
    CU_JIT_CACHE_OPTION_CA        /**< Compile with L1 cache enabled */
} CUjit_cacheMode;

/**
 * Device code formats
 */
typedef enum CUjitInputType_enum
{
    /**
     * Compiled device-class-specific device code\n
     * Applicable options: none
     */
    CU_JIT_INPUT_CUBIN = 0,

    /**
     * PTX source code\n
     * Applicable options: PTX compiler options
     */
    CU_JIT_INPUT_PTX = 1,

    /**
     * Bundle of multiple cubins and/or PTX of some device code\n
     * Applicable options: PTX compiler options, ::CU_JIT_FALLBACK_STRATEGY
     */
    CU_JIT_INPUT_FATBINARY = 2,

    /**
     * Host object with embedded device code\n
     * Applicable options: PTX compiler options, ::CU_JIT_FALLBACK_STRATEGY
     */
    CU_JIT_INPUT_OBJECT = 3,

    /**
     * Archive of host objects with embedded device code\n
     * Applicable options: PTX compiler options, ::CU_JIT_FALLBACK_STRATEGY
     */
    CU_JIT_INPUT_LIBRARY = 4,

    /**
     * \deprecated
     * High-level intermediate code for link-time optimization\n
     * Applicable options: NVVM compiler options, PTX compiler options
     *
     * Only valid with LTO-IR compiled with toolkits prior to CUDA 12.0
     */
    CU_JIT_INPUT_NVVM = 5,

    CU_JIT_NUM_INPUT_TYPES = 6
} CUjitInputType;

typedef struct CUlinkState_st *CUlinkState;

/**
 * Flags to register a graphics resource
 */
typedef enum CUgraphicsRegisterFlags_enum {
    CU_GRAPHICS_REGISTER_FLAGS_NONE           = 0x00,
    CU_GRAPHICS_REGISTER_FLAGS_READ_ONLY      = 0x01,
    CU_GRAPHICS_REGISTER_FLAGS_WRITE_DISCARD  = 0x02,
    CU_GRAPHICS_REGISTER_FLAGS_SURFACE_LDST   = 0x04,
    CU_GRAPHICS_REGISTER_FLAGS_TEXTURE_GATHER = 0x08
} CUgraphicsRegisterFlags;

/**
 * Flags for mapping and unmapping interop resources
 */
typedef enum CUgraphicsMapResourceFlags_enum {
    CU_GRAPHICS_MAP_RESOURCE_FLAGS_NONE          = 0x00,
    CU_GRAPHICS_MAP_RESOURCE_FLAGS_READ_ONLY     = 0x01,
    CU_GRAPHICS_MAP_RESOURCE_FLAGS_WRITE_DISCARD = 0x02
} CUgraphicsMapResourceFlags;

/**
 * Array indices for cube faces
 */
typedef enum CUarray_cubemap_face_enum {
    CU_CUBEMAP_FACE_POSITIVE_X  = 0x00, /**< Positive X face of cubemap */
    CU_CUBEMAP_FACE_NEGATIVE_X  = 0x01, /**< Negative X face of cubemap */
    CU_CUBEMAP_FACE_POSITIVE_Y  = 0x02, /**< Positive Y face of cubemap */
    CU_CUBEMAP_FACE_NEGATIVE_Y  = 0x03, /**< Negative Y face of cubemap */
    CU_CUBEMAP_FACE_POSITIVE_Z  = 0x04, /**< Positive Z face of cubemap */
    CU_CUBEMAP_FACE_NEGATIVE_Z  = 0x05  /**< Negative Z face of cubemap */
} CUarray_cubemap_face;

/**
 * Limits
 */
typedef enum CUlimit_enum {
    CU_LIMIT_STACK_SIZE                       = 0x00, /**< GPU thread stack size */
    CU_LIMIT_PRINTF_FIFO_SIZE                 = 0x01, /**< GPU printf FIFO size */
    CU_LIMIT_MALLOC_HEAP_SIZE                 = 0x02, /**< GPU malloc heap size */
    CU_LIMIT_DEV_RUNTIME_SYNC_DEPTH           = 0x03, /**< GPU device runtime launch synchronize depth */
    CU_LIMIT_DEV_RUNTIME_PENDING_LAUNCH_COUNT = 0x04, /**< GPU device runtime pending launch count */
    CU_LIMIT_MAX_L2_FETCH_GRANULARITY         = 0x05, /**< A value between 0 and 128 that indicates the maximum fetch granularity of L2 (in Bytes). This is a hint */
    CU_LIMIT_PERSISTING_L2_CACHE_SIZE         = 0x06, /**< A size in bytes for L2 persisting lines cache size */
    CU_LIMIT_SHMEM_SIZE                       = 0x07, /**< A maximum size in bytes of shared memory available to CUDA kernels on a CIG context. Can only be queried, cannot be set */
    CU_LIMIT_CIG_ENABLED                      = 0x08, /**< A non-zero value indicates this CUDA context is a CIG-enabled context. Can only be queried, cannot be set */
    CU_LIMIT_CIG_SHMEM_FALLBACK_ENABLED       = 0x09, /**< When set to zero, CUDA will fail to launch a kernel on a CIG context, instead of using the fallback path, if the kernel uses more shared memory than available */
    CU_LIMIT_MAX
} CUlimit;

/**
 * Resource types
 */
typedef enum CUresourcetype_enum {
    CU_RESOURCE_TYPE_ARRAY           = 0x00, /**< Array resource */
    CU_RESOURCE_TYPE_MIPMAPPED_ARRAY = 0x01, /**< Mipmapped array resource */
    CU_RESOURCE_TYPE_LINEAR          = 0x02, /**< Linear resource */
    CU_RESOURCE_TYPE_PITCH2D         = 0x03  /**< Pitch 2D resource */
} CUresourcetype;

#ifdef _WIN32
#define CUDA_CB __stdcall
#else
#define CUDA_CB
#endif

/**
 * CUDA host function
 * \param userData Argument value passed to the function
 */
typedef void (CUDA_CB *CUhostFn)(void *userData);

/**
 * Specifies performance hint with ::CUaccessPolicyWindow for hitProp and missProp members.
 */
typedef enum CUaccessProperty_enum {
    CU_ACCESS_PROPERTY_NORMAL           = 0,    /**< Normal cache persistence. */
    CU_ACCESS_PROPERTY_STREAMING        = 1,    /**< Streaming access is less likely to persit from cache. */
    CU_ACCESS_PROPERTY_PERSISTING       = 2     /**< Persisting access is more likely to persist in cache.*/
} CUaccessProperty;

/**
 * Specifies an access policy for a window, a contiguous extent of memory
 * beginning at base_ptr and ending at base_ptr + num_bytes.
 * num_bytes is limited by CU_DEVICE_ATTRIBUTE_MAX_ACCESS_POLICY_WINDOW_SIZE.
 * Partition into many segments and assign segments such that:
 * sum of "hit segments" / window == approx. ratio.
 * sum of "miss segments" / window == approx 1-ratio.
 * Segments and ratio specifications are fitted to the capabilities of
 * the architecture.
 * Accesses in a hit segment apply the hitProp access policy.
 * Accesses in a miss segment apply the missProp access policy.
 */
typedef struct CUaccessPolicyWindow_st {
    void *base_ptr;                     /**< Starting address of the access policy window. CUDA driver may align it. */
    size_t num_bytes;                   /**< Size in bytes of the window policy. CUDA driver may restrict the maximum size and alignment. */
    float hitRatio;                     /**< hitRatio specifies percentage of lines assigned hitProp, rest are assigned missProp. */
    CUaccessProperty hitProp;           /**< ::CUaccessProperty set for hit. */
    CUaccessProperty missProp;          /**< ::CUaccessProperty set for miss. Must be either NORMAL or STREAMING */
} CUaccessPolicyWindow_v1;
/**
 * Access policy window
 */
typedef CUaccessPolicyWindow_v1 CUaccessPolicyWindow;

/**
 * GPU kernel node parameters
 */
typedef struct CUDA_KERNEL_NODE_PARAMS_st {
    CUfunction func;             /**< Kernel to launch */
    unsigned int gridDimX;       /**< Width of grid in blocks */
    unsigned int gridDimY;       /**< Height of grid in blocks */
    unsigned int gridDimZ;       /**< Depth of grid in blocks */
    unsigned int blockDimX;      /**< X dimension of each thread block */
    unsigned int blockDimY;      /**< Y dimension of each thread block */
    unsigned int blockDimZ;      /**< Z dimension of each thread block */
    unsigned int sharedMemBytes; /**< Dynamic shared-memory size per thread block in bytes */
    void **kernelParams;         /**< Array of pointers to kernel parameters */
    void **extra;                /**< Extra options */
} CUDA_KERNEL_NODE_PARAMS_v1;

/**
 * GPU kernel node parameters
 */
typedef struct CUDA_KERNEL_NODE_PARAMS_v2_st {
    CUfunction func;             /**< Kernel to launch */
    unsigned int gridDimX;       /**< Width of grid in blocks */
    unsigned int gridDimY;       /**< Height of grid in blocks */
    unsigned int gridDimZ;       /**< Depth of grid in blocks */
    unsigned int blockDimX;      /**< X dimension of each thread block */
    unsigned int blockDimY;      /**< Y dimension of each thread block */
    unsigned int blockDimZ;      /**< Z dimension of each thread block */
    unsigned int sharedMemBytes; /**< Dynamic shared-memory size per thread block in bytes */
    void **kernelParams;         /**< Array of pointers to kernel parameters */
    void **extra;                /**< Extra options */
    CUkernel kern;               /**< Kernel to launch, will only be referenced if func is NULL */
    CUcontext ctx;               /**< Context for the kernel task to run in. The value NULL will indicate the current context should be used by the api. This field is ignored if func is set. */
} CUDA_KERNEL_NODE_PARAMS_v2;
typedef CUDA_KERNEL_NODE_PARAMS_v2 CUDA_KERNEL_NODE_PARAMS;

/**
 * GPU kernel node parameters
 */
typedef struct CUDA_KERNEL_NODE_PARAMS_v3_st {
    CUfunction func;             /**< Kernel to launch */
    unsigned int gridDimX;       /**< Width of grid in blocks */
    unsigned int gridDimY;       /**< Height of grid in blocks */
    unsigned int gridDimZ;       /**< Depth of grid in blocks */
    unsigned int blockDimX;      /**< X dimension of each thread block */
    unsigned int blockDimY;      /**< Y dimension of each thread block */
    unsigned int blockDimZ;      /**< Z dimension of each thread block */
    unsigned int sharedMemBytes; /**< Dynamic shared-memory size per thread block in bytes */
    void **kernelParams;         /**< Array of pointers to kernel parameters */
    void **extra;                /**< Extra options */
    CUkernel kern;               /**< Kernel to launch, will only be referenced if func is NULL */
    CUcontext ctx;               /**< Context for the kernel task to run in. The value NULL will indicate the current context should be used by the api. This field is ignored if func is set. */
} CUDA_KERNEL_NODE_PARAMS_v3;

/**
 * Memset node parameters
 */
typedef struct CUDA_MEMSET_NODE_PARAMS_st {
    CUdeviceptr dst;                        /**< Destination device pointer */
    size_t pitch;                           /**< Pitch of destination device pointer. Unused if height is 1 */
    unsigned int value;                     /**< Value to be set */
    unsigned int elementSize;               /**< Size of each element in bytes. Must be 1, 2, or 4. */
    size_t width;                           /**< Width of the row in elements */
    size_t height;                          /**< Number of rows */
} CUDA_MEMSET_NODE_PARAMS_v1;
typedef CUDA_MEMSET_NODE_PARAMS_v1 CUDA_MEMSET_NODE_PARAMS;

/**
 * Memset node parameters
 */
typedef struct CUDA_MEMSET_NODE_PARAMS_v2_st {
    CUdeviceptr dst;                        /**< Destination device pointer */
    size_t pitch;                           /**< Pitch of destination device pointer. Unused if height is 1 */
    unsigned int value;                     /**< Value to be set */
    unsigned int elementSize;               /**< Size of each element in bytes. Must be 1, 2, or 4. */
    size_t width;                           /**< Width of the row in elements */
    size_t height;                          /**< Number of rows */
    CUcontext ctx;                          /**< Context on which to run the node */
} CUDA_MEMSET_NODE_PARAMS_v2;

/**
 * Host node parameters
 */
typedef struct CUDA_HOST_NODE_PARAMS_st {
    CUhostFn fn;    /**< The function to call when the node executes */
    void* userData; /**< Argument to pass to the function */
} CUDA_HOST_NODE_PARAMS_v1;
typedef CUDA_HOST_NODE_PARAMS_v1 CUDA_HOST_NODE_PARAMS;

/**
 * Host node parameters
 */
typedef struct CUDA_HOST_NODE_PARAMS_v2_st {
    CUhostFn fn;    /**< The function to call when the node executes */
    void* userData; /**< Argument to pass to the function */
} CUDA_HOST_NODE_PARAMS_v2;

/**
 * Conditional node handle flags
 */
#define CU_GRAPH_COND_ASSIGN_DEFAULT   0x1 /**< Default value is applied when graph is launched. */

/**
 * Conditional node types
 */
typedef enum CUgraphConditionalNodeType_enum {
     CU_GRAPH_COND_TYPE_IF = 0,     /**< Conditional 'if/else' Node. Body[0] executed if condition is non-zero.  If \p size == 2, an optional ELSE graph is created and this is executed if the condition is zero. */
     CU_GRAPH_COND_TYPE_WHILE = 1,  /**< Conditional 'while' Node. Body executed repeatedly while condition value is non-zero. */
     CU_GRAPH_COND_TYPE_SWITCH = 2, /**< Conditional 'switch' Node. Body[n] is executed once, where 'n' is the value of the condition. If the condition does not match a body index, no body is launched. */
} CUgraphConditionalNodeType;

/**
 * Conditional node parameters
 */
typedef struct CUDA_CONDITIONAL_NODE_PARAMS {
    CUgraphConditionalHandle handle;   /**< Conditional node handle.
                                            Handles must be created in advance of creating the node
                                            using ::cuGraphConditionalHandleCreate. */
    CUgraphConditionalNodeType type;   /**< Type of conditional node. */
    unsigned int size;                 /**< Size of graph output array.  Allowed values are 1 for CU_GRAPH_COND_TYPE_WHILE, 1 or 2
                                            for CU_GRAPH_COND_TYPE_IF, or any value greater than zero for CU_GRAPH_COND_TYPE_SWITCH. */
    CUgraph *phGraph_out;              /**< CUDA-owned array populated with conditional node child graphs during creation of the node.
                                            Valid for the lifetime of the conditional node.
                                            The contents of the graph(s) are subject to the following constraints:

                                            - Allowed node types are kernel nodes, empty nodes, child graphs, memsets,
                                              memcopies, and conditionals. This applies recursively to child graphs and conditional bodies.
                                            - All kernels, including kernels in nested conditionals or child graphs at any level,
                                              must belong to the same CUDA context.

                                            These graphs may be populated using graph node creation APIs or ::cuStreamBeginCaptureToGraph.

                                            CU_GRAPH_COND_TYPE_IF:
                                            phGraph_out[0] is executed when the condition is non-zero.  If \p size == 2, phGraph_out[1] will
                                            be executed when the condition is zero.
                                            CU_GRAPH_COND_TYPE_WHILE:
                                            phGraph_out[0] is executed as long as the condition is non-zero.
                                            CU_GRAPH_COND_TYPE_SWITCH:
                                            phGraph_out[n] is executed when the condition is equal to n.  If the condition >= \p size,
                                            no body graph is executed.
                                         */
    CUcontext ctx;                     /**< Context on which to run the node.  Must match context used to create the handle and all body nodes. */
} CUDA_CONDITIONAL_NODE_PARAMS;

/**
 * Graph node types
 */
typedef enum CUgraphNodeType_enum {
    CU_GRAPH_NODE_TYPE_KERNEL           = 0, /**< GPU kernel node */
    CU_GRAPH_NODE_TYPE_MEMCPY           = 1, /**< Memcpy node */
    CU_GRAPH_NODE_TYPE_MEMSET           = 2, /**< Memset node */
    CU_GRAPH_NODE_TYPE_HOST             = 3, /**< Host (executable) node */
    CU_GRAPH_NODE_TYPE_GRAPH            = 4, /**< Node which executes an embedded graph */
    CU_GRAPH_NODE_TYPE_EMPTY            = 5, /**< Empty (no-op) node */
    CU_GRAPH_NODE_TYPE_WAIT_EVENT       = 6, /**< External event wait node */
    CU_GRAPH_NODE_TYPE_EVENT_RECORD     = 7, /**< External event record node */
    CU_GRAPH_NODE_TYPE_EXT_SEMAS_SIGNAL = 8, /**< External semaphore signal node */
    CU_GRAPH_NODE_TYPE_EXT_SEMAS_WAIT   = 9, /**< External semaphore wait node */
    CU_GRAPH_NODE_TYPE_MEM_ALLOC        = 10,/**< Memory Allocation Node */
    CU_GRAPH_NODE_TYPE_MEM_FREE         = 11,/**< Memory Free Node */
    CU_GRAPH_NODE_TYPE_BATCH_MEM_OP     = 12,/**< Batch MemOp Node */
    CU_GRAPH_NODE_TYPE_CONDITIONAL      = 13 /**< Conditional Node

                                                  May be used to implement a conditional execution path or loop
                                                  inside of a graph. The graph(s) contained within the body of the conditional node
                                                  can be selectively executed or iterated upon based on the value of a conditional
                                                  variable.

                                                  Handles must be created in advance of creating the node
                                                  using ::cuGraphConditionalHandleCreate.

                                                  The following restrictions apply to graphs which contain conditional nodes:
                                                   The graph cannot be used in a child node.
                                                   Only one instantiation of the graph may exist at any point in time.
                                                   The graph cannot be cloned.

                                                  To set the control value, supply a default value when creating the handle and/or
                                                  call ::cudaGraphSetConditional from device code.*/
} CUgraphNodeType;

/**
 * Type annotations that can be applied to graph edges as part of ::CUgraphEdgeData.
 */
typedef enum CUgraphDependencyType_enum {
    CU_GRAPH_DEPENDENCY_TYPE_DEFAULT = 0, /**< This is an ordinary dependency. */
    CU_GRAPH_DEPENDENCY_TYPE_PROGRAMMATIC = 1  /**< This dependency type allows the downstream node to
                                                    use \c cudaGridDependencySynchronize(). It may only be used
                                                    between kernel nodes, and must be used with either the
                                                    ::CU_GRAPH_KERNEL_NODE_PORT_PROGRAMMATIC or
                                                    ::CU_GRAPH_KERNEL_NODE_PORT_LAUNCH_ORDER outgoing port. */
} CUgraphDependencyType;

/**
 * This port activates when the kernel has finished executing.
 */
#define CU_GRAPH_KERNEL_NODE_PORT_DEFAULT 0
/**
 * This port activates when all blocks of the kernel have performed cudaTriggerProgrammaticLaunchCompletion()
 * or have terminated. It must be used with edge type ::CU_GRAPH_DEPENDENCY_TYPE_PROGRAMMATIC. See also
 * ::CU_LAUNCH_ATTRIBUTE_PROGRAMMATIC_EVENT.
 */
#define CU_GRAPH_KERNEL_NODE_PORT_PROGRAMMATIC 1
/**
 * This port activates when all blocks of the kernel have begun execution. See also
 * ::CU_LAUNCH_ATTRIBUTE_LAUNCH_COMPLETION_EVENT.
 */
#define CU_GRAPH_KERNEL_NODE_PORT_LAUNCH_ORDER 2

/**
 * Optional annotation for edges in a CUDA graph. Note, all edges implicitly have annotations and
 * default to a zero-initialized value if not specified. A zero-initialized struct indicates a
 * standard full serialization of two nodes with memory visibility.
 */
typedef struct CUgraphEdgeData_st {
    unsigned char from_port; /**< This indicates when the dependency is triggered from the upstream
                                  node on the edge. The meaning is specfic to the node type. A value
                                  of 0 in all cases means full completion of the upstream node, with
                                  memory visibility to the downstream node or portion thereof
                                  (indicated by \c to_port).
                                  <br>
                                  Only kernel nodes define non-zero ports. A kernel node
                                  can use the following output port types:
                                  ::CU_GRAPH_KERNEL_NODE_PORT_DEFAULT, ::CU_GRAPH_KERNEL_NODE_PORT_PROGRAMMATIC,
                                  or ::CU_GRAPH_KERNEL_NODE_PORT_LAUNCH_ORDER. */
    unsigned char to_port; /**< This indicates what portion of the downstream node is dependent on
                                the upstream node or portion thereof (indicated by \c from_port). The
                                meaning is specific to the node type. A value of 0 in all cases means
                                the entirety of the downstream node is dependent on the upstream work.
                                <br>
                                Currently no node types define non-zero ports. Accordingly, this field
                                must be set to zero. */
    unsigned char type; /**< This should be populated with a value from ::CUgraphDependencyType. (It
                             is typed as char due to compiler-specific layout of bitfields.) See
                             ::CUgraphDependencyType. */
    unsigned char reserved[5]; /**< These bytes are unused and must be zeroed. This ensures
                                    compatibility if additional fields are added in the future. */
} CUgraphEdgeData;

/**
 * Graph instantiation results
*/
typedef enum CUgraphInstantiateResult_enum
{
    CUDA_GRAPH_INSTANTIATE_SUCCESS = 0,                          /**< Instantiation succeeded */
    CUDA_GRAPH_INSTANTIATE_ERROR = 1,                            /**< Instantiation failed for an unexpected reason which is described in the return value of the function */
    CUDA_GRAPH_INSTANTIATE_INVALID_STRUCTURE = 2,                /**< Instantiation failed due to invalid structure, such as cycles */
    CUDA_GRAPH_INSTANTIATE_NODE_OPERATION_NOT_SUPPORTED = 3,     /**< Instantiation for device launch failed because the graph contained an unsupported operation */
    CUDA_GRAPH_INSTANTIATE_MULTIPLE_CTXS_NOT_SUPPORTED = 4,      /**< Instantiation for device launch failed due to the nodes belonging to different contexts */
    CUDA_GRAPH_INSTANTIATE_CONDITIONAL_HANDLE_UNUSED = 5,        /**< One or more conditional handles are not associated with conditional nodes */
} CUgraphInstantiateResult;

/**
 * Graph instantiation parameters
 */
typedef struct CUDA_GRAPH_INSTANTIATE_PARAMS_st
{
	cuuint64_t flags;                    /**< Instantiation flags */
	CUstream hUploadStream;              /**< Upload stream */
	CUgraphNode hErrNode_out;            /**< The node which caused instantiation to fail, if any */
	CUgraphInstantiateResult result_out; /**< Whether instantiation was successful.  If it failed, the reason why */
} CUDA_GRAPH_INSTANTIATE_PARAMS;

typedef enum CUsynchronizationPolicy_enum {
    CU_SYNC_POLICY_AUTO = 1,
    CU_SYNC_POLICY_SPIN = 2,
    CU_SYNC_POLICY_YIELD = 3,
    CU_SYNC_POLICY_BLOCKING_SYNC = 4
} CUsynchronizationPolicy;

/**
 * Cluster scheduling policies. These may be passed to ::cuFuncSetAttribute or ::cuKernelSetAttribute
 */
typedef enum CUclusterSchedulingPolicy_enum {
    CU_CLUSTER_SCHEDULING_POLICY_DEFAULT        = 0, /**< the default policy */
    CU_CLUSTER_SCHEDULING_POLICY_SPREAD         = 1, /**< spread the blocks within a cluster to the SMs */
    CU_CLUSTER_SCHEDULING_POLICY_LOAD_BALANCING = 2  /**< allow the hardware to load-balance the blocks in a cluster to the SMs */
} CUclusterSchedulingPolicy;

/**
 * Memory Synchronization Domain
 *
 * A kernel can be launched in a specified memory synchronization domain that affects all memory operations issued by
 * that kernel. A memory barrier issued in one domain will only order memory operations in that domain, thus eliminating
 * latency increase from memory barriers ordering unrelated traffic.
 *
 * By default, kernels are launched in domain 0. Kernel launched with ::CU_LAUNCH_MEM_SYNC_DOMAIN_REMOTE will have a
 * different domain ID. User may also alter the domain ID with ::CUlaunchMemSyncDomainMap for a specific stream /
 * graph node / kernel launch. See ::CU_LAUNCH_ATTRIBUTE_MEM_SYNC_DOMAIN, ::cuStreamSetAttribute, ::cuLaunchKernelEx,
 * ::cuGraphKernelNodeSetAttribute.
 *
 * Memory operations done in kernels launched in different domains are considered system-scope distanced. In other
 * words, a GPU scoped memory synchronization is not sufficient for memory order to be observed by kernels in another
 * memory synchronization domain even if they are on the same GPU.
 */
typedef enum CUlaunchMemSyncDomain_enum {
    CU_LAUNCH_MEM_SYNC_DOMAIN_DEFAULT = 0,    /**< Launch kernels in the default domain */
    CU_LAUNCH_MEM_SYNC_DOMAIN_REMOTE  = 1     /**< Launch kernels in the remote domain */
} CUlaunchMemSyncDomain;

/**
 * Memory Synchronization Domain map
 *
 * See ::cudaLaunchMemSyncDomain.
 *
 * By default, kernels are launched in domain 0. Kernel launched with ::CU_LAUNCH_MEM_SYNC_DOMAIN_REMOTE will have a
 * different domain ID. User may also alter the domain ID with ::CUlaunchMemSyncDomainMap for a specific stream /
 * graph node / kernel launch. See ::CU_LAUNCH_ATTRIBUTE_MEM_SYNC_DOMAIN_MAP.
 *
 * Domain ID range is available through ::CU_DEVICE_ATTRIBUTE_MEM_SYNC_DOMAIN_COUNT.
 */
typedef struct CUlaunchMemSyncDomainMap_st {
    unsigned char default_;     /**< The default domain ID to use for designated kernels */
    unsigned char remote;       /**< The remote domain ID to use for designated kernels */
} CUlaunchMemSyncDomainMap;

/**
 * Launch attributes enum; used as id field of ::CUlaunchAttribute
 */
typedef enum CUlaunchAttributeID_enum {
    CU_LAUNCH_ATTRIBUTE_IGNORE = 0 /**< Ignored entry, for convenient composition */
  , CU_LAUNCH_ATTRIBUTE_ACCESS_POLICY_WINDOW   = 1 /**< Valid for streams, graph nodes, launches. See
                                                      ::CUlaunchAttributeValue::accessPolicyWindow. */
  , CU_LAUNCH_ATTRIBUTE_COOPERATIVE            = 2 /**< Valid for graph nodes, launches. See
                                                      ::CUlaunchAttributeValue::cooperative. */
  , CU_LAUNCH_ATTRIBUTE_SYNCHRONIZATION_POLICY = 3 /**< Valid for streams. See
                                                      ::CUlaunchAttributeValue::syncPolicy. */
  , CU_LAUNCH_ATTRIBUTE_CLUSTER_DIMENSION                    = 4 /**< Valid for graph nodes, launches. See ::CUlaunchAttributeValue::clusterDim. */
  , CU_LAUNCH_ATTRIBUTE_CLUSTER_SCHEDULING_POLICY_PREFERENCE = 5 /**< Valid for graph nodes, launches. See ::CUlaunchAttributeValue::clusterSchedulingPolicyPreference. */
  , CU_LAUNCH_ATTRIBUTE_PROGRAMMATIC_STREAM_SERIALIZATION    = 6 /**< Valid for launches. Setting
                                                                  ::CUlaunchAttributeValue::programmaticStreamSerializationAllowed
                                                                  to non-0 signals that the kernel will use programmatic
                                                                  means to resolve its stream dependency, so that the
                                                                  CUDA runtime should opportunistically allow the grid's
                                                                  execution to overlap with the previous kernel in the
                                                                  stream, if that kernel requests the overlap. The
                                                                  dependent launches can choose to wait on the
                                                                  dependency using the programmatic sync
                                                                  (cudaGridDependencySynchronize() or equivalent PTX
                                                                  instructions). */
  , CU_LAUNCH_ATTRIBUTE_PROGRAMMATIC_EVENT                   = 7 /**< Valid for launches. Set
                                                                      ::CUlaunchAttributeValue::programmaticEvent to
                                                                      record the event. Event recorded through this
                                                                      launch attribute is guaranteed to only trigger
                                                                      after all block in the associated kernel trigger
                                                                      the event. A block can trigger the event through
                                                                      PTX launchdep.release or CUDA builtin function
                                                                      cudaTriggerProgrammaticLaunchCompletion(). A
                                                                      trigger can also be inserted at the beginning of
                                                                      each block's execution if triggerAtBlockStart is
                                                                      set to non-0. The dependent launches can choose to
                                                                      wait on the dependency using the programmatic sync
                                                                      (cudaGridDependencySynchronize() or equivalent PTX
                                                                      instructions). Note that dependents (including the
                                                                      CPU thread calling cuEventSynchronize()) are not
                                                                      guaranteed to observe the release precisely when
                                                                      it is released.  For example, cuEventSynchronize()
                                                                      may only observe the event trigger long after the
                                                                      associated kernel has completed. This recording
                                                                      type is primarily meant for establishing
                                                                      programmatic dependency between device tasks. Note
                                                                      also this type of dependency allows, but does not
                                                                      guarantee, concurrent execution of tasks.
                                                                      <br>
                                                                      The event supplied must not be an interprocess or
                                                                      interop event. The event must disable timing (i.e.
                                                                      must be created with the ::CU_EVENT_DISABLE_TIMING
                                                                      flag set).
                                                                      */
  , CU_LAUNCH_ATTRIBUTE_PRIORITY               = 8 /**< Valid for streams, graph nodes, launches. See
                                                        ::CUlaunchAttributeValue::priority. */
  , CU_LAUNCH_ATTRIBUTE_MEM_SYNC_DOMAIN_MAP    = 9 /**< Valid for streams, graph nodes, launches. See
                                                      ::CUlaunchAttributeValue::memSyncDomainMap. */
  , CU_LAUNCH_ATTRIBUTE_MEM_SYNC_DOMAIN        = 10 /**< Valid for streams, graph nodes, launches. See
                                                       ::CUlaunchAttributeValue::memSyncDomain. */
  , CU_LAUNCH_ATTRIBUTE_PREFERRED_CLUSTER_DIMENSION = 11 /**< Valid for graph nodes, launches. Set
                                                              ::CUlaunchAttributeValue::preferredClusterDim
                                                              to allow the kernel launch to specify a preferred substitute
                                                              cluster dimension. Blocks may be grouped according to either
                                                              the dimensions specified with this attribute (grouped into a
                                                              "preferred substitute cluster"), or the one specified with
                                                              ::CU_LAUNCH_ATTRIBUTE_CLUSTER_DIMENSION attribute (grouped
                                                              into a "regular cluster"). The cluster dimensions of a
                                                              "preferred substitute cluster" shall be an integer multiple
                                                              greater than zero of the regular cluster dimensions. The
                                                              device will attempt - on a best-effort basis - to group
                                                              thread blocks into preferred clusters over grouping them
                                                              into regular clusters. When it deems necessary (primarily
                                                              when the device temporarily runs out of physical resources
                                                              to launch the larger preferred clusters), the device may
                                                              switch to launch the regular clusters instead to attempt to
                                                              utilize as much of the physical device resources as possible.
                                                              <br>
                                                              Each type of cluster will have its enumeration / coordinate
                                                              setup as if the grid consists solely of its type of cluster.
                                                              For example, if the preferred substitute cluster dimensions
                                                              double the regular cluster dimensions, there might be
                                                              simultaneously a regular cluster indexed at (1,0,0), and a
                                                              preferred cluster indexed at (1,0,0). In this example, the
                                                              preferred substitute cluster (1,0,0) replaces regular
                                                              clusters (2,0,0) and (3,0,0) and groups their blocks.
                                                              <br>
                                                              This attribute will only take effect when a regular cluster
                                                              dimension has been specified. The preferred substitute
                                                              cluster dimension must be an integer multiple greater than
                                                              zero of the regular cluster dimension and must divide the
                                                              grid. It must also be no more than `maxBlocksPerCluster`, if
                                                              it is set in the kernel's `__launch_bounds__`. Otherwise it
                                                              must be less than the maximum value the driver can support.
                                                              Otherwise, setting this attribute to a value physically
                                                              unable to fit on any particular device is permitted. */
  , CU_LAUNCH_ATTRIBUTE_LAUNCH_COMPLETION_EVENT = 12 /**< Valid for launches. Set
                                                          ::CUlaunchAttributeValue::launchCompletionEvent to record the
                                                          event.
                                                          <br>
                                                          Nominally, the event is triggered once all blocks of the kernel
                                                          have begun execution. Currently this is a best effort. If a kernel
                                                          B has a launch completion dependency on a kernel A, B may wait
                                                          until A is complete. Alternatively, blocks of B may begin before
                                                          all blocks of A have begun, for example if B can claim execution
                                                          resources unavailable to A (e.g. they run on different GPUs) or
                                                          if B is a higher priority than A.
                                                          Exercise caution if such an ordering inversion could lead
                                                          to deadlock.
                                                          <br>
                                                          A launch completion event is nominally similar to a programmatic
                                                          event with \c triggerAtBlockStart set except that it is not
                                                          visible to \c cudaGridDependencySynchronize() and can be used with
                                                          compute capability less than 9.0.
                                                          <br>
                                                          The event supplied must not be an interprocess or interop
                                                          event. The event must disable timing (i.e. must be created
                                                          with the ::CU_EVENT_DISABLE_TIMING flag set). */
  , CU_LAUNCH_ATTRIBUTE_DEVICE_UPDATABLE_KERNEL_NODE = 13 /**< Valid for graph nodes, launches. This attribute is graphs-only,
                                                               and passing it to a launch in a non-capturing stream will result
                                                               in an error.
                                                               <br>
                                                               ::CUlaunchAttributeValue::deviceUpdatableKernelNode::deviceUpdatable can 
                                                               only be set to 0 or 1. Setting the field to 1 indicates that the
                                                               corresponding kernel node should be device-updatable. On success, a handle
                                                               will be returned via
                                                               ::CUlaunchAttributeValue::deviceUpdatableKernelNode::devNode which can be
                                                               passed to the various device-side update functions to update the node's
                                                               kernel parameters from within another kernel. For more information on the
                                                               types of device updates that can be made, as well as the relevant limitations
                                                               thereof, see ::cudaGraphKernelNodeUpdatesApply.
                                                               <br>
                                                               Nodes which are device-updatable have additional restrictions compared to
                                                               regular kernel nodes. Firstly, device-updatable nodes cannot be removed
                                                               from their graph via ::cuGraphDestroyNode. Additionally, once opted-in
                                                               to this functionality, a node cannot opt out, and any attempt to set the
                                                               deviceUpdatable attribute to 0 will result in an error. Device-updatable
                                                               kernel nodes also cannot have their attributes copied to/from another kernel
                                                               node via ::cuGraphKernelNodeCopyAttributes. Graphs containing one or more
                                                               device-updatable nodes also do not allow multiple instantiation, and neither
                                                               the graph nor its instantiated version can be passed to ::cuGraphExecUpdate.
                                                               <br>
                                                               If a graph contains device-updatable nodes and updates those nodes from the device
                                                               from within the graph, the graph must be uploaded with ::cuGraphUpload before it
                                                               is launched. For such a graph, if host-side executable graph updates are made to the
                                                               device-updatable nodes, the graph must be uploaded before it is launched again. */
  , CU_LAUNCH_ATTRIBUTE_PREFERRED_SHARED_MEMORY_CARVEOUT = 14 /**< Valid for launches. On devices where the L1 cache and shared memory use the
                                                                   same hardware resources, setting ::CUlaunchAttributeValue::sharedMemCarveout to a 
                                                                   percentage between 0-100 signals the CUDA driver to set the shared memory carveout 
                                                                   preference, in percent of the total shared memory for that kernel launch. 
                                                                   This attribute takes precedence over ::CU_FUNC_ATTRIBUTE_PREFERRED_SHARED_MEMORY_CARVEOUT.
                                                                   This is only a hint, and the CUDA driver can choose a different configuration if
                                                                   required for the launch. */
#if defined(__CUDA_API_VERSION_INTERNAL) && !defined(__CUDA_API_VERSION_INTERNAL_ODR)
  , CU_LAUNCH_ATTRIBUTE_MAX
#endif
} CUlaunchAttributeID;

/**
 * Launch attributes union; used as value field of ::CUlaunchAttribute
 */
typedef union CUlaunchAttributeValue_union {
    char pad[64]; /* Pad to 64 bytes */
    CUaccessPolicyWindow accessPolicyWindow; /**< Value of launch attribute ::CU_LAUNCH_ATTRIBUTE_ACCESS_POLICY_WINDOW. */
    int cooperative; /**< Value of launch attribute ::CU_LAUNCH_ATTRIBUTE_COOPERATIVE. Nonzero indicates a cooperative
                        kernel (see ::cuLaunchCooperativeKernel). */
    CUsynchronizationPolicy syncPolicy; /**< Value of launch attribute
                                           ::CU_LAUNCH_ATTRIBUTE_SYNCHRONIZATION_POLICY. ::CUsynchronizationPolicy for
                                           work queued up in this stream */

    /**
     *  Value of launch attribute ::CU_LAUNCH_ATTRIBUTE_CLUSTER_DIMENSION that
     *  represents the desired cluster dimensions for the kernel. Opaque type
     *  with the following fields:
     *      - \p x - The X dimension of the cluster, in blocks. Must be a divisor
     *               of the grid X dimension.
     *      - \p y - The Y dimension of the cluster, in blocks. Must be a divisor
     *               of the grid Y dimension.
     *      - \p z - The Z dimension of the cluster, in blocks. Must be a divisor
     *               of the grid Z dimension.
     */
    struct {
        unsigned int x;
        unsigned int y;
        unsigned int z;
    } clusterDim;
    CUclusterSchedulingPolicy clusterSchedulingPolicyPreference; /**< Value of launch attribute
                                                                    ::CU_LAUNCH_ATTRIBUTE_CLUSTER_SCHEDULING_POLICY_PREFERENCE. Cluster
                                                                    scheduling policy preference for the kernel. */
    int programmaticStreamSerializationAllowed;  /**< Value of launch attribute
                                                   ::CU_LAUNCH_ATTRIBUTE_PROGRAMMATIC_STREAM_SERIALIZATION. */
    /**
     *  Value of launch attribute ::CU_LAUNCH_ATTRIBUTE_PROGRAMMATIC_EVENT
     *  with the following fields:
     *      - \p CUevent event - Event to fire when all blocks trigger it.
     *      - \p Event record flags, see ::cuEventRecordWithFlags. Does not accept :CU_EVENT_RECORD_EXTERNAL.
     *      - \p triggerAtBlockStart - If this is set to non-0, each block launch will automatically trigger the event.
     */
    struct {
        CUevent event;
        int flags;
        int triggerAtBlockStart;
    } programmaticEvent;
    /**
     * Value of launch attribute ::CU_LAUNCH_ATTRIBUTE_LAUNCH_COMPLETION_EVENT
     * with the following fields:
     *     - \p CUevent event - Event to fire when the last block launches
     *     - \p int flags; - Event record flags, see ::cuEventRecordWithFlags. Does not accept ::CU_EVENT_RECORD_EXTERNAL.
     */ 
    struct {
        CUevent event;
        int flags;
    } launchCompletionEvent;
    int priority; /**< Value of launch attribute ::CU_LAUNCH_ATTRIBUTE_PRIORITY. Execution priority of the kernel. */
    CUlaunchMemSyncDomainMap memSyncDomainMap; /**< Value of launch attribute
                                                  ::CU_LAUNCH_ATTRIBUTE_MEM_SYNC_DOMAIN_MAP. See
                                                  ::CUlaunchMemSyncDomainMap. */
    CUlaunchMemSyncDomain memSyncDomain;       /**< Value of launch attribute
                                                  ::CU_LAUNCH_ATTRIBUTE_MEM_SYNC_DOMAIN. See::CUlaunchMemSyncDomain */
    /**
     *  Value of launch attribute ::CU_LAUNCH_ATTRIBUTE_PREFERRED_CLUSTER_DIMENSION
     *  that represents the desired preferred cluster dimensions for the kernel.
     *  Opaque type with the following fields:
     *      - \p x - The X dimension of the preferred cluster, in blocks. Must
     *               be a divisor of the grid X dimension, and must be a
     *               multiple of the \p x field of ::CUlaunchAttributeValue::clusterDim.
     *      - \p y - The Y dimension of the preferred cluster, in blocks. Must
     *               be a divisor of the grid Y dimension, and must be a
     *               multiple of the \p y field of ::CUlaunchAttributeValue::clusterDim.
     *      - \p z - The Z dimension of the preferred cluster, in blocks. Must be
     *               equal to the \p z field of ::CUlaunchAttributeValue::clusterDim.
     */
    struct {
        unsigned int x;
        unsigned int y;
        unsigned int z;
    } preferredClusterDim;

    /**
     *  Value of launch attribute ::CU_LAUNCH_ATTRIBUTE_DEVICE_UPDATABLE_KERNEL_NODE.
     *  with the following fields:
     *      - \p int deviceUpdatable - Whether or not the resulting kernel node should be device-updatable.
     *      - \p CUgraphDeviceNode devNode - Returns a handle to pass to the various device-side update functions.
     */
    struct {
        int deviceUpdatable;
        CUgraphDeviceNode devNode;
    } deviceUpdatableKernelNode;
    unsigned int sharedMemCarveout; /**< Value of launch attribute ::CU_LAUNCH_ATTRIBUTE_PREFERRED_SHARED_MEMORY_CARVEOUT. */
} CUlaunchAttributeValue;

/**
 * Launch attribute
 */
typedef struct CUlaunchAttribute_st {
    CUlaunchAttributeID id; /**< Attribute to set */
    char pad[8 - sizeof(CUlaunchAttributeID)];
    CUlaunchAttributeValue value; /**< Value of the attribute */
} CUlaunchAttribute;

/**
 * CUDA extensible launch configuration
 */
typedef struct CUlaunchConfig_st {
    unsigned int gridDimX;       /**< Width of grid in blocks */
    unsigned int gridDimY;       /**< Height of grid in blocks */
    unsigned int gridDimZ;       /**< Depth of grid in blocks */
    unsigned int blockDimX;      /**< X dimension of each thread block */
    unsigned int blockDimY;      /**< Y dimension of each thread block */
    unsigned int blockDimZ;      /**< Z dimension of each thread block */
    unsigned int sharedMemBytes; /**< Dynamic shared-memory size per thread block in bytes */
    CUstream hStream;            /**< Stream identifier */
    CUlaunchAttribute *attrs;    /**< List of attributes; nullable if ::CUlaunchConfig::numAttrs == 0 */
    unsigned int numAttrs;       /**< Number of attributes populated in ::CUlaunchConfig::attrs */
} CUlaunchConfig;

typedef CUlaunchAttributeID CUkernelNodeAttrID;
#define CU_KERNEL_NODE_ATTRIBUTE_ACCESS_POLICY_WINDOW CU_LAUNCH_ATTRIBUTE_ACCESS_POLICY_WINDOW
#define CU_KERNEL_NODE_ATTRIBUTE_COOPERATIVE          CU_LAUNCH_ATTRIBUTE_COOPERATIVE
#define CU_KERNEL_NODE_ATTRIBUTE_CLUSTER_DIMENSION                    CU_LAUNCH_ATTRIBUTE_CLUSTER_DIMENSION
#define CU_KERNEL_NODE_ATTRIBUTE_CLUSTER_SCHEDULING_POLICY_PREFERENCE CU_LAUNCH_ATTRIBUTE_CLUSTER_SCHEDULING_POLICY_PREFERENCE
#define CU_KERNEL_NODE_ATTRIBUTE_PRIORITY             CU_LAUNCH_ATTRIBUTE_PRIORITY
#define CU_KERNEL_NODE_ATTRIBUTE_MEM_SYNC_DOMAIN_MAP  CU_LAUNCH_ATTRIBUTE_MEM_SYNC_DOMAIN_MAP
#define CU_KERNEL_NODE_ATTRIBUTE_MEM_SYNC_DOMAIN      CU_LAUNCH_ATTRIBUTE_MEM_SYNC_DOMAIN
#define CU_KERNEL_NODE_ATTRIBUTE_PREFERRED_CLUSTER_DIMENSION CU_LAUNCH_ATTRIBUTE_PREFERRED_CLUSTER_DIMENSION
#define CU_KERNEL_NODE_ATTRIBUTE_DEVICE_UPDATABLE_KERNEL_NODE CU_LAUNCH_ATTRIBUTE_DEVICE_UPDATABLE_KERNEL_NODE
#define CU_KERNEL_NODE_ATTRIBUTE_PREFERRED_SHARED_MEMORY_CARVEOUT CU_LAUNCH_ATTRIBUTE_PREFERRED_SHARED_MEMORY_CARVEOUT

typedef CUlaunchAttributeValue CUkernelNodeAttrValue_v1;
typedef CUkernelNodeAttrValue_v1 CUkernelNodeAttrValue;

/**
 * Possible stream capture statuses returned by ::cuStreamIsCapturing
 */
typedef enum CUstreamCaptureStatus_enum {
    CU_STREAM_CAPTURE_STATUS_NONE        = 0, /**< Stream is not capturing */
    CU_STREAM_CAPTURE_STATUS_ACTIVE      = 1, /**< Stream is actively capturing */
    CU_STREAM_CAPTURE_STATUS_INVALIDATED = 2  /**< Stream is part of a capture sequence that
                                                   has been invalidated, but not terminated */
} CUstreamCaptureStatus;

/**
 * Possible modes for stream capture thread interactions. For more details see
 * ::cuStreamBeginCapture and ::cuThreadExchangeStreamCaptureMode
 */
typedef enum CUstreamCaptureMode_enum {
    CU_STREAM_CAPTURE_MODE_GLOBAL       = 0,
    CU_STREAM_CAPTURE_MODE_THREAD_LOCAL = 1,
    CU_STREAM_CAPTURE_MODE_RELAXED      = 2
} CUstreamCaptureMode;

typedef CUlaunchAttributeID CUstreamAttrID;
#define CU_STREAM_ATTRIBUTE_ACCESS_POLICY_WINDOW   CU_LAUNCH_ATTRIBUTE_ACCESS_POLICY_WINDOW
#define CU_STREAM_ATTRIBUTE_SYNCHRONIZATION_POLICY CU_LAUNCH_ATTRIBUTE_SYNCHRONIZATION_POLICY
#define CU_STREAM_ATTRIBUTE_PRIORITY               CU_LAUNCH_ATTRIBUTE_PRIORITY
#define CU_STREAM_ATTRIBUTE_MEM_SYNC_DOMAIN_MAP    CU_LAUNCH_ATTRIBUTE_MEM_SYNC_DOMAIN_MAP
#define CU_STREAM_ATTRIBUTE_MEM_SYNC_DOMAIN        CU_LAUNCH_ATTRIBUTE_MEM_SYNC_DOMAIN

typedef CUlaunchAttributeValue CUstreamAttrValue_v1;
typedef CUstreamAttrValue_v1 CUstreamAttrValue;

/**
 * Flags to specify search options. For more details see ::cuGetProcAddress
 */
typedef enum CUdriverProcAddress_flags_enum {
    CU_GET_PROC_ADDRESS_DEFAULT = 0,                        /**< Default search mode for driver symbols. */
    CU_GET_PROC_ADDRESS_LEGACY_STREAM = 1 << 0,             /**< Search for legacy versions of driver symbols. */
    CU_GET_PROC_ADDRESS_PER_THREAD_DEFAULT_STREAM = 1 << 1  /**< Search for per-thread versions of driver symbols. */ 
} CUdriverProcAddress_flags;

/**
 * Flags to indicate search status. For more details see ::cuGetProcAddress
 */
typedef enum CUdriverProcAddressQueryResult_enum {
    CU_GET_PROC_ADDRESS_SUCCESS                = 0,  /**< Symbol was succesfully found */
    CU_GET_PROC_ADDRESS_SYMBOL_NOT_FOUND       = 1,  /**< Symbol was not found in search */
    CU_GET_PROC_ADDRESS_VERSION_NOT_SUFFICIENT = 2   /**< Symbol was found but version supplied was not sufficient */
}  CUdriverProcAddressQueryResult;

/**
 * Execution Affinity Types 
 */
typedef enum CUexecAffinityType_enum {
    CU_EXEC_AFFINITY_TYPE_SM_COUNT = 0,  /**< Create a context with limited SMs. */
    CU_EXEC_AFFINITY_TYPE_MAX
} CUexecAffinityType;

/**
 * Value for ::CU_EXEC_AFFINITY_TYPE_SM_COUNT
 */
typedef struct CUexecAffinitySmCount_st {
    unsigned int val;    /**< The number of SMs the context is limited to use. */
} CUexecAffinitySmCount_v1;
typedef CUexecAffinitySmCount_v1 CUexecAffinitySmCount;

/**
 * Execution Affinity Parameters 
 */
typedef struct CUexecAffinityParam_st {
    CUexecAffinityType type;
    union {
        CUexecAffinitySmCount smCount;    /** Value for ::CU_EXEC_AFFINITY_TYPE_SM_COUNT */
    } param;
} CUexecAffinityParam_v1;
/**
 * Execution Affinity Parameters
 */
typedef CUexecAffinityParam_v1 CUexecAffinityParam;

typedef enum CUcigDataType_enum {
    CIG_DATA_TYPE_D3D12_COMMAND_QUEUE = 0x1,    /** D3D12 Command Queue Handle */
} CUcigDataType;

/**
* CIG Context Create Params
*/
typedef struct CUctxCigParam_st {
    CUcigDataType sharedDataType;
    void* sharedData;
} CUctxCigParam;

/**
* Params for creating CUDA context
* Exactly one of execAffinityParams and cigParams 
* must be non-NULL.
*/
typedef struct CUctxCreateParams_st {
    CUexecAffinityParam *execAffinityParams;
    int                  numExecAffinityParams;
    CUctxCigParam       *cigParams;
} CUctxCreateParams;

/**
 * Library options to be specified with ::cuLibraryLoadData() or ::cuLibraryLoadFromFile()
 */
typedef enum CUlibraryOption_enum
{
    CU_LIBRARY_HOST_UNIVERSAL_FUNCTION_AND_DATA_TABLE = 0,

    /**
     * Specifes that the argument \p code passed to ::cuLibraryLoadData() will be preserved.
     * Specifying this option will let the driver know that \p code can be accessed at any point
     * until ::cuLibraryUnload(). The default behavior is for the driver to allocate and
     * maintain its own copy of \p code. Note that this is only a memory usage optimization
     * hint and the driver can choose to ignore it if required.
     * Specifying this option with ::cuLibraryLoadFromFile() is invalid and
     * will return ::CUDA_ERROR_INVALID_VALUE.
     */
    CU_LIBRARY_BINARY_IS_PRESERVED = 1,

    CU_LIBRARY_NUM_OPTIONS
} CUlibraryOption;

typedef struct CUlibraryHostUniversalFunctionAndDataTable_st
{
    void *functionTable;
    size_t functionWindowSize;
    void *dataTable;
    size_t dataWindowSize;
} CUlibraryHostUniversalFunctionAndDataTable;

/**
 * Error codes
 */
typedef enum cudaError_enum {
    /**
     * The API call returned with no errors. In the case of query calls, this
     * also means that the operation being queried is complete (see
     * ::cuEventQuery() and ::cuStreamQuery()).
     */
    CUDA_SUCCESS                              = 0,

    /**
     * This indicates that one or more of the parameters passed to the API call
     * is not within an acceptable range of values.
     */
    CUDA_ERROR_INVALID_VALUE                  = 1,

    /**
     * The API call failed because it was unable to allocate enough memory or
     * other resources to perform the requested operation.
     */
    CUDA_ERROR_OUT_OF_MEMORY                  = 2,

    /**
     * This indicates that the CUDA driver has not been initialized with
     * ::cuInit() or that initialization has failed.
     */
    CUDA_ERROR_NOT_INITIALIZED                = 3,

    /**
     * This indicates that the CUDA driver is in the process of shutting down.
     */
    CUDA_ERROR_DEINITIALIZED                  = 4,

    /**
     * This indicates profiler is not initialized for this run. This can
     * happen when the application is running with external profiling tools
     * like visual profiler.
     */
    CUDA_ERROR_PROFILER_DISABLED              = 5,

    /**
     * \deprecated
     * This error return is deprecated as of CUDA 5.0. It is no longer an error
     * to attempt to enable/disable the profiling via ::cuProfilerStart or
     * ::cuProfilerStop without initialization.
     */
    CUDA_ERROR_PROFILER_NOT_INITIALIZED       = 6,

    /**
     * \deprecated
     * This error return is deprecated as of CUDA 5.0. It is no longer an error
     * to call cuProfilerStart() when profiling is already enabled.
     */
    CUDA_ERROR_PROFILER_ALREADY_STARTED       = 7,

    /**
     * \deprecated
     * This error return is deprecated as of CUDA 5.0. It is no longer an error
     * to call cuProfilerStop() when profiling is already disabled.
     */
    CUDA_ERROR_PROFILER_ALREADY_STOPPED       = 8,

    /**
     * This indicates that the CUDA driver that the application has loaded is a
     * stub library. Applications that run with the stub rather than a real
     * driver loaded will result in CUDA API returning this error.
     */
    CUDA_ERROR_STUB_LIBRARY                   = 34,

    /**  
     * This indicates that requested CUDA device is unavailable at the current
     * time. Devices are often unavailable due to use of
     * ::CU_COMPUTEMODE_EXCLUSIVE_PROCESS or ::CU_COMPUTEMODE_PROHIBITED.
     */
    CUDA_ERROR_DEVICE_UNAVAILABLE            = 46,

    /**
     * This indicates that no CUDA-capable devices were detected by the installed
     * CUDA driver.
     */
    CUDA_ERROR_NO_DEVICE                      = 100,

    /**
     * This indicates that the device ordinal supplied by the user does not
     * correspond to a valid CUDA device or that the action requested is
     * invalid for the specified device.
     */
    CUDA_ERROR_INVALID_DEVICE                 = 101,

    /**
     * This error indicates that the Grid license is not applied.
     */
    CUDA_ERROR_DEVICE_NOT_LICENSED            = 102,

    /**
     * This indicates that the device kernel image is invalid. This can also
     * indicate an invalid CUDA module.
     */
    CUDA_ERROR_INVALID_IMAGE                  = 200,

    /**
     * This most frequently indicates that there is no context bound to the
     * current thread. This can also be returned if the context passed to an
     * API call is not a valid handle (such as a context that has had
     * ::cuCtxDestroy() invoked on it). This can also be returned if a user
     * mixes different API versions (i.e. 3010 context with 3020 API calls).
     * See ::cuCtxGetApiVersion() for more details.
     * This can also be returned if the green context passed to an API call
     * was not converted to a ::CUcontext using ::cuCtxFromGreenCtx API.
     */
    CUDA_ERROR_INVALID_CONTEXT                = 201,

    /**
     * This indicated that the context being supplied as a parameter to the
     * API call was already the active context.
     * \deprecated
     * This error return is deprecated as of CUDA 3.2. It is no longer an
     * error to attempt to push the active context via ::cuCtxPushCurrent().
     */
    CUDA_ERROR_CONTEXT_ALREADY_CURRENT        = 202,

    /**
     * This indicates that a map or register operation has failed.
     */
    CUDA_ERROR_MAP_FAILED                     = 205,

    /**
     * This indicates that an unmap or unregister operation has failed.
     */
    CUDA_ERROR_UNMAP_FAILED                   = 206,

    /**
     * This indicates that the specified array is currently mapped and thus
     * cannot be destroyed.
     */
    CUDA_ERROR_ARRAY_IS_MAPPED                = 207,

    /**
     * This indicates that the resource is already mapped.
     */
    CUDA_ERROR_ALREADY_MAPPED                 = 208,

    /**
     * This indicates that there is no kernel image available that is suitable
     * for the device. This can occur when a user specifies code generation
     * options for a particular CUDA source file that do not include the
     * corresponding device configuration.
     */
    CUDA_ERROR_NO_BINARY_FOR_GPU              = 209,

    /**
     * This indicates that a resource has already been acquired.
     */
    CUDA_ERROR_ALREADY_ACQUIRED               = 210,

    /**
     * This indicates that a resource is not mapped.
     */
    CUDA_ERROR_NOT_MAPPED                     = 211,

    /**
     * This indicates that a mapped resource is not available for access as an
     * array.
     */
    CUDA_ERROR_NOT_MAPPED_AS_ARRAY            = 212,

    /**
     * This indicates that a mapped resource is not available for access as a
     * pointer.
     */
    CUDA_ERROR_NOT_MAPPED_AS_POINTER          = 213,

    /**
     * This indicates that an uncorrectable ECC error was detected during
     * execution.
     */
    CUDA_ERROR_ECC_UNCORRECTABLE              = 214,

    /**
     * This indicates that the ::CUlimit passed to the API call is not
     * supported by the active device.
     */
    CUDA_ERROR_UNSUPPORTED_LIMIT              = 215,

    /**
     * This indicates that the ::CUcontext passed to the API call can
     * only be bound to a single CPU thread at a time but is already
     * bound to a CPU thread.
     */
    CUDA_ERROR_CONTEXT_ALREADY_IN_USE         = 216,

    /**
     * This indicates that peer access is not supported across the given
     * devices.
     */
    CUDA_ERROR_PEER_ACCESS_UNSUPPORTED        = 217,

    /**
     * This indicates that a PTX JIT compilation failed.
     */
    CUDA_ERROR_INVALID_PTX                    = 218,

    /**
     * This indicates an error with OpenGL or DirectX context.
     */
    CUDA_ERROR_INVALID_GRAPHICS_CONTEXT       = 219,

    /**
    * This indicates that an uncorrectable NVLink error was detected during the
    * execution.
    */
    CUDA_ERROR_NVLINK_UNCORRECTABLE           = 220,

    /**
    * This indicates that the PTX JIT compiler library was not found.
    */
    CUDA_ERROR_JIT_COMPILER_NOT_FOUND         = 221,

    /**
     * This indicates that the provided PTX was compiled with an unsupported toolchain.
     */

    CUDA_ERROR_UNSUPPORTED_PTX_VERSION        = 222,

    /**
     * This indicates that the PTX JIT compilation was disabled.
     */
    CUDA_ERROR_JIT_COMPILATION_DISABLED       = 223,

    /**
     * This indicates that the ::CUexecAffinityType passed to the API call is not
     * supported by the active device.
     */ 
    CUDA_ERROR_UNSUPPORTED_EXEC_AFFINITY      = 224,

    /**
     * This indicates that the code to be compiled by the PTX JIT contains
     * unsupported call to cudaDeviceSynchronize.
     */
    CUDA_ERROR_UNSUPPORTED_DEVSIDE_SYNC       = 225,

    /**
     * This indicates that an exception occurred on the device that is now
     * contained by the GPU's error containment capability. Common causes are -
     * a. Certain types of invalid accesses of peer GPU memory over nvlink
     * b. Certain classes of hardware errors
     * This leaves the process in an inconsistent state and any further CUDA
     * work will return the same error. To continue using CUDA, the process must
     * be terminated and relaunched.
     */
    CUDA_ERROR_CONTAINED                      = 226,

    /**
     * This indicates that the device kernel source is invalid. This includes
     * compilation/linker errors encountered in device code or user error.
     */
    CUDA_ERROR_INVALID_SOURCE                 = 300,

    /**
     * This indicates that the file specified was not found.
     */
    CUDA_ERROR_FILE_NOT_FOUND                 = 301,

    /**
     * This indicates that a link to a shared object failed to resolve.
     */
    CUDA_ERROR_SHARED_OBJECT_SYMBOL_NOT_FOUND = 302,

    /**
     * This indicates that initialization of a shared object failed.
     */
    CUDA_ERROR_SHARED_OBJECT_INIT_FAILED      = 303,

    /**
     * This indicates that an OS call failed.
     */
    CUDA_ERROR_OPERATING_SYSTEM               = 304,

    /**
     * This indicates that a resource handle passed to the API call was not
     * valid. Resource handles are opaque types like ::CUstream and ::CUevent.
     */
    CUDA_ERROR_INVALID_HANDLE                 = 400,

    /**
     * This indicates that a resource required by the API call is not in a
     * valid state to perform the requested operation.
     */
    CUDA_ERROR_ILLEGAL_STATE                  = 401,

    /**
     * This indicates an attempt was made to introspect an object in a way that
     * would discard semantically important information. This is either due to
     * the object using funtionality newer than the API version used to
     * introspect it or omission of optional return arguments.
     */
    CUDA_ERROR_LOSSY_QUERY                    = 402,

    /**
     * This indicates that a named symbol was not found. Examples of symbols
     * are global/constant variable names, driver function names, texture names,
     * and surface names.
     */
    CUDA_ERROR_NOT_FOUND                      = 500,

    /**
     * This indicates that asynchronous operations issued previously have not
     * completed yet. This result is not actually an error, but must be indicated
     * differently than ::CUDA_SUCCESS (which indicates completion). Calls that
     * may return this value include ::cuEventQuery() and ::cuStreamQuery().
     */
    CUDA_ERROR_NOT_READY                      = 600,

    /**
     * While executing a kernel, the device encountered a
     * load or store instruction on an invalid memory address.
     * This leaves the process in an inconsistent state and any further CUDA work
     * will return the same error. To continue using CUDA, the process must be terminated
     * and relaunched.
     */
    CUDA_ERROR_ILLEGAL_ADDRESS                = 700,

    /**
     * This indicates that a launch did not occur because it did not have
     * appropriate resources. This error usually indicates that the user has
     * attempted to pass too many arguments to the device kernel, or the
     * kernel launch specifies too many threads for the kernel's register
     * count. Passing arguments of the wrong size (i.e. a 64-bit pointer
     * when a 32-bit int is expected) is equivalent to passing too many
     * arguments and can also result in this error.
     */
    CUDA_ERROR_LAUNCH_OUT_OF_RESOURCES        = 701,

    /**
     * This indicates that the device kernel took too long to execute. This can
     * only occur if timeouts are enabled - see the device attribute
     * ::CU_DEVICE_ATTRIBUTE_KERNEL_EXEC_TIMEOUT for more information.
     * This leaves the process in an inconsistent state and any further CUDA work
     * will return the same error. To continue using CUDA, the process must be terminated
     * and relaunched.
     */
    CUDA_ERROR_LAUNCH_TIMEOUT                 = 702,

    /**
     * This error indicates a kernel launch that uses an incompatible texturing
     * mode.
     */
    CUDA_ERROR_LAUNCH_INCOMPATIBLE_TEXTURING  = 703,

    /**
     * This error indicates that a call to ::cuCtxEnablePeerAccess() is
     * trying to re-enable peer access to a context which has already
     * had peer access to it enabled.
     */
    CUDA_ERROR_PEER_ACCESS_ALREADY_ENABLED    = 704,

    /**
     * This error indicates that ::cuCtxDisablePeerAccess() is
     * trying to disable peer access which has not been enabled yet
     * via ::cuCtxEnablePeerAccess().
     */
    CUDA_ERROR_PEER_ACCESS_NOT_ENABLED        = 705,

    /**
     * This error indicates that the primary context for the specified device
     * has already been initialized.
     */
    CUDA_ERROR_PRIMARY_CONTEXT_ACTIVE         = 708,

    /**
     * This error indicates that the context current to the calling thread
     * has been destroyed using ::cuCtxDestroy, or is a primary context which
     * has not yet been initialized.
     */
    CUDA_ERROR_CONTEXT_IS_DESTROYED           = 709,

    /**
     * A device-side assert triggered during kernel execution. The context
     * cannot be used anymore, and must be destroyed. All existing device
     * memory allocations from this context are invalid and must be
     * reconstructed if the program is to continue using CUDA.
     */
    CUDA_ERROR_ASSERT                         = 710,

    /**
     * This error indicates that the hardware resources required to enable
     * peer access have been exhausted for one or more of the devices
     * passed to ::cuCtxEnablePeerAccess().
     */
    CUDA_ERROR_TOO_MANY_PEERS                 = 711,

    /**
     * This error indicates that the memory range passed to ::cuMemHostRegister()
     * has already been registered.
     */
    CUDA_ERROR_HOST_MEMORY_ALREADY_REGISTERED = 712,

    /**
     * This error indicates that the pointer passed to ::cuMemHostUnregister()
     * does not correspond to any currently registered memory region.
     */
    CUDA_ERROR_HOST_MEMORY_NOT_REGISTERED     = 713,

    /**
     * While executing a kernel, the device encountered a stack error.
     * This can be due to stack corruption or exceeding the stack size limit.
     * This leaves the process in an inconsistent state and any further CUDA work
     * will return the same error. To continue using CUDA, the process must be terminated
     * and relaunched.
     */
    CUDA_ERROR_HARDWARE_STACK_ERROR           = 714,

    /**
     * While executing a kernel, the device encountered an illegal instruction.
     * This leaves the process in an inconsistent state and any further CUDA work
     * will return the same error. To continue using CUDA, the process must be terminated
     * and relaunched.
     */
    CUDA_ERROR_ILLEGAL_INSTRUCTION            = 715,

    /**
     * While executing a kernel, the device encountered a load or store instruction
     * on a memory address which is not aligned.
     * This leaves the process in an inconsistent state and any further CUDA work
     * will return the same error. To continue using CUDA, the process must be terminated
     * and relaunched.
     */
    CUDA_ERROR_MISALIGNED_ADDRESS             = 716,

    /**
     * While executing a kernel, the device encountered an instruction
     * which can only operate on memory locations in certain address spaces
     * (global, shared, or local), but was supplied a memory address not
     * belonging to an allowed address space.
     * This leaves the process in an inconsistent state and any further CUDA work
     * will return the same error. To continue using CUDA, the process must be terminated
     * and relaunched.
     */
    CUDA_ERROR_INVALID_ADDRESS_SPACE          = 717,

    /**
     * While executing a kernel, the device program counter wrapped its address space.
     * This leaves the process in an inconsistent state and any further CUDA work
     * will return the same error. To continue using CUDA, the process must be terminated
     * and relaunched.
     */
    CUDA_ERROR_INVALID_PC                     = 718,

    /**
     * An exception occurred on the device while executing a kernel. Common
     * causes include dereferencing an invalid device pointer and accessing
     * out of bounds shared memory. Less common cases can be system specific - more
     * information about these cases can be found in the system specific user guide.
     * This leaves the process in an inconsistent state and any further CUDA work
     * will return the same error. To continue using CUDA, the process must be terminated
     * and relaunched.
     */
    CUDA_ERROR_LAUNCH_FAILED                  = 719,

    /**
     * This error indicates that the number of blocks launched per grid for a kernel that was
     * launched via either ::cuLaunchCooperativeKernel or ::cuLaunchCooperativeKernelMultiDevice
     * exceeds the maximum number of blocks as allowed by ::cuOccupancyMaxActiveBlocksPerMultiprocessor
     * or ::cuOccupancyMaxActiveBlocksPerMultiprocessorWithFlags times the number of multiprocessors
     * as specified by the device attribute ::CU_DEVICE_ATTRIBUTE_MULTIPROCESSOR_COUNT.
     */
    CUDA_ERROR_COOPERATIVE_LAUNCH_TOO_LARGE   = 720,

    /**
     * An exception occurred on the device while exiting a kernel using tensor memory: the
     * tensor memory was not completely deallocated. This leaves the process in an inconsistent
     * state and any further CUDA work will return the same error. To continue using CUDA, the
     * process must be terminated and relaunched.
     */
    CUDA_ERROR_TENSOR_MEMORY_LEAK             = 721,

    /**
     * This error indicates that the attempted operation is not permitted.
     */
    CUDA_ERROR_NOT_PERMITTED                  = 800,

    /**
     * This error indicates that the attempted operation is not supported
     * on the current system or device.
     */
    CUDA_ERROR_NOT_SUPPORTED                  = 801,

    /**
     * This error indicates that the system is not yet ready to start any CUDA
     * work.  To continue using CUDA, verify the system configuration is in a
     * valid state and all required driver daemons are actively running.
     * More information about this error can be found in the system specific
     * user guide.
     */
    CUDA_ERROR_SYSTEM_NOT_READY               = 802,

    /**
     * This error indicates that there is a mismatch between the versions of
     * the display driver and the CUDA driver. Refer to the compatibility documentation
     * for supported versions.
     */
    CUDA_ERROR_SYSTEM_DRIVER_MISMATCH         = 803,

    /**
     * This error indicates that the system was upgraded to run with forward compatibility
     * but the visible hardware detected by CUDA does not support this configuration.
     * Refer to the compatibility documentation for the supported hardware matrix or ensure
     * that only supported hardware is visible during initialization via the CUDA_VISIBLE_DEVICES
     * environment variable.
     */
    CUDA_ERROR_COMPAT_NOT_SUPPORTED_ON_DEVICE = 804,

    /**
     * This error indicates that the MPS client failed to connect to the MPS control daemon or the MPS server.
     */
    CUDA_ERROR_MPS_CONNECTION_FAILED          = 805,

    /**
     * This error indicates that the remote procedural call between the MPS server and the MPS client failed.
     */
    CUDA_ERROR_MPS_RPC_FAILURE                = 806,

    /**
     * This error indicates that the MPS server is not ready to accept new MPS client requests.
     * This error can be returned when the MPS server is in the process of recovering from a fatal failure.
     */
    CUDA_ERROR_MPS_SERVER_NOT_READY           = 807,

    /**
     * This error indicates that the hardware resources required to create MPS client have been exhausted.
     */
    CUDA_ERROR_MPS_MAX_CLIENTS_REACHED        = 808,

    /**
     * This error indicates the the hardware resources required to support device connections have been exhausted.
     */
    CUDA_ERROR_MPS_MAX_CONNECTIONS_REACHED    = 809,

    /**
     * This error indicates that the MPS client has been terminated by the server. To continue using CUDA, the process must be terminated and relaunched.
     */
    CUDA_ERROR_MPS_CLIENT_TERMINATED          = 810,

    /**
     * This error indicates that the module is using CUDA Dynamic Parallelism, but the current configuration, like MPS, does not support it.
     */
    CUDA_ERROR_CDP_NOT_SUPPORTED              = 811,

    /**
     * This error indicates that a module contains an unsupported interaction between different versions of CUDA Dynamic Parallelism.
     */
    CUDA_ERROR_CDP_VERSION_MISMATCH           = 812,

    /**
     * This error indicates that the operation is not permitted when
     * the stream is capturing.
     */
    CUDA_ERROR_STREAM_CAPTURE_UNSUPPORTED     = 900,

    /**
     * This error indicates that the current capture sequence on the stream
     * has been invalidated due to a previous error.
     */
    CUDA_ERROR_STREAM_CAPTURE_INVALIDATED     = 901,

    /**
     * This error indicates that the operation would have resulted in a merge
     * of two independent capture sequences.
     */
    CUDA_ERROR_STREAM_CAPTURE_MERGE           = 902,

    /**
     * This error indicates that the capture was not initiated in this stream.
     */
    CUDA_ERROR_STREAM_CAPTURE_UNMATCHED       = 903,

    /**
     * This error indicates that the capture sequence contains a fork that was
     * not joined to the primary stream.
     */
    CUDA_ERROR_STREAM_CAPTURE_UNJOINED        = 904,

    /**
     * This error indicates that a dependency would have been created which
     * crosses the capture sequence boundary. Only implicit in-stream ordering
     * dependencies are allowed to cross the boundary.
     */
    CUDA_ERROR_STREAM_CAPTURE_ISOLATION       = 905,

    /**
     * This error indicates a disallowed implicit dependency on a current capture
     * sequence from cudaStreamLegacy.
     */
    CUDA_ERROR_STREAM_CAPTURE_IMPLICIT        = 906,

    /**
     * This error indicates that the operation is not permitted on an event which
     * was last recorded in a capturing stream.
     */
    CUDA_ERROR_CAPTURED_EVENT                 = 907,

    /**
     * A stream capture sequence not initiated with the ::CU_STREAM_CAPTURE_MODE_RELAXED
     * argument to ::cuStreamBeginCapture was passed to ::cuStreamEndCapture in a
     * different thread.
     */
    CUDA_ERROR_STREAM_CAPTURE_WRONG_THREAD    = 908,

    /**
     * This error indicates that the timeout specified for the wait operation has lapsed.
     */
    CUDA_ERROR_TIMEOUT                        = 909,

    /**
     * This error indicates that the graph update was not performed because it included 
     * changes which violated constraints specific to instantiated graph update.
     */
    CUDA_ERROR_GRAPH_EXEC_UPDATE_FAILURE      = 910,

    /**
     * This indicates that an async error has occurred in a device outside of CUDA.
     * If CUDA was waiting for an external device's signal before consuming shared data,
     * the external device signaled an error indicating that the data is not valid for
     * consumption. This leaves the process in an inconsistent state and any further CUDA
     * work will return the same error. To continue using CUDA, the process must be
     * terminated and relaunched.
     */
    CUDA_ERROR_EXTERNAL_DEVICE               = 911,

    /**
     * Indicates a kernel launch error due to cluster misconfiguration.
     */
    CUDA_ERROR_INVALID_CLUSTER_SIZE           = 912,

    /**
     * Indiciates a function handle is not loaded when calling an API that requires
     * a loaded function.
    */
    CUDA_ERROR_FUNCTION_NOT_LOADED            = 913,

    /**
     * This error indicates one or more resources passed in are not valid resource
     * types for the operation.
    */
    CUDA_ERROR_INVALID_RESOURCE_TYPE          = 914,

    /**
     * This error indicates one or more resources are insufficient or non-applicable for
     * the operation.
    */
    CUDA_ERROR_INVALID_RESOURCE_CONFIGURATION = 915,

    /**
     * This error indicates that an error happened during the key rotation
     * sequence.
    */
    CUDA_ERROR_KEY_ROTATION                   = 916,

    /**
     * This indicates that an unknown internal error has occurred.
     */
    CUDA_ERROR_UNKNOWN                        = 999
} CUresult;

/**
 * P2P Attributes
 */
typedef enum CUdevice_P2PAttribute_enum {
    CU_DEVICE_P2P_ATTRIBUTE_PERFORMANCE_RANK                     = 0x01,  /**< A relative value indicating the performance of the link between two devices */
    CU_DEVICE_P2P_ATTRIBUTE_ACCESS_SUPPORTED                     = 0x02,  /**< P2P Access is enable */
    CU_DEVICE_P2P_ATTRIBUTE_NATIVE_ATOMIC_SUPPORTED              = 0x03,  /**< Atomic operation over the link supported */
    CU_DEVICE_P2P_ATTRIBUTE_ACCESS_ACCESS_SUPPORTED              = 0x04,  /**< \deprecated use CU_DEVICE_P2P_ATTRIBUTE_CUDA_ARRAY_ACCESS_SUPPORTED instead */
    CU_DEVICE_P2P_ATTRIBUTE_CUDA_ARRAY_ACCESS_SUPPORTED          = 0x04   /**< Accessing CUDA arrays over the link supported */
} CUdevice_P2PAttribute;

/**
 * CUDA stream callback
 * \param hStream The stream the callback was added to, as passed to ::cuStreamAddCallback.  May be NULL.
 * \param status ::CUDA_SUCCESS or any persistent error on the stream.
 * \param userData User parameter provided at registration.
 */
typedef void (CUDA_CB *CUstreamCallback)(CUstream hStream, CUresult status, void *userData);

/**
 * Block size to per-block dynamic shared memory mapping for a certain
 * kernel \param blockSize Block size of the kernel.
 *
 * \return The dynamic shared memory needed by a block.
 */
typedef size_t (CUDA_CB *CUoccupancyB2DSize)(int blockSize);

/**
 * If set, host memory is portable between CUDA contexts.
 * Flag for ::cuMemHostAlloc()
 */
#define CU_MEMHOSTALLOC_PORTABLE        0x01

/**
 * If set, host memory is mapped into CUDA address space and
 * ::cuMemHostGetDevicePointer() may be called on the host pointer.
 * Flag for ::cuMemHostAlloc()
 */
#define CU_MEMHOSTALLOC_DEVICEMAP       0x02

/**
 * If set, host memory is allocated as write-combined - fast to write,
 * faster to DMA, slow to read except via SSE4 streaming load instruction
 * (MOVNTDQA).
 * Flag for ::cuMemHostAlloc()
 */
#define CU_MEMHOSTALLOC_WRITECOMBINED   0x04

/**
 * If set, host memory is portable between CUDA contexts.
 * Flag for ::cuMemHostRegister()
 */
#define CU_MEMHOSTREGISTER_PORTABLE     0x01

/**
 * If set, host memory is mapped into CUDA address space and
 * ::cuMemHostGetDevicePointer() may be called on the host pointer.
 * Flag for ::cuMemHostRegister()
 */
#define CU_MEMHOSTREGISTER_DEVICEMAP    0x02

/**
 * If set, the passed memory pointer is treated as pointing to some
 * memory-mapped I/O space, e.g. belonging to a third-party PCIe device.
 * On Windows the flag is a no-op.
 * On Linux that memory is marked as non cache-coherent for the GPU and
 * is expected to be physically contiguous. It may return
 * ::CUDA_ERROR_NOT_PERMITTED if run as an unprivileged user,
 * ::CUDA_ERROR_NOT_SUPPORTED on older Linux kernel versions.
 * On all other platforms, it is not supported and ::CUDA_ERROR_NOT_SUPPORTED
 * is returned.
 * Flag for ::cuMemHostRegister()
 */
#define CU_MEMHOSTREGISTER_IOMEMORY     0x04

/**
* If set, the passed memory pointer is treated as pointing to memory that is
* considered read-only by the device.  On platforms without
* ::CU_DEVICE_ATTRIBUTE_PAGEABLE_MEMORY_ACCESS_USES_HOST_PAGE_TABLES, this flag is
* required in order to register memory mapped to the CPU as read-only.  Support
* for the use of this flag can be queried from the device attribute
* ::CU_DEVICE_ATTRIBUTE_READ_ONLY_HOST_REGISTER_SUPPORTED.  Using this flag with
* a current context associated with a device that does not have this attribute
* set will cause ::cuMemHostRegister to error with ::CUDA_ERROR_NOT_SUPPORTED.
*/
#define CU_MEMHOSTREGISTER_READ_ONLY    0x08

/**
 * 2D memory copy parameters
 */
typedef struct CUDA_MEMCPY2D_st {
    size_t srcXInBytes;         /**< Source X in bytes */
    size_t srcY;                /**< Source Y */

    CUmemorytype srcMemoryType; /**< Source memory type (host, device, array) */
    const void *srcHost;        /**< Source host pointer */
    CUdeviceptr srcDevice;      /**< Source device pointer */
    CUarray srcArray;           /**< Source array reference */
    size_t srcPitch;            /**< Source pitch (ignored when src is array) */

    size_t dstXInBytes;         /**< Destination X in bytes */
    size_t dstY;                /**< Destination Y */

    CUmemorytype dstMemoryType; /**< Destination memory type (host, device, array) */
    void *dstHost;              /**< Destination host pointer */
    CUdeviceptr dstDevice;      /**< Destination device pointer */
    CUarray dstArray;           /**< Destination array reference */
    size_t dstPitch;            /**< Destination pitch (ignored when dst is array) */

    size_t WidthInBytes;        /**< Width of 2D memory copy in bytes */
    size_t Height;              /**< Height of 2D memory copy */
} CUDA_MEMCPY2D_v2;
typedef CUDA_MEMCPY2D_v2 CUDA_MEMCPY2D;

/**
 * 3D memory copy parameters
 */
typedef struct CUDA_MEMCPY3D_st {
    size_t srcXInBytes;         /**< Source X in bytes */
    size_t srcY;                /**< Source Y */
    size_t srcZ;                /**< Source Z */
    size_t srcLOD;              /**< Source LOD */
    CUmemorytype srcMemoryType; /**< Source memory type (host, device, array) */
    const void *srcHost;        /**< Source host pointer */
    CUdeviceptr srcDevice;      /**< Source device pointer */
    CUarray srcArray;           /**< Source array reference */
    void *reserved0;            /**< Must be NULL */
    size_t srcPitch;            /**< Source pitch (ignored when src is array) */
    size_t srcHeight;           /**< Source height (ignored when src is array; may be 0 if Depth==1) */

    size_t dstXInBytes;         /**< Destination X in bytes */
    size_t dstY;                /**< Destination Y */
    size_t dstZ;                /**< Destination Z */
    size_t dstLOD;              /**< Destination LOD */
    CUmemorytype dstMemoryType; /**< Destination memory type (host, device, array) */
    void *dstHost;              /**< Destination host pointer */
    CUdeviceptr dstDevice;      /**< Destination device pointer */
    CUarray dstArray;           /**< Destination array reference */
    void *reserved1;            /**< Must be NULL */
    size_t dstPitch;            /**< Destination pitch (ignored when dst is array) */
    size_t dstHeight;           /**< Destination height (ignored when dst is array; may be 0 if Depth==1) */

    size_t WidthInBytes;        /**< Width of 3D memory copy in bytes */
    size_t Height;              /**< Height of 3D memory copy */
    size_t Depth;               /**< Depth of 3D memory copy */
} CUDA_MEMCPY3D_v2;
typedef CUDA_MEMCPY3D_v2 CUDA_MEMCPY3D;

/**
 * 3D memory cross-context copy parameters
 */
typedef struct CUDA_MEMCPY3D_PEER_st {
    size_t srcXInBytes;         /**< Source X in bytes */
    size_t srcY;                /**< Source Y */
    size_t srcZ;                /**< Source Z */
    size_t srcLOD;              /**< Source LOD */
    CUmemorytype srcMemoryType; /**< Source memory type (host, device, array) */
    const void *srcHost;        /**< Source host pointer */
    CUdeviceptr srcDevice;      /**< Source device pointer */
    CUarray srcArray;           /**< Source array reference */
    CUcontext srcContext;       /**< Source context (ignored with srcMemoryType is ::CU_MEMORYTYPE_ARRAY) */
    size_t srcPitch;            /**< Source pitch (ignored when src is array) */
    size_t srcHeight;           /**< Source height (ignored when src is array; may be 0 if Depth==1) */

    size_t dstXInBytes;         /**< Destination X in bytes */
    size_t dstY;                /**< Destination Y */
    size_t dstZ;                /**< Destination Z */
    size_t dstLOD;              /**< Destination LOD */
    CUmemorytype dstMemoryType; /**< Destination memory type (host, device, array) */
    void *dstHost;              /**< Destination host pointer */
    CUdeviceptr dstDevice;      /**< Destination device pointer */
    CUarray dstArray;           /**< Destination array reference */
    CUcontext dstContext;       /**< Destination context (ignored with dstMemoryType is ::CU_MEMORYTYPE_ARRAY) */
    size_t dstPitch;            /**< Destination pitch (ignored when dst is array) */
    size_t dstHeight;           /**< Destination height (ignored when dst is array; may be 0 if Depth==1) */

    size_t WidthInBytes;        /**< Width of 3D memory copy in bytes */
    size_t Height;              /**< Height of 3D memory copy */
    size_t Depth;               /**< Depth of 3D memory copy */
} CUDA_MEMCPY3D_PEER_v1;
typedef CUDA_MEMCPY3D_PEER_v1 CUDA_MEMCPY3D_PEER;

/**
 * Memcpy node parameters
 */
typedef struct CUDA_MEMCPY_NODE_PARAMS_st {
    int flags;                 /**< Must be zero */
    int reserved;              /**< Must be zero */
    CUcontext copyCtx;         /**< Context on which to run the node */
    CUDA_MEMCPY3D copyParams;  /**< Parameters for the memory copy */
} CUDA_MEMCPY_NODE_PARAMS;

/**
 * Array descriptor
 */
typedef struct CUDA_ARRAY_DESCRIPTOR_st
{
    size_t Width;             /**< Width of array */
    size_t Height;            /**< Height of array */

    CUarray_format Format;    /**< Array format */
    unsigned int NumChannels; /**< Channels per array element */
} CUDA_ARRAY_DESCRIPTOR_v2;
typedef CUDA_ARRAY_DESCRIPTOR_v2 CUDA_ARRAY_DESCRIPTOR;

/**
 * 3D array descriptor
 */
typedef struct CUDA_ARRAY3D_DESCRIPTOR_st
{
    size_t Width;             /**< Width of 3D array */
    size_t Height;            /**< Height of 3D array */
    size_t Depth;             /**< Depth of 3D array */

    CUarray_format Format;    /**< Array format */
    unsigned int NumChannels; /**< Channels per array element */
    unsigned int Flags;       /**< Flags */
} CUDA_ARRAY3D_DESCRIPTOR_v2;
typedef CUDA_ARRAY3D_DESCRIPTOR_v2 CUDA_ARRAY3D_DESCRIPTOR;

/**
 * Indicates that the layered sparse CUDA array or CUDA mipmapped array has a single mip tail region for all layers
 */
#define CU_ARRAY_SPARSE_PROPERTIES_SINGLE_MIPTAIL 0x1

/**
 * CUDA array sparse properties
 */
typedef struct CUDA_ARRAY_SPARSE_PROPERTIES_st {
    struct {
        unsigned int width;     /**< Width of sparse tile in elements */
        unsigned int height;    /**< Height of sparse tile in elements */
        unsigned int depth;     /**< Depth of sparse tile in elements */
    } tileExtent;

    /**
     * First mip level at which the mip tail begins.
     */
    unsigned int miptailFirstLevel;
    /**
     * Total size of the mip tail.
     */
    unsigned long long miptailSize;
    /**
     * Flags will either be zero or ::CU_ARRAY_SPARSE_PROPERTIES_SINGLE_MIPTAIL
     */
    unsigned int flags;
    unsigned int reserved[4];
} CUDA_ARRAY_SPARSE_PROPERTIES_v1;
typedef CUDA_ARRAY_SPARSE_PROPERTIES_v1 CUDA_ARRAY_SPARSE_PROPERTIES;

/**
 * CUDA array memory requirements
 */
typedef struct CUDA_ARRAY_MEMORY_REQUIREMENTS_st {
    size_t size;                /**< Total required memory size */
    size_t alignment;           /**< alignment requirement */
    unsigned int reserved[4];
} CUDA_ARRAY_MEMORY_REQUIREMENTS_v1;
typedef CUDA_ARRAY_MEMORY_REQUIREMENTS_v1 CUDA_ARRAY_MEMORY_REQUIREMENTS;

/**
 * CUDA Resource descriptor
 */
typedef struct CUDA_RESOURCE_DESC_st
{
    CUresourcetype resType;                   /**< Resource type */

    union {
        struct {
            CUarray hArray;                   /**< CUDA array */
        } array;
        struct {
            CUmipmappedArray hMipmappedArray; /**< CUDA mipmapped array */
        } mipmap;
        struct {
            CUdeviceptr devPtr;               /**< Device pointer */
            CUarray_format format;            /**< Array format */
            unsigned int numChannels;         /**< Channels per array element */
            size_t sizeInBytes;               /**< Size in bytes */
        } linear;
        struct {
            CUdeviceptr devPtr;               /**< Device pointer */
            CUarray_format format;            /**< Array format */
            unsigned int numChannels;         /**< Channels per array element */
            size_t width;                     /**< Width of the array in elements */
            size_t height;                    /**< Height of the array in elements */
            size_t pitchInBytes;              /**< Pitch between two rows in bytes */
        } pitch2D;
        struct {
            int reserved[32];
        } reserved;
    } res;

    unsigned int flags;                       /**< Flags (must be zero) */
} CUDA_RESOURCE_DESC_v1;
typedef CUDA_RESOURCE_DESC_v1 CUDA_RESOURCE_DESC;

/**
 * Texture descriptor
 */
typedef struct CUDA_TEXTURE_DESC_st {
    CUaddress_mode addressMode[3];  /**< Address modes */
    CUfilter_mode filterMode;       /**< Filter mode */
    unsigned int flags;             /**< Flags */
    unsigned int maxAnisotropy;     /**< Maximum anisotropy ratio */
    CUfilter_mode mipmapFilterMode; /**< Mipmap filter mode */
    float mipmapLevelBias;          /**< Mipmap level bias */
    float minMipmapLevelClamp;      /**< Mipmap minimum level clamp */
    float maxMipmapLevelClamp;      /**< Mipmap maximum level clamp */
    float borderColor[4];           /**< Border Color */
    int reserved[12];
} CUDA_TEXTURE_DESC_v1;
typedef CUDA_TEXTURE_DESC_v1 CUDA_TEXTURE_DESC;

/**
 * Resource view format
 */
typedef enum CUresourceViewFormat_enum
{
    CU_RES_VIEW_FORMAT_NONE          = 0x00, /**< No resource view format (use underlying resource format) */
    CU_RES_VIEW_FORMAT_UINT_1X8      = 0x01, /**< 1 channel unsigned 8-bit integers */
    CU_RES_VIEW_FORMAT_UINT_2X8      = 0x02, /**< 2 channel unsigned 8-bit integers */
    CU_RES_VIEW_FORMAT_UINT_4X8      = 0x03, /**< 4 channel unsigned 8-bit integers */
    CU_RES_VIEW_FORMAT_SINT_1X8      = 0x04, /**< 1 channel signed 8-bit integers */
    CU_RES_VIEW_FORMAT_SINT_2X8      = 0x05, /**< 2 channel signed 8-bit integers */
    CU_RES_VIEW_FORMAT_SINT_4X8      = 0x06, /**< 4 channel signed 8-bit integers */
    CU_RES_VIEW_FORMAT_UINT_1X16     = 0x07, /**< 1 channel unsigned 16-bit integers */
    CU_RES_VIEW_FORMAT_UINT_2X16     = 0x08, /**< 2 channel unsigned 16-bit integers */
    CU_RES_VIEW_FORMAT_UINT_4X16     = 0x09, /**< 4 channel unsigned 16-bit integers */
    CU_RES_VIEW_FORMAT_SINT_1X16     = 0x0a, /**< 1 channel signed 16-bit integers */
    CU_RES_VIEW_FORMAT_SINT_2X16     = 0x0b, /**< 2 channel signed 16-bit integers */
    CU_RES_VIEW_FORMAT_SINT_4X16     = 0x0c, /**< 4 channel signed 16-bit integers */
    CU_RES_VIEW_FORMAT_UINT_1X32     = 0x0d, /**< 1 channel unsigned 32-bit integers */
    CU_RES_VIEW_FORMAT_UINT_2X32     = 0x0e, /**< 2 channel unsigned 32-bit integers */
    CU_RES_VIEW_FORMAT_UINT_4X32     = 0x0f, /**< 4 channel unsigned 32-bit integers */
    CU_RES_VIEW_FORMAT_SINT_1X32     = 0x10, /**< 1 channel signed 32-bit integers */
    CU_RES_VIEW_FORMAT_SINT_2X32     = 0x11, /**< 2 channel signed 32-bit integers */
    CU_RES_VIEW_FORMAT_SINT_4X32     = 0x12, /**< 4 channel signed 32-bit integers */
    CU_RES_VIEW_FORMAT_FLOAT_1X16    = 0x13, /**< 1 channel 16-bit floating point */
    CU_RES_VIEW_FORMAT_FLOAT_2X16    = 0x14, /**< 2 channel 16-bit floating point */
    CU_RES_VIEW_FORMAT_FLOAT_4X16    = 0x15, /**< 4 channel 16-bit floating point */
    CU_RES_VIEW_FORMAT_FLOAT_1X32    = 0x16, /**< 1 channel 32-bit floating point */
    CU_RES_VIEW_FORMAT_FLOAT_2X32    = 0x17, /**< 2 channel 32-bit floating point */
    CU_RES_VIEW_FORMAT_FLOAT_4X32    = 0x18, /**< 4 channel 32-bit floating point */
    CU_RES_VIEW_FORMAT_UNSIGNED_BC1  = 0x19, /**< Block compressed 1 */
    CU_RES_VIEW_FORMAT_UNSIGNED_BC2  = 0x1a, /**< Block compressed 2 */
    CU_RES_VIEW_FORMAT_UNSIGNED_BC3  = 0x1b, /**< Block compressed 3 */
    CU_RES_VIEW_FORMAT_UNSIGNED_BC4  = 0x1c, /**< Block compressed 4 unsigned */
    CU_RES_VIEW_FORMAT_SIGNED_BC4    = 0x1d, /**< Block compressed 4 signed */
    CU_RES_VIEW_FORMAT_UNSIGNED_BC5  = 0x1e, /**< Block compressed 5 unsigned */
    CU_RES_VIEW_FORMAT_SIGNED_BC5    = 0x1f, /**< Block compressed 5 signed */
    CU_RES_VIEW_FORMAT_UNSIGNED_BC6H = 0x20, /**< Block compressed 6 unsigned half-float */
    CU_RES_VIEW_FORMAT_SIGNED_BC6H   = 0x21, /**< Block compressed 6 signed half-float */
    CU_RES_VIEW_FORMAT_UNSIGNED_BC7  = 0x22  /**< Block compressed 7 */
} CUresourceViewFormat;

/**
 * Resource view descriptor
 */
typedef struct CUDA_RESOURCE_VIEW_DESC_st
{
    CUresourceViewFormat format;   /**< Resource view format */
    size_t width;                  /**< Width of the resource view */
    size_t height;                 /**< Height of the resource view */
    size_t depth;                  /**< Depth of the resource view */
    unsigned int firstMipmapLevel; /**< First defined mipmap level */
    unsigned int lastMipmapLevel;  /**< Last defined mipmap level */
    unsigned int firstLayer;       /**< First layer index */
    unsigned int lastLayer;        /**< Last layer index */
    unsigned int reserved[16];
} CUDA_RESOURCE_VIEW_DESC_v1;
typedef CUDA_RESOURCE_VIEW_DESC_v1 CUDA_RESOURCE_VIEW_DESC;

/**
 * Size of tensor map descriptor
 */
#define CU_TENSOR_MAP_NUM_QWORDS 16

/**
 * Tensor map descriptor. Requires compiler support for aligning to 64 bytes.
 */
typedef struct CUtensorMap_st {
#if defined(__cplusplus) && (__cplusplus >= 201103L)
    alignas(64)
#elif __STDC_VERSION__ >= 201112L
    _Alignas(64)
#endif
    cuuint64_t opaque[CU_TENSOR_MAP_NUM_QWORDS];
} CUtensorMap;

/**
 * Tensor map data type
 */
typedef enum CUtensorMapDataType_enum {
    CU_TENSOR_MAP_DATA_TYPE_UINT8 = 0,
    CU_TENSOR_MAP_DATA_TYPE_UINT16,
    CU_TENSOR_MAP_DATA_TYPE_UINT32,
    CU_TENSOR_MAP_DATA_TYPE_INT32,
    CU_TENSOR_MAP_DATA_TYPE_UINT64,
    CU_TENSOR_MAP_DATA_TYPE_INT64,
    CU_TENSOR_MAP_DATA_TYPE_FLOAT16,
    CU_TENSOR_MAP_DATA_TYPE_FLOAT32,
    CU_TENSOR_MAP_DATA_TYPE_FLOAT64,
    CU_TENSOR_MAP_DATA_TYPE_BFLOAT16,
    CU_TENSOR_MAP_DATA_TYPE_FLOAT32_FTZ,
    CU_TENSOR_MAP_DATA_TYPE_TFLOAT32,
    CU_TENSOR_MAP_DATA_TYPE_TFLOAT32_FTZ,
    CU_TENSOR_MAP_DATA_TYPE_16U4_ALIGN8B,
    CU_TENSOR_MAP_DATA_TYPE_16U4_ALIGN16B,
    CU_TENSOR_MAP_DATA_TYPE_16U6_ALIGN16B
} CUtensorMapDataType;

/**
 * Tensor map interleave layout type
 */
typedef enum CUtensorMapInterleave_enum {
    CU_TENSOR_MAP_INTERLEAVE_NONE = 0,
    CU_TENSOR_MAP_INTERLEAVE_16B,
    CU_TENSOR_MAP_INTERLEAVE_32B
} CUtensorMapInterleave;

/**
 * Tensor map swizzling mode of shared memory banks
 */
typedef enum CUtensorMapSwizzle_enum {
    CU_TENSOR_MAP_SWIZZLE_NONE = 0,
    CU_TENSOR_MAP_SWIZZLE_32B,
    CU_TENSOR_MAP_SWIZZLE_64B,
    CU_TENSOR_MAP_SWIZZLE_128B,
    CU_TENSOR_MAP_SWIZZLE_128B_ATOM_32B,
    CU_TENSOR_MAP_SWIZZLE_128B_ATOM_32B_FLIP_8B,
    CU_TENSOR_MAP_SWIZZLE_128B_ATOM_64B
} CUtensorMapSwizzle;

/**
 * Tensor map L2 promotion type
 */
typedef enum CUtensorMapL2promotion_enum {
    CU_TENSOR_MAP_L2_PROMOTION_NONE = 0,
    CU_TENSOR_MAP_L2_PROMOTION_L2_64B,
    CU_TENSOR_MAP_L2_PROMOTION_L2_128B,
    CU_TENSOR_MAP_L2_PROMOTION_L2_256B
} CUtensorMapL2promotion;

/**
 * Tensor map out-of-bounds fill type
 */
typedef enum CUtensorMapFloatOOBfill_enum {
    CU_TENSOR_MAP_FLOAT_OOB_FILL_NONE = 0,
    CU_TENSOR_MAP_FLOAT_OOB_FILL_NAN_REQUEST_ZERO_FMA
} CUtensorMapFloatOOBfill;

/**
 * Tensor map Im2Col wide mode
 */
typedef enum CUtensorMapIm2ColWideMode_enum {
    CU_TENSOR_MAP_IM2COL_WIDE_MODE_W = 0,
    CU_TENSOR_MAP_IM2COL_WIDE_MODE_W128
} CUtensorMapIm2ColWideMode;

/**
 * GPU Direct v3 tokens
 */
typedef struct CUDA_POINTER_ATTRIBUTE_P2P_TOKENS_st {
    unsigned long long p2pToken;
    unsigned int vaSpaceToken;
} CUDA_POINTER_ATTRIBUTE_P2P_TOKENS_v1;
typedef CUDA_POINTER_ATTRIBUTE_P2P_TOKENS_v1 CUDA_POINTER_ATTRIBUTE_P2P_TOKENS;

/**
* Access flags that specify the level of access the current context's device has
* on the memory referenced.
*/
typedef enum CUDA_POINTER_ATTRIBUTE_ACCESS_FLAGS_enum {
    CU_POINTER_ATTRIBUTE_ACCESS_FLAG_NONE      = 0x0,   /**< No access, meaning the device cannot access this memory at all, thus must be staged through accessible memory in order to complete certain operations */
    CU_POINTER_ATTRIBUTE_ACCESS_FLAG_READ      = 0x1,   /**< Read-only access, meaning writes to this memory are considered invalid accesses and thus return error in that case. */
    CU_POINTER_ATTRIBUTE_ACCESS_FLAG_READWRITE = 0x3    /**< Read-write access, the device has full read-write access to the memory */
} CUDA_POINTER_ATTRIBUTE_ACCESS_FLAGS;

/**
 * Kernel launch parameters
 */
typedef struct CUDA_LAUNCH_PARAMS_st {
    CUfunction function;         /**< Kernel to launch */
    unsigned int gridDimX;       /**< Width of grid in blocks */
    unsigned int gridDimY;       /**< Height of grid in blocks */
    unsigned int gridDimZ;       /**< Depth of grid in blocks */
    unsigned int blockDimX;      /**< X dimension of each thread block */
    unsigned int blockDimY;      /**< Y dimension of each thread block */
    unsigned int blockDimZ;      /**< Z dimension of each thread block */
    unsigned int sharedMemBytes; /**< Dynamic shared-memory size per thread block in bytes */
    CUstream hStream;            /**< Stream identifier */
    void **kernelParams;         /**< Array of pointers to kernel parameters */
} CUDA_LAUNCH_PARAMS_v1;
typedef CUDA_LAUNCH_PARAMS_v1 CUDA_LAUNCH_PARAMS;

/**
 * External memory handle types
 */
typedef enum CUexternalMemoryHandleType_enum {
    /**
     * Handle is an opaque file descriptor
     */
    CU_EXTERNAL_MEMORY_HANDLE_TYPE_OPAQUE_FD          = 1,
    /**
     * Handle is an opaque shared NT handle
     */
    CU_EXTERNAL_MEMORY_HANDLE_TYPE_OPAQUE_WIN32       = 2,
    /**
     * Handle is an opaque, globally shared handle
     */
    CU_EXTERNAL_MEMORY_HANDLE_TYPE_OPAQUE_WIN32_KMT   = 3,
    /**
     * Handle is a D3D12 heap object
     */
    CU_EXTERNAL_MEMORY_HANDLE_TYPE_D3D12_HEAP         = 4,
    /**
     * Handle is a D3D12 committed resource
     */
    CU_EXTERNAL_MEMORY_HANDLE_TYPE_D3D12_RESOURCE     = 5,
    /**
     * Handle is a shared NT handle to a D3D11 resource
     */
    CU_EXTERNAL_MEMORY_HANDLE_TYPE_D3D11_RESOURCE     = 6,
    /**
     * Handle is a globally shared handle to a D3D11 resource
     */
    CU_EXTERNAL_MEMORY_HANDLE_TYPE_D3D11_RESOURCE_KMT = 7,
    /**
     * Handle is an NvSciBuf object
     */
    CU_EXTERNAL_MEMORY_HANDLE_TYPE_NVSCIBUF = 8,
} CUexternalMemoryHandleType;

/**
 * Indicates that the external memory object is a dedicated resource
 */
#define CUDA_EXTERNAL_MEMORY_DEDICATED   0x1

/** When the \p flags parameter of ::CUDA_EXTERNAL_SEMAPHORE_SIGNAL_PARAMS
 * contains this flag, it indicates that signaling an external semaphore object
 * should skip performing appropriate memory synchronization operations over all
 * the external memory objects that are imported as ::CU_EXTERNAL_MEMORY_HANDLE_TYPE_NVSCIBUF,
 * which otherwise are performed by default to ensure data coherency with other
 * importers of the same NvSciBuf memory objects.
 */
#define CUDA_EXTERNAL_SEMAPHORE_SIGNAL_SKIP_NVSCIBUF_MEMSYNC 0x01

/** When the \p flags parameter of ::CUDA_EXTERNAL_SEMAPHORE_WAIT_PARAMS
 * contains this flag, it indicates that waiting on an external semaphore object
 * should skip performing appropriate memory synchronization operations over all
 * the external memory objects that are imported as ::CU_EXTERNAL_MEMORY_HANDLE_TYPE_NVSCIBUF,
 * which otherwise are performed by default to ensure data coherency with other
 * importers of the same NvSciBuf memory objects.
 */
#define CUDA_EXTERNAL_SEMAPHORE_WAIT_SKIP_NVSCIBUF_MEMSYNC 0x02

/**
 * When \p flags of ::cuDeviceGetNvSciSyncAttributes is set to this,
 * it indicates that application needs signaler specific NvSciSyncAttr
 * to be filled by ::cuDeviceGetNvSciSyncAttributes.
 */
#define CUDA_NVSCISYNC_ATTR_SIGNAL 0x1

/**
 * When \p flags of ::cuDeviceGetNvSciSyncAttributes is set to this,
 * it indicates that application needs waiter specific NvSciSyncAttr
 * to be filled by ::cuDeviceGetNvSciSyncAttributes.
 */
#define CUDA_NVSCISYNC_ATTR_WAIT 0x2
/**
 * External memory handle descriptor
 */
typedef struct CUDA_EXTERNAL_MEMORY_HANDLE_DESC_st {
    /**
     * Type of the handle
     */
    CUexternalMemoryHandleType type;
    union {
        /**
         * File descriptor referencing the memory object. Valid
         * when type is
         * ::CU_EXTERNAL_MEMORY_HANDLE_TYPE_OPAQUE_FD
         */
        int fd;
        /**
         * Win32 handle referencing the semaphore object. Valid when
         * type is one of the following:
         * - ::CU_EXTERNAL_MEMORY_HANDLE_TYPE_OPAQUE_WIN32
         * - ::CU_EXTERNAL_MEMORY_HANDLE_TYPE_OPAQUE_WIN32_KMT
         * - ::CU_EXTERNAL_MEMORY_HANDLE_TYPE_D3D12_HEAP
         * - ::CU_EXTERNAL_MEMORY_HANDLE_TYPE_D3D12_RESOURCE
         * - ::CU_EXTERNAL_MEMORY_HANDLE_TYPE_D3D11_RESOURCE
         * - ::CU_EXTERNAL_MEMORY_HANDLE_TYPE_D3D11_RESOURCE_KMT
         * Exactly one of 'handle' and 'name' must be non-NULL. If
         * type is one of the following:
         * ::CU_EXTERNAL_MEMORY_HANDLE_TYPE_OPAQUE_WIN32_KMT
         * ::CU_EXTERNAL_MEMORY_HANDLE_TYPE_D3D11_RESOURCE_KMT
         * then 'name' must be NULL.
         */
        struct {
            /**
             * Valid NT handle. Must be NULL if 'name' is non-NULL
             */
            void *handle;
            /**
             * Name of a valid memory object.
             * Must be NULL if 'handle' is non-NULL.
             */
            const void *name;
        } win32;
        /**
         * A handle representing an NvSciBuf Object. Valid when type
         * is ::CU_EXTERNAL_MEMORY_HANDLE_TYPE_NVSCIBUF
         */
        const void *nvSciBufObject;
    } handle;
    /**
     * Size of the memory allocation
     */
    unsigned long long size;
    /**
     * Flags must either be zero or ::CUDA_EXTERNAL_MEMORY_DEDICATED
     */
    unsigned int flags;
    unsigned int reserved[16];
} CUDA_EXTERNAL_MEMORY_HANDLE_DESC_v1;
typedef CUDA_EXTERNAL_MEMORY_HANDLE_DESC_v1 CUDA_EXTERNAL_MEMORY_HANDLE_DESC;

/**
 * External memory buffer descriptor
 */
typedef struct CUDA_EXTERNAL_MEMORY_BUFFER_DESC_st {
    /**
     * Offset into the memory object where the buffer's base is
     */
    unsigned long long offset;
    /**
     * Size of the buffer
     */
    unsigned long long size;
    /**
     * Flags reserved for future use. Must be zero.
     */
    unsigned int flags;
    unsigned int reserved[16];
} CUDA_EXTERNAL_MEMORY_BUFFER_DESC_v1;
typedef CUDA_EXTERNAL_MEMORY_BUFFER_DESC_v1 CUDA_EXTERNAL_MEMORY_BUFFER_DESC;

/**
 * External memory mipmap descriptor
 */
typedef struct CUDA_EXTERNAL_MEMORY_MIPMAPPED_ARRAY_DESC_st {
    /**
     * Offset into the memory object where the base level of the
     * mipmap chain is.
     */
    unsigned long long offset;
    /**
     * Format, dimension and type of base level of the mipmap chain
     */
    CUDA_ARRAY3D_DESCRIPTOR arrayDesc;
    /**
     * Total number of levels in the mipmap chain
     */
    unsigned int numLevels;
    unsigned int reserved[16];
} CUDA_EXTERNAL_MEMORY_MIPMAPPED_ARRAY_DESC_v1;
typedef CUDA_EXTERNAL_MEMORY_MIPMAPPED_ARRAY_DESC_v1 CUDA_EXTERNAL_MEMORY_MIPMAPPED_ARRAY_DESC;

/**
 * External semaphore handle types
 */
typedef enum CUexternalSemaphoreHandleType_enum {
    /**
     * Handle is an opaque file descriptor
     */
    CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_OPAQUE_FD             = 1,
    /**
     * Handle is an opaque shared NT handle
     */
    CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_OPAQUE_WIN32          = 2,
    /**
     * Handle is an opaque, globally shared handle
     */
    CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_OPAQUE_WIN32_KMT      = 3,
    /**
     * Handle is a shared NT handle referencing a D3D12 fence object
     */
    CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_D3D12_FENCE           = 4,
    /**
     * Handle is a shared NT handle referencing a D3D11 fence object
     */
    CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_D3D11_FENCE           = 5,
    /**
     * Opaque handle to NvSciSync Object
	 */
	CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_NVSCISYNC             = 6,
    /**
     * Handle is a shared NT handle referencing a D3D11 keyed mutex object
     */
    CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_D3D11_KEYED_MUTEX     = 7,
    /**
     * Handle is a globally shared handle referencing a D3D11 keyed mutex object
     */
    CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_D3D11_KEYED_MUTEX_KMT = 8,
    /**
     * Handle is an opaque file descriptor referencing a timeline semaphore
     */
    CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_TIMELINE_SEMAPHORE_FD = 9,
    /**
     * Handle is an opaque shared NT handle referencing a timeline semaphore
     */
    CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_TIMELINE_SEMAPHORE_WIN32 = 10
} CUexternalSemaphoreHandleType;

/**
 * External semaphore handle descriptor
 */
typedef struct CUDA_EXTERNAL_SEMAPHORE_HANDLE_DESC_st {
    /**
     * Type of the handle
     */
    CUexternalSemaphoreHandleType type;
    union {
        /**
         * File descriptor referencing the semaphore object. Valid
         * when type is one of the following:
         * - ::CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_OPAQUE_FD
         * - ::CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_TIMELINE_SEMAPHORE_FD
         */
        int fd;
        /**
         * Win32 handle referencing the semaphore object. Valid when
         * type is one of the following:
         * - ::CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_OPAQUE_WIN32
         * - ::CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_OPAQUE_WIN32_KMT
         * - ::CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_D3D12_FENCE
         * - ::CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_D3D11_FENCE
         * - ::CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_D3D11_KEYED_MUTEX
         * - ::CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_TIMELINE_SEMAPHORE_WIN32
         * Exactly one of 'handle' and 'name' must be non-NULL. If
         * type is one of the following:
         * - ::CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_OPAQUE_WIN32_KMT
         * - ::CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_D3D11_KEYED_MUTEX_KMT
         * then 'name' must be NULL.
         */
        struct {
            /**
             * Valid NT handle. Must be NULL if 'name' is non-NULL
             */
            void *handle;
            /**
             * Name of a valid synchronization primitive.
             * Must be NULL if 'handle' is non-NULL.
             */
            const void *name;
        } win32;
        /**
         * Valid NvSciSyncObj. Must be non NULL
         */
        const void* nvSciSyncObj;
    } handle;
    /**
     * Flags reserved for the future. Must be zero.
     */
    unsigned int flags;
    unsigned int reserved[16];
} CUDA_EXTERNAL_SEMAPHORE_HANDLE_DESC_v1;
typedef CUDA_EXTERNAL_SEMAPHORE_HANDLE_DESC_v1 CUDA_EXTERNAL_SEMAPHORE_HANDLE_DESC;

/**
 * External semaphore signal parameters
 */
typedef struct CUDA_EXTERNAL_SEMAPHORE_SIGNAL_PARAMS_st {
    struct {
        /**
         * Parameters for fence objects
         */
        struct {
            /**
             * Value of fence to be signaled
             */
            unsigned long long value;
        } fence;
        union {
            /**
             * Pointer to NvSciSyncFence. Valid if ::CUexternalSemaphoreHandleType
             * is of type ::CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_NVSCISYNC.
             */
            void *fence;
            unsigned long long reserved;
        } nvSciSync;
        /**
         * Parameters for keyed mutex objects
         */
        struct {
            /**
             * Value of key to release the mutex with
             */
            unsigned long long key;
        } keyedMutex;
        unsigned int reserved[12];
    } params;
    /**
     * Only when ::CUDA_EXTERNAL_SEMAPHORE_SIGNAL_PARAMS is used to
     * signal a ::CUexternalSemaphore of type
     * ::CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_NVSCISYNC, the valid flag is
     * ::CUDA_EXTERNAL_SEMAPHORE_SIGNAL_SKIP_NVSCIBUF_MEMSYNC which indicates
     * that while signaling the ::CUexternalSemaphore, no memory synchronization
     * operations should be performed for any external memory object imported
     * as ::CU_EXTERNAL_MEMORY_HANDLE_TYPE_NVSCIBUF.
     * For all other types of ::CUexternalSemaphore, flags must be zero.
     */
    unsigned int flags;
    unsigned int reserved[16];
} CUDA_EXTERNAL_SEMAPHORE_SIGNAL_PARAMS_v1;
typedef CUDA_EXTERNAL_SEMAPHORE_SIGNAL_PARAMS_v1 CUDA_EXTERNAL_SEMAPHORE_SIGNAL_PARAMS;

/**
 * External semaphore wait parameters
 */
typedef struct CUDA_EXTERNAL_SEMAPHORE_WAIT_PARAMS_st {
    struct {
        /**
         * Parameters for fence objects
         */
        struct {
            /**
             * Value of fence to be waited on
             */
            unsigned long long value;
        } fence;
        /**
         * Pointer to NvSciSyncFence. Valid if CUexternalSemaphoreHandleType
         * is of type CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_NVSCISYNC.
         */
        union {
            void *fence;
            unsigned long long reserved;
        } nvSciSync;
        /**
         * Parameters for keyed mutex objects
         */
        struct {
            /**
             * Value of key to acquire the mutex with
             */
            unsigned long long key;
            /**
             * Timeout in milliseconds to wait to acquire the mutex
             */
            unsigned int timeoutMs;
        } keyedMutex;
        unsigned int reserved[10];
    } params;
    /**
     * Only when ::CUDA_EXTERNAL_SEMAPHORE_WAIT_PARAMS is used to wait on
     * a ::CUexternalSemaphore of type ::CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_NVSCISYNC,
     * the valid flag is ::CUDA_EXTERNAL_SEMAPHORE_WAIT_SKIP_NVSCIBUF_MEMSYNC
     * which indicates that while waiting for the ::CUexternalSemaphore, no memory
     * synchronization operations should be performed for any external memory
     * object imported as ::CU_EXTERNAL_MEMORY_HANDLE_TYPE_NVSCIBUF.
     * For all other types of ::CUexternalSemaphore, flags must be zero.
     */
    unsigned int flags;
    unsigned int reserved[16];
} CUDA_EXTERNAL_SEMAPHORE_WAIT_PARAMS_v1;
typedef CUDA_EXTERNAL_SEMAPHORE_WAIT_PARAMS_v1 CUDA_EXTERNAL_SEMAPHORE_WAIT_PARAMS;

/**
 * Semaphore signal node parameters
 */
typedef struct CUDA_EXT_SEM_SIGNAL_NODE_PARAMS_st {
    CUexternalSemaphore* extSemArray;                         /**< Array of external semaphore handles. */
    const CUDA_EXTERNAL_SEMAPHORE_SIGNAL_PARAMS* paramsArray; /**< Array of external semaphore signal parameters. */
    unsigned int numExtSems;                                  /**< Number of handles and parameters supplied in extSemArray and paramsArray. */
} CUDA_EXT_SEM_SIGNAL_NODE_PARAMS_v1;
typedef CUDA_EXT_SEM_SIGNAL_NODE_PARAMS_v1 CUDA_EXT_SEM_SIGNAL_NODE_PARAMS;

/**
 * Semaphore signal node parameters
 */
typedef struct CUDA_EXT_SEM_SIGNAL_NODE_PARAMS_v2_st {
    CUexternalSemaphore* extSemArray;                         /**< Array of external semaphore handles. */
    const CUDA_EXTERNAL_SEMAPHORE_SIGNAL_PARAMS* paramsArray; /**< Array of external semaphore signal parameters. */
    unsigned int numExtSems;                                  /**< Number of handles and parameters supplied in extSemArray and paramsArray. */
} CUDA_EXT_SEM_SIGNAL_NODE_PARAMS_v2;

/**
 * Semaphore wait node parameters
 */
typedef struct CUDA_EXT_SEM_WAIT_NODE_PARAMS_st {
    CUexternalSemaphore* extSemArray;                       /**< Array of external semaphore handles. */
    const CUDA_EXTERNAL_SEMAPHORE_WAIT_PARAMS* paramsArray; /**< Array of external semaphore wait parameters. */
    unsigned int numExtSems;                                /**< Number of handles and parameters supplied in extSemArray and paramsArray. */
} CUDA_EXT_SEM_WAIT_NODE_PARAMS_v1;
typedef CUDA_EXT_SEM_WAIT_NODE_PARAMS_v1 CUDA_EXT_SEM_WAIT_NODE_PARAMS;

/**
 * Semaphore wait node parameters
 */
typedef struct CUDA_EXT_SEM_WAIT_NODE_PARAMS_v2_st {
    CUexternalSemaphore* extSemArray;                       /**< Array of external semaphore handles. */
    const CUDA_EXTERNAL_SEMAPHORE_WAIT_PARAMS* paramsArray; /**< Array of external semaphore wait parameters. */
    unsigned int numExtSems;                                /**< Number of handles and parameters supplied in extSemArray and paramsArray. */
} CUDA_EXT_SEM_WAIT_NODE_PARAMS_v2;

typedef unsigned long long CUmemGenericAllocationHandle_v1;
typedef CUmemGenericAllocationHandle_v1 CUmemGenericAllocationHandle;

/**
 * Flags for specifying particular handle types
 */
typedef enum CUmemAllocationHandleType_enum {
    CU_MEM_HANDLE_TYPE_NONE                  = 0x0,  /**< Does not allow any export mechanism. > */
    CU_MEM_HANDLE_TYPE_POSIX_FILE_DESCRIPTOR = 0x1,  /**< Allows a file descriptor to be used for exporting. Permitted only on POSIX systems. (int) */
    CU_MEM_HANDLE_TYPE_WIN32                 = 0x2,  /**< Allows a Win32 NT handle to be used for exporting. (HANDLE) */
    CU_MEM_HANDLE_TYPE_WIN32_KMT             = 0x4,  /**< Allows a Win32 KMT handle to be used for exporting. (D3DKMT_HANDLE) */
    CU_MEM_HANDLE_TYPE_FABRIC                = 0x8,  /**< Allows a fabric handle to be used for exporting. (CUmemFabricHandle)*/
    CU_MEM_HANDLE_TYPE_MAX                   = 0x7FFFFFFF
} CUmemAllocationHandleType;

/**
 * Specifies the memory protection flags for mapping.
 */
typedef enum CUmemAccess_flags_enum {
    CU_MEM_ACCESS_FLAGS_PROT_NONE        = 0x0,  /**< Default, make the address range not accessible */
    CU_MEM_ACCESS_FLAGS_PROT_READ        = 0x1,  /**< Make the address range read accessible */
    CU_MEM_ACCESS_FLAGS_PROT_READWRITE   = 0x3,  /**< Make the address range read-write accessible */
    CU_MEM_ACCESS_FLAGS_PROT_MAX         = 0x7FFFFFFF
} CUmemAccess_flags;

/**
 * Specifies the type of location
 */
typedef enum CUmemLocationType_enum {
    CU_MEM_LOCATION_TYPE_INVALID    = 0x0,
    CU_MEM_LOCATION_TYPE_DEVICE     = 0x1,  /**< Location is a device location, thus id is a device ordinal */
    CU_MEM_LOCATION_TYPE_HOST       = 0x2,   /**< Location is host, id is ignored */
    CU_MEM_LOCATION_TYPE_HOST_NUMA  = 0x3,  /**< Location is a host NUMA node, thus id is a host NUMA node id */
    CU_MEM_LOCATION_TYPE_HOST_NUMA_CURRENT = 0x4,  /**< Location is a host NUMA node of the current thread, id is ignored */
    CU_MEM_LOCATION_TYPE_MAX        = 0x7FFFFFFF
} CUmemLocationType;

/**
* Defines the allocation types available
*/
typedef enum CUmemAllocationType_enum {
    CU_MEM_ALLOCATION_TYPE_INVALID = 0x0,

    /** This allocation type is 'pinned', i.e. cannot migrate from its current
      * location while the application is actively using it
      */
    CU_MEM_ALLOCATION_TYPE_PINNED  = 0x1,
    CU_MEM_ALLOCATION_TYPE_MAX     = 0x7FFFFFFF
} CUmemAllocationType;

/**
* Flag for requesting different optimal and required granularities for an allocation.
*/
typedef enum CUmemAllocationGranularity_flags_enum {
    CU_MEM_ALLOC_GRANULARITY_MINIMUM     = 0x0,     /**< Minimum required granularity for allocation */
    CU_MEM_ALLOC_GRANULARITY_RECOMMENDED = 0x1      /**< Recommended granularity for allocation for best performance */
} CUmemAllocationGranularity_flags;

/**
* Specifies the handle type for address range
*/
typedef enum CUmemRangeHandleType_enum
{
    CU_MEM_RANGE_HANDLE_TYPE_DMA_BUF_FD = 0x1,
    CU_MEM_RANGE_HANDLE_TYPE_MAX        = 0x7FFFFFFF
} CUmemRangeHandleType;

/**
* Flag for requesting handle type for address range.
*/
typedef enum CUmemRangeFlags_enum {
    CU_MEM_RANGE_FLAG_DMA_BUF_MAPPING_TYPE_PCIE     = 0x1   /**< Indicates that DMA_BUF handle should be mapped via PCIe BAR1 */
} CUmemRangeFlags;

/**
 * Sparse subresource types
 */
typedef enum CUarraySparseSubresourceType_enum {
    CU_ARRAY_SPARSE_SUBRESOURCE_TYPE_SPARSE_LEVEL = 0,
    CU_ARRAY_SPARSE_SUBRESOURCE_TYPE_MIPTAIL = 1
} CUarraySparseSubresourceType;

/**
 * Memory operation types
 */
typedef enum CUmemOperationType_enum {
    CU_MEM_OPERATION_TYPE_MAP = 1,
    CU_MEM_OPERATION_TYPE_UNMAP = 2
} CUmemOperationType;

/**
 * Memory handle types
 */
typedef enum CUmemHandleType_enum {
    CU_MEM_HANDLE_TYPE_GENERIC = 0
} CUmemHandleType;

/**
 * Specifies the CUDA array or CUDA mipmapped array memory mapping information
 */
typedef struct CUarrayMapInfo_st {    
    CUresourcetype resourceType;                    /**< Resource type */

    union {
        CUmipmappedArray mipmap;
        CUarray array;
    } resource;

    CUarraySparseSubresourceType subresourceType;   /**< Sparse subresource type */

    union {
        struct {
            unsigned int level;                     /**< For CUDA mipmapped arrays must a valid mipmap level. For CUDA arrays must be zero */            
            unsigned int layer;                     /**< For CUDA layered arrays must be a valid layer index. Otherwise, must be zero */
            unsigned int offsetX;                   /**< Starting X offset in elements */
            unsigned int offsetY;                   /**< Starting Y offset in elements */
            unsigned int offsetZ;                   /**< Starting Z offset in elements */            
            unsigned int extentWidth;               /**< Width in elements */
            unsigned int extentHeight;              /**< Height in elements */
            unsigned int extentDepth;               /**< Depth in elements */
        } sparseLevel;
        struct {
            unsigned int layer;                     /**< For CUDA layered arrays must be a valid layer index. Otherwise, must be zero */
            unsigned long long offset;              /**< Offset within mip tail */
            unsigned long long size;                /**< Extent in bytes */
        } miptail;
    } subresource;
    
    CUmemOperationType memOperationType;            /**< Memory operation type */
    CUmemHandleType memHandleType;                  /**< Memory handle type */

    union {
        CUmemGenericAllocationHandle memHandle;
    } memHandle;
    
    unsigned long long offset;                      /**< Offset within the memory */
    unsigned int deviceBitMask;                     /**< Device ordinal bit mask */
    unsigned int flags;                             /**< flags for future use, must be zero now. */
    unsigned int reserved[2];                       /**< Reserved for future use, must be zero now. */
} CUarrayMapInfo_v1;
typedef CUarrayMapInfo_v1 CUarrayMapInfo;

/**
 * Specifies a memory location.
 */
typedef struct CUmemLocation_st {
    CUmemLocationType type; /**< Specifies the location type, which modifies the meaning of id. */
    int id;                 /**< identifier for a given this location's ::CUmemLocationType. */
} CUmemLocation_v1;
typedef CUmemLocation_v1 CUmemLocation;

/**
 * Specifies compression attribute for an allocation.
 */
typedef enum CUmemAllocationCompType_enum {
    CU_MEM_ALLOCATION_COMP_NONE = 0x0, /**< Allocating non-compressible memory */
    CU_MEM_ALLOCATION_COMP_GENERIC = 0x1 /**< Allocating  compressible memory */
} CUmemAllocationCompType;

/**
 * This flag if set indicates that the memory will be used as a tile pool.
 */
#define CU_MEM_CREATE_USAGE_TILE_POOL    0x1
/**
 * This flag, if set, indicates that the memory will be used as a buffer for
 * hardware accelerated decompression.
 */
#define CU_MEM_CREATE_USAGE_HW_DECOMPRESS 0x2

/**
* Specifies the allocation properties for a allocation.
*/
typedef struct CUmemAllocationProp_st {
    /** Allocation type */
    CUmemAllocationType type;
    /** requested ::CUmemAllocationHandleType */
    CUmemAllocationHandleType requestedHandleTypes;
    /** Location of allocation */
    CUmemLocation location;
    /**
     * Windows-specific POBJECT_ATTRIBUTES required when
     * ::CU_MEM_HANDLE_TYPE_WIN32 is specified.  This object attributes structure
     * includes security attributes that define
     * the scope of which exported allocations may be transferred to other
     * processes.  In all other cases, this field is required to be zero.
     */
    void *win32HandleMetaData;
    struct {
         /**
         * Allocation hint for requesting compressible memory.
         * On devices that support Compute Data Compression, compressible
         * memory can be used to accelerate accesses to data with unstructured
         * sparsity and other compressible data patterns. Applications are 
         * expected to query allocation property of the handle obtained with 
         * ::cuMemCreate using ::cuMemGetAllocationPropertiesFromHandle to 
         * validate if the obtained allocation is compressible or not. Note that 
         * compressed memory may not be mappable on all devices.
         */
         unsigned char compressionType;
         unsigned char gpuDirectRDMACapable;
         /** Bitmask indicating intended usage for this allocation */
         unsigned short usage;
         unsigned char reserved[4];
    } allocFlags;
} CUmemAllocationProp_v1;
typedef CUmemAllocationProp_v1 CUmemAllocationProp;

/**
* Flags for querying different granularities for a multicast object
*/
typedef enum CUmulticastGranularity_flags_enum {
    CU_MULTICAST_GRANULARITY_MINIMUM     = 0x0,     /**< Minimum required granularity */
    CU_MULTICAST_GRANULARITY_RECOMMENDED = 0x1      /**< Recommended granularity for best performance */
} CUmulticastGranularity_flags;

/**
* Specifies the properties for a multicast object.
*/
typedef struct CUmulticastObjectProp_st {
    /**
     * The number of devices in the multicast team that will bind memory to this
     * object
     */
    unsigned int numDevices;
    /** 
     * The maximum amount of memory that can be bound to this multicast object
     * per device
     */
    size_t size;
    /**
     * Bitmask of exportable handle types (see ::CUmemAllocationHandleType) for
     * this object
     */
    unsigned long long handleTypes;
    /** 
     * Flags for future use, must be zero now
     */
    unsigned long long flags;
} CUmulticastObjectProp_v1;
typedef CUmulticastObjectProp_v1 CUmulticastObjectProp;

/**
 * Memory access descriptor
 */
typedef struct CUmemAccessDesc_st {
    CUmemLocation location;        /**< Location on which the request is to change it's accessibility */
    CUmemAccess_flags flags;       /**< ::CUmemProt accessibility flags to set on the request */
} CUmemAccessDesc_v1;
typedef CUmemAccessDesc_v1 CUmemAccessDesc;

/**
 * CUDA Graph Update error types
 */
typedef enum CUgraphExecUpdateResult_enum {
    CU_GRAPH_EXEC_UPDATE_SUCCESS                     = 0x0, /**< The update succeeded */
    CU_GRAPH_EXEC_UPDATE_ERROR                       = 0x1, /**< The update failed for an unexpected reason which is described in the return value of the function */
    CU_GRAPH_EXEC_UPDATE_ERROR_TOPOLOGY_CHANGED      = 0x2, /**< The update failed because the topology changed */
    CU_GRAPH_EXEC_UPDATE_ERROR_NODE_TYPE_CHANGED     = 0x3, /**< The update failed because a node type changed */
    CU_GRAPH_EXEC_UPDATE_ERROR_FUNCTION_CHANGED      = 0x4, /**< The update failed because the function of a kernel node changed (CUDA driver < 11.2) */
    CU_GRAPH_EXEC_UPDATE_ERROR_PARAMETERS_CHANGED    = 0x5, /**< The update failed because the parameters changed in a way that is not supported */
    CU_GRAPH_EXEC_UPDATE_ERROR_NOT_SUPPORTED         = 0x6, /**< The update failed because something about the node is not supported */
    CU_GRAPH_EXEC_UPDATE_ERROR_UNSUPPORTED_FUNCTION_CHANGE = 0x7, /**< The update failed because the function of a kernel node changed in an unsupported way */
    CU_GRAPH_EXEC_UPDATE_ERROR_ATTRIBUTES_CHANGED    = 0x8  /**< The update failed because the node attributes changed in a way that is not supported */
} CUgraphExecUpdateResult;

/**
 * Result information returned by cuGraphExecUpdate
 */
typedef struct CUgraphExecUpdateResultInfo_st {
    /**
     * Gives more specific detail when a cuda graph update fails.
     */
    CUgraphExecUpdateResult result;

    /**
     * The "to node" of the error edge when the topologies do not match.
     * The error node when the error is associated with a specific node.
     * NULL when the error is generic.
     */
    CUgraphNode errorNode;

    /**
     * The from node of error edge when the topologies do not match. Otherwise NULL.
     */
    CUgraphNode errorFromNode;
} CUgraphExecUpdateResultInfo_v1; 
typedef CUgraphExecUpdateResultInfo_v1 CUgraphExecUpdateResultInfo;

/**
 * CUDA memory pool attributes
 */
typedef enum CUmemPool_attribute_enum {
    /**
     * (value type = int)
     * Allow cuMemAllocAsync to use memory asynchronously freed
     * in another streams as long as a stream ordering dependency
     * of the allocating stream on the free action exists.
     * Cuda events and null stream interactions can create the required
     * stream ordered dependencies. (default enabled)
     */
    CU_MEMPOOL_ATTR_REUSE_FOLLOW_EVENT_DEPENDENCIES = 1,

    /**
     * (value type = int)
     * Allow reuse of already completed frees when there is no dependency
     * between the free and allocation. (default enabled)
     */
    CU_MEMPOOL_ATTR_REUSE_ALLOW_OPPORTUNISTIC,

    /**
     * (value type = int)
     * Allow cuMemAllocAsync to insert new stream dependencies
     * in order to establish the stream ordering required to reuse
     * a piece of memory released by cuFreeAsync (default enabled).
     */
    CU_MEMPOOL_ATTR_REUSE_ALLOW_INTERNAL_DEPENDENCIES,

    /**
     * (value type = cuuint64_t)
     * Amount of reserved memory in bytes to hold onto before trying
     * to release memory back to the OS. When more than the release
     * threshold bytes of memory are held by the memory pool, the
     * allocator will try to release memory back to the OS on the
     * next call to stream, event or context synchronize. (default 0)
     */
    CU_MEMPOOL_ATTR_RELEASE_THRESHOLD,

    /**
     * (value type = cuuint64_t)
     * Amount of backing memory currently allocated for the mempool.
     */
    CU_MEMPOOL_ATTR_RESERVED_MEM_CURRENT,

    /**
     * (value type = cuuint64_t)
     * High watermark of backing memory allocated for the mempool since the
     * last time it was reset. High watermark can only be reset to zero.
     */
    CU_MEMPOOL_ATTR_RESERVED_MEM_HIGH,

    /**
     * (value type = cuuint64_t)
     * Amount of memory from the pool that is currently in use by the application.
     */
    CU_MEMPOOL_ATTR_USED_MEM_CURRENT,

    /**
     * (value type = cuuint64_t)
     * High watermark of the amount of memory from the pool that was in use by the application since
     * the last time it was reset. High watermark can only be reset to zero.
     */
    CU_MEMPOOL_ATTR_USED_MEM_HIGH
} CUmemPool_attribute;

/**
 * This flag, if set, indicates that the memory will be used as a buffer for
 * hardware accelerated decompression.
 */
#define CU_MEM_POOL_CREATE_USAGE_HW_DECOMPRESS 0x2

/**
 * Specifies the properties of allocations made from the pool.
 */
typedef struct CUmemPoolProps_st {
    CUmemAllocationType allocType;         /**< Allocation type. Currently must be specified as CU_MEM_ALLOCATION_TYPE_PINNED */
    CUmemAllocationHandleType handleTypes; /**< Handle types that will be supported by allocations from the pool. */
    CUmemLocation location;                /**< Location where allocations should reside. */
    /**
     * Windows-specific LPSECURITYATTRIBUTES required when
     * ::CU_MEM_HANDLE_TYPE_WIN32 is specified.  This security attribute defines
     * the scope of which exported allocations may be transferred to other
     * processes.  In all other cases, this field is required to be zero.
     */
    void *win32SecurityAttributes;
    size_t maxSize;             /**< Maximum pool size. When set to 0, defaults to a system dependent value. */
    unsigned short usage;       /**< Bitmask indicating intended usage for the pool. */
    unsigned char reserved[54]; /**< reserved for future use, must be 0 */
} CUmemPoolProps_v1;
typedef CUmemPoolProps_v1 CUmemPoolProps;

/**
 * Opaque data for exporting a pool allocation
 */
typedef struct CUmemPoolPtrExportData_st {
    unsigned char reserved[64];
} CUmemPoolPtrExportData_v1;
typedef CUmemPoolPtrExportData_v1 CUmemPoolPtrExportData;

/**
 * Memory allocation node parameters
 */
typedef struct CUDA_MEM_ALLOC_NODE_PARAMS_v1_st {
    /**
    * in: location where the allocation should reside (specified in ::location).
    * ::handleTypes must be ::CU_MEM_HANDLE_TYPE_NONE. IPC is not supported.
    */
    CUmemPoolProps poolProps;
    const CUmemAccessDesc *accessDescs; /**< in: array of memory access descriptors. Used to describe peer GPU access */
    size_t accessDescCount; /**< in: number of memory access descriptors.  Must not exceed the number of GPUs. */
    size_t bytesize; /**< in: size in bytes of the requested allocation */
    CUdeviceptr dptr; /**< out: address of the allocation returned by CUDA */
} CUDA_MEM_ALLOC_NODE_PARAMS_v1;
typedef CUDA_MEM_ALLOC_NODE_PARAMS_v1 CUDA_MEM_ALLOC_NODE_PARAMS;

/**
 * Memory allocation node parameters
 */
typedef struct CUDA_MEM_ALLOC_NODE_PARAMS_v2_st {
    /**
    * in: location where the allocation should reside (specified in ::location).
    * ::handleTypes must be ::CU_MEM_HANDLE_TYPE_NONE. IPC is not supported.
    */
    CUmemPoolProps poolProps;
    const CUmemAccessDesc *accessDescs; /**< in: array of memory access descriptors. Used to describe peer GPU access */
    size_t accessDescCount; /**< in: number of memory access descriptors.  Must not exceed the number of GPUs. */
    size_t bytesize; /**< in: size in bytes of the requested allocation */
    CUdeviceptr dptr; /**< out: address of the allocation returned by CUDA */
} CUDA_MEM_ALLOC_NODE_PARAMS_v2;

/**
 * Memory free node parameters
 */
typedef struct CUDA_MEM_FREE_NODE_PARAMS_st {
    CUdeviceptr dptr; /**< in: the pointer to free */
} CUDA_MEM_FREE_NODE_PARAMS;

typedef enum CUgraphMem_attribute_enum {
    /**
     * (value type = cuuint64_t)
     * Amount of memory, in bytes, currently associated with graphs
     */
    CU_GRAPH_MEM_ATTR_USED_MEM_CURRENT,

    /**
     * (value type = cuuint64_t)
     * High watermark of memory, in bytes, associated with graphs since the
     * last time it was reset.  High watermark can only be reset to zero.
     */
    CU_GRAPH_MEM_ATTR_USED_MEM_HIGH,

    /**
     * (value type = cuuint64_t)
     * Amount of memory, in bytes, currently allocated for use by
     * the CUDA graphs asynchronous allocator.
     */
    CU_GRAPH_MEM_ATTR_RESERVED_MEM_CURRENT,

    /**
     * (value type = cuuint64_t)
     * High watermark of memory, in bytes, currently allocated for use by
     * the CUDA graphs asynchronous allocator.
     */
    CU_GRAPH_MEM_ATTR_RESERVED_MEM_HIGH
} CUgraphMem_attribute;

/**
 * Child graph node parameters
 */
typedef struct CUDA_CHILD_GRAPH_NODE_PARAMS_st {
    CUgraph graph; /**< The child graph to clone into the node for node creation, or
                        a handle to the graph owned by the node for node query */
} CUDA_CHILD_GRAPH_NODE_PARAMS;

/**
 * Event record node parameters
 */
typedef struct CUDA_EVENT_RECORD_NODE_PARAMS_st {
    CUevent event; /**< The event to record when the node executes */
} CUDA_EVENT_RECORD_NODE_PARAMS;

/**
 * Event wait node parameters
 */
typedef struct CUDA_EVENT_WAIT_NODE_PARAMS_st {
    CUevent event; /**< The event to wait on from the node */
} CUDA_EVENT_WAIT_NODE_PARAMS;

/**
 * Graph node parameters.  See ::cuGraphAddNode.
 */
typedef struct CUgraphNodeParams_st {
    CUgraphNodeType type; /**< Type of the node */
    int reserved0[3]; /**< Reserved. Must be zero. */

    union {
        long long                             reserved1[29]; /**< Padding. Unused bytes must be zero. */
        CUDA_KERNEL_NODE_PARAMS_v3            kernel;        /**< Kernel node parameters. */
        CUDA_MEMCPY_NODE_PARAMS               memcpy;        /**< Memcpy node parameters. */
        CUDA_MEMSET_NODE_PARAMS_v2            memset;        /**< Memset node parameters. */
        CUDA_HOST_NODE_PARAMS_v2              host;          /**< Host node parameters. */
        CUDA_CHILD_GRAPH_NODE_PARAMS          graph;         /**< Child graph node parameters. */
        CUDA_EVENT_WAIT_NODE_PARAMS           eventWait;     /**< Event wait node parameters. */
        CUDA_EVENT_RECORD_NODE_PARAMS         eventRecord;   /**< Event record node parameters. */
        CUDA_EXT_SEM_SIGNAL_NODE_PARAMS_v2    extSemSignal;  /**< External semaphore signal node parameters. */
        CUDA_EXT_SEM_WAIT_NODE_PARAMS_v2      extSemWait;    /**< External semaphore wait node parameters. */
        CUDA_MEM_ALLOC_NODE_PARAMS_v2         alloc;         /**< Memory allocation node parameters. */
        CUDA_MEM_FREE_NODE_PARAMS             free;          /**< Memory free node parameters. */
        CUDA_BATCH_MEM_OP_NODE_PARAMS_v2      memOp;         /**< MemOp node parameters. */
        CUDA_CONDITIONAL_NODE_PARAMS          conditional;   /**< Conditional node parameters. */
    };

    long long reserved2; /**< Reserved bytes. Must be zero. */
} CUgraphNodeParams;

/**
 * If set, each kernel launched as part of ::cuLaunchCooperativeKernelMultiDevice only
 * waits for prior work in the stream corresponding to that GPU to complete before the
 * kernel begins execution.
 */
#define CUDA_COOPERATIVE_LAUNCH_MULTI_DEVICE_NO_PRE_LAUNCH_SYNC   0x01

/**
 * If set, any subsequent work pushed in a stream that participated in a call to
 * ::cuLaunchCooperativeKernelMultiDevice will only wait for the kernel launched on
 * the GPU corresponding to that stream to complete before it begins execution.
 */
#define CUDA_COOPERATIVE_LAUNCH_MULTI_DEVICE_NO_POST_LAUNCH_SYNC  0x02

/**
 * If set, the CUDA array is a collection of layers, where each layer is either a 1D
 * or a 2D array and the Depth member of CUDA_ARRAY3D_DESCRIPTOR specifies the number
 * of layers, not the depth of a 3D array.
 */
#define CUDA_ARRAY3D_LAYERED        0x01

/**
 * Deprecated, use CUDA_ARRAY3D_LAYERED
 */
#define CUDA_ARRAY3D_2DARRAY        0x01

/**
 * This flag must be set in order to bind a surface reference
 * to the CUDA array
 */
#define CUDA_ARRAY3D_SURFACE_LDST   0x02

/**
 * If set, the CUDA array is a collection of six 2D arrays, representing faces of a cube. The
 * width of such a CUDA array must be equal to its height, and Depth must be six.
 * If ::CUDA_ARRAY3D_LAYERED flag is also set, then the CUDA array is a collection of cubemaps
 * and Depth must be a multiple of six.
 */
#define CUDA_ARRAY3D_CUBEMAP        0x04

/**
 * This flag must be set in order to perform texture gather operations
 * on a CUDA array.
 */
#define CUDA_ARRAY3D_TEXTURE_GATHER 0x08

/**
 * This flag if set indicates that the CUDA
 * array is a DEPTH_TEXTURE.
 */
#define CUDA_ARRAY3D_DEPTH_TEXTURE 0x10

/**
 * This flag indicates that the CUDA array may be bound as a color target
 * in an external graphics API
 */
#define CUDA_ARRAY3D_COLOR_ATTACHMENT 0x20

/**
 * This flag if set indicates that the CUDA array or CUDA mipmapped array
 * is a sparse CUDA array or CUDA mipmapped array respectively
 */
#define CUDA_ARRAY3D_SPARSE 0x40

/**
 * This flag if set indicates that the CUDA array or CUDA mipmapped array
 * will allow deferred memory mapping
 */
#define CUDA_ARRAY3D_DEFERRED_MAPPING 0x80

/**
 * This flag indicates that the CUDA array will be used for hardware accelerated
 * video encode/decode operations.
 */
#define CUDA_ARRAY3D_VIDEO_ENCODE_DECODE 0x100

/**
 * Override the texref format with a format inferred from the array.
 * Flag for ::cuTexRefSetArray()
 */
#define CU_TRSA_OVERRIDE_FORMAT 0x01

/**
 * Read the texture as integers rather than promoting the values to floats
 * in the range [0,1].
 * Flag for ::cuTexRefSetFlags() and ::cuTexObjectCreate()
 */
#define CU_TRSF_READ_AS_INTEGER         0x01

/**
 * Use normalized texture coordinates in the range [0,1) instead of [0,dim).
 * Flag for ::cuTexRefSetFlags() and ::cuTexObjectCreate()
 */
#define CU_TRSF_NORMALIZED_COORDINATES  0x02

/**
 * Perform sRGB->linear conversion during texture read.
 * Flag for ::cuTexRefSetFlags() and ::cuTexObjectCreate()
 */
#define CU_TRSF_SRGB  0x10

 /**
  * Disable any trilinear filtering optimizations.
  * Flag for ::cuTexRefSetFlags() and ::cuTexObjectCreate()
  */
#define CU_TRSF_DISABLE_TRILINEAR_OPTIMIZATION  0x20

/**
 * Enable seamless cube map filtering.
 * Flag for ::cuTexObjectCreate()
 */
#define CU_TRSF_SEAMLESS_CUBEMAP  0x40

/**
 * C++ compile time constant for CU_LAUNCH_PARAM_END
 */
#define CU_LAUNCH_PARAM_END_AS_INT     0x00

/**
 * End of array terminator for the \p extra parameter to
 * ::cuLaunchKernel
 */
#define CU_LAUNCH_PARAM_END            ((void*)CU_LAUNCH_PARAM_END_AS_INT)

/**
 * C++ compile time constant for CU_LAUNCH_PARAM_BUFFER_POINTER
 */
#define CU_LAUNCH_PARAM_BUFFER_POINTER_AS_INT 0x01

/**
 * Indicator that the next value in the \p extra parameter to
 * ::cuLaunchKernel will be a pointer to a buffer containing all kernel
 * parameters used for launching kernel \p f.  This buffer needs to
 * honor all alignment/padding requirements of the individual parameters.
 * If ::CU_LAUNCH_PARAM_BUFFER_SIZE is not also specified in the
 * \p extra array, then ::CU_LAUNCH_PARAM_BUFFER_POINTER will have no
 * effect.
 */
#define CU_LAUNCH_PARAM_BUFFER_POINTER        ((void*)CU_LAUNCH_PARAM_BUFFER_POINTER_AS_INT)

/**
 * C++ compile time constant for CU_LAUNCH_PARAM_BUFFER_SIZE
 */
#define CU_LAUNCH_PARAM_BUFFER_SIZE_AS_INT 0x02

/**
 * Indicator that the next value in the \p extra parameter to
 * ::cuLaunchKernel will be a pointer to a size_t which contains the
 * size of the buffer specified with ::CU_LAUNCH_PARAM_BUFFER_POINTER.
 * It is required that ::CU_LAUNCH_PARAM_BUFFER_POINTER also be specified
 * in the \p extra array if the value associated with
 * ::CU_LAUNCH_PARAM_BUFFER_SIZE is not zero.
 */
#define CU_LAUNCH_PARAM_BUFFER_SIZE        ((void*)CU_LAUNCH_PARAM_BUFFER_SIZE_AS_INT)

/**
 * For texture references loaded into the module, use default texunit from
 * texture reference.
 */
#define CU_PARAM_TR_DEFAULT -1

/**
 * Device that represents the CPU
 */
#define CU_DEVICE_CPU               ((CUdevice)-1)

/**
 * Device that represents an invalid device
 */
#define CU_DEVICE_INVALID           ((CUdevice)-2)

/**
 * Bitmasks for ::CU_DEVICE_ATTRIBUTE_GPU_DIRECT_RDMA_FLUSH_WRITES_OPTIONS
 */
typedef enum CUflushGPUDirectRDMAWritesOptions_enum {
    CU_FLUSH_GPU_DIRECT_RDMA_WRITES_OPTION_HOST   = 1<<0, /**< ::cuFlushGPUDirectRDMAWrites() and its CUDA Runtime API counterpart are supported on the device. */
    CU_FLUSH_GPU_DIRECT_RDMA_WRITES_OPTION_MEMOPS = 1<<1  /**< The ::CU_STREAM_WAIT_VALUE_FLUSH flag and the ::CU_STREAM_MEM_OP_FLUSH_REMOTE_WRITES MemOp are supported on the device. */
} CUflushGPUDirectRDMAWritesOptions;

/**
 * Platform native ordering for GPUDirect RDMA writes
 */
typedef enum CUGPUDirectRDMAWritesOrdering_enum {
    CU_GPU_DIRECT_RDMA_WRITES_ORDERING_NONE        = 0,   /**< The device does not natively support ordering of remote writes. ::cuFlushGPUDirectRDMAWrites() can be leveraged if supported. */
    CU_GPU_DIRECT_RDMA_WRITES_ORDERING_OWNER       = 100, /**< Natively, the device can consistently consume remote writes, although other CUDA devices may not. */
    CU_GPU_DIRECT_RDMA_WRITES_ORDERING_ALL_DEVICES = 200  /**< Any CUDA device in the system can consistently consume remote writes to this device. */
} CUGPUDirectRDMAWritesOrdering;

/**
 * The scopes for ::cuFlushGPUDirectRDMAWrites
 */
typedef enum CUflushGPUDirectRDMAWritesScope_enum {
    CU_FLUSH_GPU_DIRECT_RDMA_WRITES_TO_OWNER       = 100, /**< Blocks until remote writes are visible to the CUDA device context owning the data. */
    CU_FLUSH_GPU_DIRECT_RDMA_WRITES_TO_ALL_DEVICES = 200  /**< Blocks until remote writes are visible to all CUDA device contexts. */
} CUflushGPUDirectRDMAWritesScope;
 
/**
 * The targets for ::cuFlushGPUDirectRDMAWrites
 */
typedef enum CUflushGPUDirectRDMAWritesTarget_enum {
    CU_FLUSH_GPU_DIRECT_RDMA_WRITES_TARGET_CURRENT_CTX = 0 /**< Sets the target for ::cuFlushGPUDirectRDMAWrites() to the currently active CUDA device context. */
} CUflushGPUDirectRDMAWritesTarget;

/**
 * The additional write options for ::cuGraphDebugDotPrint
 */
typedef enum CUgraphDebugDot_flags_enum {
    CU_GRAPH_DEBUG_DOT_FLAGS_VERBOSE                        = 1<<0,  /**< Output all debug data as if every debug flag is enabled */
    CU_GRAPH_DEBUG_DOT_FLAGS_RUNTIME_TYPES                  = 1<<1,  /**< Use CUDA Runtime structures for output */
    CU_GRAPH_DEBUG_DOT_FLAGS_KERNEL_NODE_PARAMS             = 1<<2,  /**< Adds CUDA_KERNEL_NODE_PARAMS values to output */
    CU_GRAPH_DEBUG_DOT_FLAGS_MEMCPY_NODE_PARAMS             = 1<<3,  /**< Adds CUDA_MEMCPY3D values to output */
    CU_GRAPH_DEBUG_DOT_FLAGS_MEMSET_NODE_PARAMS             = 1<<4,  /**< Adds CUDA_MEMSET_NODE_PARAMS values to output */
    CU_GRAPH_DEBUG_DOT_FLAGS_HOST_NODE_PARAMS               = 1<<5,  /**< Adds CUDA_HOST_NODE_PARAMS values to output */
    CU_GRAPH_DEBUG_DOT_FLAGS_EVENT_NODE_PARAMS              = 1<<6,  /**< Adds CUevent handle from record and wait nodes to output */
    CU_GRAPH_DEBUG_DOT_FLAGS_EXT_SEMAS_SIGNAL_NODE_PARAMS   = 1<<7,  /**< Adds CUDA_EXT_SEM_SIGNAL_NODE_PARAMS values to output */
    CU_GRAPH_DEBUG_DOT_FLAGS_EXT_SEMAS_WAIT_NODE_PARAMS     = 1<<8,  /**< Adds CUDA_EXT_SEM_WAIT_NODE_PARAMS values to output */
    CU_GRAPH_DEBUG_DOT_FLAGS_KERNEL_NODE_ATTRIBUTES         = 1<<9,  /**< Adds CUkernelNodeAttrValue values to output */
    CU_GRAPH_DEBUG_DOT_FLAGS_HANDLES                        = 1<<10, /**< Adds node handles and every kernel function handle to output */
    CU_GRAPH_DEBUG_DOT_FLAGS_MEM_ALLOC_NODE_PARAMS          = 1<<11, /**< Adds memory alloc node parameters to output */
    CU_GRAPH_DEBUG_DOT_FLAGS_MEM_FREE_NODE_PARAMS           = 1<<12, /**< Adds memory free node parameters to output */
    CU_GRAPH_DEBUG_DOT_FLAGS_BATCH_MEM_OP_NODE_PARAMS       = 1<<13, /**< Adds batch mem op node parameters to output */
    CU_GRAPH_DEBUG_DOT_FLAGS_EXTRA_TOPO_INFO                = 1<<14, /**< Adds edge numbering information */
    CU_GRAPH_DEBUG_DOT_FLAGS_CONDITIONAL_NODE_PARAMS        = 1<<15  /**< Adds conditional node parameters to output */
} CUgraphDebugDot_flags;

/**
 * Flags for user objects for graphs
 */
typedef enum CUuserObject_flags_enum {
    CU_USER_OBJECT_NO_DESTRUCTOR_SYNC = 1  /**< Indicates the destructor execution is not synchronized by any CUDA handle. */
} CUuserObject_flags;

/**
 * Flags for retaining user object references for graphs
 */
typedef enum CUuserObjectRetain_flags_enum {
    CU_GRAPH_USER_OBJECT_MOVE = 1  /**< Transfer references from the caller rather than creating new references. */
} CUuserObjectRetain_flags;

/**
 * Flags for instantiating a graph
 */
typedef enum CUgraphInstantiate_flags_enum {
    CUDA_GRAPH_INSTANTIATE_FLAG_AUTO_FREE_ON_LAUNCH  = 1 /**< Automatically free memory allocated in a graph before relaunching. */
  , CUDA_GRAPH_INSTANTIATE_FLAG_UPLOAD               = 2 /**< Automatically upload the graph after instantiation. Only supported by
                                                              ::cuGraphInstantiateWithParams.  The upload will be performed using the
                                                              stream provided in \p instantiateParams. */
  , CUDA_GRAPH_INSTANTIATE_FLAG_DEVICE_LAUNCH        = 4 /**< Instantiate the graph to be launchable from the device. This flag can only
                                                              be used on platforms which support unified addressing. This flag cannot be
                                                              used in conjunction with CUDA_GRAPH_INSTANTIATE_FLAG_AUTO_FREE_ON_LAUNCH. */
  , CUDA_GRAPH_INSTANTIATE_FLAG_USE_NODE_PRIORITY    = 8 /**< Run the graph using the per-node priority attributes rather than the
                                                              priority of the stream it is launched into. */
} CUgraphInstantiate_flags;

/**
 * CUDA device NUMA configuration
 */
typedef enum CUdeviceNumaConfig_enum {
    CU_DEVICE_NUMA_CONFIG_NONE = 0, /**< The GPU is not a NUMA node */
    CU_DEVICE_NUMA_CONFIG_NUMA_NODE, /**< The GPU is a NUMA node, CU_DEVICE_ATTRIBUTE_NUMA_ID contains its NUMA ID */
} CUdeviceNumaConfig;

/**
 * CUDA Process States
 */
typedef enum CUprocessState_enum {
    CU_PROCESS_STATE_RUNNING = 0,  /**< Default process state */
    CU_PROCESS_STATE_LOCKED,       /**< CUDA API locks are taken so further CUDA API calls will block */
    CU_PROCESS_STATE_CHECKPOINTED, /**< Application memory contents have been checkpointed and underlying allocations and device handles have been released */
    CU_PROCESS_STATE_FAILED,       /**< Application entered an uncorrectable error during the checkpoint/restore process */
} CUprocessState;

/**
 * CUDA checkpoint optional lock arguments
 */
typedef struct CUcheckpointLockArgs_st {
    unsigned int timeoutMs; /**< Timeout in milliseconds to attempt to lock the process, 0 indicates no timeout */
    unsigned int reserved0; /**< Reserved for future use, must be zero */
    cuuint64_t reserved1[7]; /**< Reserved for future use, must be zeroed */
} CUcheckpointLockArgs;

/**
 * CUDA checkpoint optional checkpoint arguments
 */
typedef struct CUcheckpointCheckpointArgs_st {
    cuuint64_t reserved[8]; /**< Reserved for future use, must be zeroed */
} CUcheckpointCheckpointArgs;

/**
 * CUDA checkpoint optional restore arguments
 */
typedef struct CUcheckpointRestoreArgs_st {
    cuuint64_t reserved[8]; /**< Reserved for future use, must be zeroed */
} CUcheckpointRestoreArgs;

/**
 * CUDA checkpoint optional unlock arguments
 */
typedef struct CUcheckpointUnlockArgs_st {
    cuuint64_t reserved[8]; /**< Reserved for future use, must be zeroed */
} CUcheckpointUnlockArgs;

/**
 * Flags to specify for copies within a batch. For more details see ::cuMemcpyBatchAsync.
 */
typedef enum CUmemcpyFlags_enum {
    CU_MEMCPY_FLAG_DEFAULT = 0x0,

    /**
     * Hint to the driver to try and overlap the copy with compute work on the SMs.
     */
    CU_MEMCPY_FLAG_PREFER_OVERLAP_WITH_COMPUTE = 0x1
} CUmemcpyFlags;

/**
 * These flags allow applications to convey the source access ordering CUDA must maintain.
 * The destination will always be accessed in stream order.
 */
typedef enum CUmemcpySrcAccessOrder_enum {
    /**
     * Default invalid.
     */
    CU_MEMCPY_SRC_ACCESS_ORDER_INVALID = 0x0,

    /**
     * Indicates that access to the source pointer must be in stream order.
     */
    CU_MEMCPY_SRC_ACCESS_ORDER_STREAM = 0x1,

    /**
     * Indicates that access to the source pointer can be out of stream order and
     * all accesses must be complete before the API call returns. This flag is suited for
     * ephemeral sources (ex., stack variables) when it's known that no prior operations
     * in the stream can be accessing the memory and also that the lifetime of the memory
     * is limited to the scope that the source variable was declared in. Specifying
     * this flag allows the driver to optimize the copy and removes the need for the user
     * to synchronize the stream after the API call.
     */
    CU_MEMCPY_SRC_ACCESS_ORDER_DURING_API_CALL = 0x2,

    /**
     * Indicates that access to the source pointer can be out of stream order and the accesses
     * can happen even after the API call returns. This flag is suited for host pointers
     * allocated outside CUDA (ex., via malloc) when it's known that no prior operations
     * in the stream can be accessing the memory. Specifying this flag allows the driver
     * to optimize the copy on certain platforms.
     */
    CU_MEMCPY_SRC_ACCESS_ORDER_ANY = 0x3,

    CU_MEMCPY_SRC_ACCESS_ORDER_MAX = 0x7FFFFFFF
}  CUmemcpySrcAccessOrder;

/**
 * Attributes specific to copies within a batch. For more details on usage see ::cuMemcpyBatchAsync.
 */
typedef struct CUmemcpyAttributes_st {
    CUmemcpySrcAccessOrder srcAccessOrder;  /**< Source access ordering to be observed for copies with this attribute. */
    CUmemLocation srcLocHint;               /**< Hint location for the source operand. Ignored when the pointers are not managed memory or memory allocated outside CUDA. */
    CUmemLocation dstLocHint;               /**< Hint location for the destination operand. Ignored when the pointers are not managed memory or memory allocated outside CUDA. */
    unsigned int flags;                     /**< Additional flags for copies with this attribute. See ::CUmemcpyFlags */
} CUmemcpyAttributes_v1;
typedef CUmemcpyAttributes_v1 CUmemcpyAttributes;

/**
 * These flags allow applications to convey the operand type for individual copies specified in ::cuMemcpy3DBatchAsync.
 */
typedef enum CUmemcpy3DOperandType_enum {
    CU_MEMCPY_OPERAND_TYPE_POINTER = 0x1,     /**< Memcpy operand is a valid pointer. */
    CU_MEMCPY_OPERAND_TYPE_ARRAY = 0x2,       /**< Memcpy operand is a CUarray. */
    CU_MEMCPY_OPERAND_TYPE_MAX = 0x7FFFFFFF
} CUmemcpy3DOperandType;

/**
 * Struct representing offset into a CUarray in elements
 */
typedef struct CUoffset3D_st {
    size_t x;
    size_t y;
    size_t z;
} CUoffset3D_v1;
typedef CUoffset3D_v1 CUoffset3D;

/**
 * Struct representing width/height/depth of a CUarray in elements
 */
typedef struct CUextent3D_st {
    size_t width;
    size_t height;
    size_t depth;
} CUextent3D_v1;
typedef CUextent3D_v1 CUextent3D;

/**
 * Struct representing an operand for copy with ::cuMemcpy3DBatchAsync
 */
typedef struct CUmemcpy3DOperand_st {
    CUmemcpy3DOperandType type;
    union {
        /**
         * Struct representing an operand when ::CUmemcpy3DOperand::type is ::CU_MEMCPY_OPERAND_TYPE_POINTER
         */
        struct {
            CUdeviceptr ptr;
            size_t rowLength;        /**< Length of each row in elements. */
            size_t layerHeight;      /**< Height of each layer in elements. */ 
            CUmemLocation locHint;   /**< Hint location for the operand. Ignored when the pointers are not managed memory or memory allocated outside CUDA. */
        } ptr;

        /**
         * Struct representing an operand when ::CUmemcpy3DOperand::type is ::CU_MEMCPY_OPERAND_TYPE_ARRAY
         */
        struct {
            CUarray array;
            CUoffset3D offset;
        } array;
    } op;
} CUmemcpy3DOperand_v1;
typedef CUmemcpy3DOperand_v1 CUmemcpy3DOperand;

typedef struct CUDA_MEMCPY3D_BATCH_OP_st {
    CUmemcpy3DOperand src;                    /**< Source memcpy operand. */
    CUmemcpy3DOperand dst;                    /**< Destination memcpy operand. */
    CUextent3D extent;                        /**< Extents of the memcpy between src and dst. The width, height and depth components must not be 0.*/
    CUmemcpySrcAccessOrder srcAccessOrder;    /**< Source access ordering to be observed for copy from src to dst. */
    unsigned int flags;                       /**< Additional flags for copies with this attribute. See ::CUmemcpyFlags */
} CUDA_MEMCPY3D_BATCH_OP_v1;
typedef CUDA_MEMCPY3D_BATCH_OP_v1 CUDA_MEMCPY3D_BATCH_OP;

/** @} */ /* END CUDA_TYPES */

#if defined(__GNUC__)
  #if defined(__CUDA_API_PUSH_VISIBILITY_DEFAULT)
    #pragma GCC visibility push(default)
  #endif
#endif

#ifdef _WIN32
#define CUDAAPI __stdcall
#else
#define CUDAAPI
#endif

/**
 * \defgroup CUDA_ERROR Error Handling
 *
 * ___MANBRIEF___ error handling functions of the low-level CUDA driver API
 * (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the error handling functions of the low-level CUDA
 * driver application programming interface.
 *
 * @{
 */

/**
 * \brief Gets the string description of an error code
 *
 * Sets \p *pStr to the address of a NULL-terminated string description
 * of the error code \p error.
 * If the error code is not recognized, ::CUDA_ERROR_INVALID_VALUE
 * will be returned and \p *pStr will be set to the NULL address.
 *
 * \param error - Error code to convert to string
 * \param pStr - Address of the string pointer.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa
 * ::CUresult,
 * ::cudaGetErrorString
 */
CUresult CUDAAPI cuGetErrorString(CUresult error, const char **pStr);

/**
 * \brief Gets the string representation of an error code enum name
 *
 * Sets \p *pStr to the address of a NULL-terminated string representation
 * of the name of the enum error code \p error.
 * If the error code is not recognized, ::CUDA_ERROR_INVALID_VALUE
 * will be returned and \p *pStr will be set to the NULL address.
 *
 * \param error - Error code to convert to string
 * \param pStr - Address of the string pointer.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa
 * ::CUresult,
 * ::cudaGetErrorName
 */
CUresult CUDAAPI cuGetErrorName(CUresult error, const char **pStr);

/** @} */ /* END CUDA_ERROR */

/**
 * \defgroup CUDA_INITIALIZE Initialization
 *
 * ___MANBRIEF___ initialization functions of the low-level CUDA driver API
 * (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the initialization functions of the low-level CUDA
 * driver application programming interface.
 *
 * @{
 */

/**
 * \brief Initialize the CUDA driver API
 * Initializes the driver API and must be called before any other function from
 * the driver API in the current process. Currently, the \p Flags parameter must be 0. If ::cuInit()
 * has not been called, any function from the driver API will return
 * ::CUDA_ERROR_NOT_INITIALIZED.
 *
 * \param Flags - Initialization flag for CUDA.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_DEVICE,
 * ::CUDA_ERROR_SYSTEM_DRIVER_MISMATCH,
 * ::CUDA_ERROR_COMPAT_NOT_SUPPORTED_ON_DEVICE
 * \notefnerr
 */
CUresult CUDAAPI cuInit(unsigned int Flags);

/** @} */ /* END CUDA_INITIALIZE */

/**
 * \defgroup CUDA_VERSION Version Management
 *
 * ___MANBRIEF___ version management functions of the low-level CUDA driver
 * API (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the version management functions of the low-level
 * CUDA driver application programming interface.
 *
 * @{
 */

/**
 * \brief Returns the latest CUDA version supported by driver
 *
 * Returns in \p *driverVersion the version of CUDA supported by
 * the driver.  The version is returned as
 * (1000 &times; major + 10 &times; minor). For example, CUDA 9.2
 * would be represented by 9020.
 *
 * This function automatically returns ::CUDA_ERROR_INVALID_VALUE if
 * \p driverVersion is NULL.
 *
 * \param driverVersion - Returns the CUDA driver version
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 *
 * \sa
 * ::cudaDriverGetVersion,
 * ::cudaRuntimeGetVersion
 */
CUresult CUDAAPI cuDriverGetVersion(int *driverVersion);

/** @} */ /* END CUDA_VERSION */

/**
 * \defgroup CUDA_DEVICE Device Management
 *
 * ___MANBRIEF___ device management functions of the low-level CUDA driver API
 * (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the device management functions of the low-level
 * CUDA driver application programming interface.
 *
 * @{
 */

/**
 * \brief Returns a handle to a compute device
 *
 * Returns in \p *device a device handle given an ordinal in the range <b>[0,
 * ::cuDeviceGetCount()-1]</b>.
 *
 * \param device  - Returned device handle
 * \param ordinal - Device number to get handle for
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_DEVICE
 * \notefnerr
 *
 * \sa
 * ::cuDeviceGetAttribute,
 * ::cuDeviceGetCount,
 * ::cuDeviceGetName,
 * ::cuDeviceGetUuid,
 * ::cuDeviceGetLuid,
 * ::cuDeviceTotalMem,
 * ::cuDeviceGetExecAffinitySupport
 */
CUresult CUDAAPI cuDeviceGet(CUdevice *device, int ordinal);

/**
 * \brief Returns the number of compute-capable devices
 *
 * Returns in \p *count the number of devices with compute capability greater
 * than or equal to 2.0 that are available for execution. If there is no such
 * device, ::cuDeviceGetCount() returns 0.
 *
 * \param count - Returned number of compute-capable devices
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 *
 * \sa
 * ::cuDeviceGetAttribute,
 * ::cuDeviceGetName,
 * ::cuDeviceGetUuid,
 * ::cuDeviceGetLuid,
 * ::cuDeviceGet,
 * ::cuDeviceTotalMem,
 * ::cuDeviceGetExecAffinitySupport,
 * ::cudaGetDeviceCount
 */
CUresult CUDAAPI cuDeviceGetCount(int *count);

/**
 * \brief Returns an identifier string for the device
 *
 * Returns an ASCII string identifying the device \p dev in the NULL-terminated
 * string pointed to by \p name. \p len specifies the maximum length of the
 * string that may be returned.
 *
 * \param name - Returned identifier string for the device
 * \param len  - Maximum length of string to store in \p name
 * \param dev  - Device to get identifier string for
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_DEVICE
 * \notefnerr
 *
 * \sa
 * ::cuDeviceGetAttribute,
 * ::cuDeviceGetUuid,
 * ::cuDeviceGetLuid,
 * ::cuDeviceGetCount,
 * ::cuDeviceGet,
 * ::cuDeviceTotalMem,
 * ::cuDeviceGetExecAffinitySupport,
 * ::cudaGetDeviceProperties
 */
CUresult CUDAAPI cuDeviceGetName(char *name, int len, CUdevice dev);

/**
 * \brief Return an UUID for the device
 *
 * Note there is a later version of this API, ::cuDeviceGetUuid_v2. It will
 * supplant this version in 12.0, which is retained for minor version compatibility.
 *
 * Returns 16-octets identifying the device \p dev in the structure
 * pointed by the \p uuid.
 *
 * \param uuid - Returned UUID
 * \param dev  - Device to get identifier string for
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_DEVICE
 * \notefnerr
 *
 * \sa
 * ::cuDeviceGetUuid_v2
 * ::cuDeviceGetAttribute,
 * ::cuDeviceGetCount,
 * ::cuDeviceGetName,
 * ::cuDeviceGetLuid,
 * ::cuDeviceGet,
 * ::cuDeviceTotalMem,
 * ::cuDeviceGetExecAffinitySupport,
 * ::cudaGetDeviceProperties
 */
CUresult CUDAAPI cuDeviceGetUuid(CUuuid *uuid, CUdevice dev);

/**
 * \brief Return an UUID for the device (11.4+)
 *
 * Returns 16-octets identifying the device \p dev in the structure
 * pointed by the \p uuid. If the device is in MIG mode, returns its
 * MIG UUID which uniquely identifies the subscribed MIG compute instance.
 *
 * \param uuid - Returned UUID
 * \param dev  - Device to get identifier string for
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_DEVICE
 * \notefnerr
 *
 * \sa
 * ::cuDeviceGetAttribute,
 * ::cuDeviceGetCount,
 * ::cuDeviceGetName,
 * ::cuDeviceGetLuid,
 * ::cuDeviceGet,
 * ::cuDeviceTotalMem,
 * ::cudaGetDeviceProperties
 */
CUresult CUDAAPI cuDeviceGetUuid_v2(CUuuid *uuid, CUdevice dev);

/**
 * \brief Return an LUID and device node mask for the device
 *
 * Return identifying information (\p luid and \p deviceNodeMask) to allow
 * matching device with graphics APIs.
 *
 * \param luid - Returned LUID
 * \param deviceNodeMask - Returned device node mask
 * \param dev  - Device to get identifier string for
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_DEVICE
 * \notefnerr
 *
 * \sa
 * ::cuDeviceGetAttribute,
 * ::cuDeviceGetCount,
 * ::cuDeviceGetName,
 * ::cuDeviceGet,
 * ::cuDeviceTotalMem,
 * ::cuDeviceGetExecAffinitySupport,
 * ::cudaGetDeviceProperties
 */
CUresult CUDAAPI cuDeviceGetLuid(char *luid, unsigned int *deviceNodeMask, CUdevice dev);

/**
 * \brief Returns the total amount of memory on the device
 *
 * Returns in \p *bytes the total amount of memory available on the device
 * \p dev in bytes.
 *
 * \param bytes - Returned memory available on device in bytes
 * \param dev   - Device handle
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_DEVICE
 * \notefnerr
 *
 * \sa
 * ::cuDeviceGetAttribute,
 * ::cuDeviceGetCount,
 * ::cuDeviceGetName,
 * ::cuDeviceGetUuid,
 * ::cuDeviceGet,
 * ::cuDeviceGetExecAffinitySupport,
 * ::cudaMemGetInfo
 */
CUresult CUDAAPI cuDeviceTotalMem(size_t *bytes, CUdevice dev);

/**
 * \brief Returns the maximum number of elements allocatable in a 1D linear texture for a given texture element size.
 *
 * Returns in \p maxWidthInElements the maximum number of texture elements allocatable in a 1D linear texture
 * for given \p format and \p numChannels.
 *
 * \param maxWidthInElements    - Returned maximum number of texture elements allocatable for given \p format and \p numChannels.
 * \param format                - Texture format.
 * \param numChannels           - Number of channels per texture element.
 * \param dev                   - Device handle.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_DEVICE
 * \notefnerr
 *
 * \sa
 * ::cuDeviceGetAttribute,
 * ::cuDeviceGetCount,
 * ::cuDeviceGetName,
 * ::cuDeviceGetUuid,
 * ::cuDeviceGet,
 * ::cudaMemGetInfo,
 * ::cuDeviceTotalMem
 */
CUresult CUDAAPI cuDeviceGetTexture1DLinearMaxWidth(size_t *maxWidthInElements, CUarray_format format, unsigned numChannels, CUdevice dev);

/**
 * \brief Returns information about the device
 *
 * Returns in \p *pi the integer value of the attribute \p attrib on device
 * \p dev. The supported attributes are:
 * - ::CU_DEVICE_ATTRIBUTE_MAX_THREADS_PER_BLOCK: Maximum number of threads per
 *   block;
 * - ::CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_X: Maximum x-dimension of a block
 * - ::CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_Y: Maximum y-dimension of a block
 * - ::CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_Z: Maximum z-dimension of a block
 * - ::CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_X: Maximum x-dimension of a grid
 * - ::CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_Y: Maximum y-dimension of a grid
 * - ::CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_Z: Maximum z-dimension of a grid
 * - ::CU_DEVICE_ATTRIBUTE_MAX_SHARED_MEMORY_PER_BLOCK: Maximum amount of
 *   shared memory available to a thread block in bytes
 * - ::CU_DEVICE_ATTRIBUTE_TOTAL_CONSTANT_MEMORY: Memory available on device for
 *   __constant__ variables in a CUDA C kernel in bytes
 * - ::CU_DEVICE_ATTRIBUTE_WARP_SIZE: Warp size in threads
 * - ::CU_DEVICE_ATTRIBUTE_MAX_PITCH: Maximum pitch in bytes allowed by the
 *   memory copy functions that involve memory regions allocated through
 *   ::cuMemAllocPitch()
 * - ::CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE1D_WIDTH: Maximum 1D
 *  texture width
 * - ::CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE1D_LINEAR_WIDTH: Maximum width
 *  for a 1D texture bound to linear memory
 * - ::CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE1D_MIPMAPPED_WIDTH: Maximum
 *  mipmapped 1D texture width
 * - ::CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_WIDTH: Maximum 2D
 *  texture width
 * - ::CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_HEIGHT: Maximum 2D
 *  texture height
 * - ::CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_LINEAR_WIDTH: Maximum width
 *  for a 2D texture bound to linear memory
 * - ::CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_LINEAR_HEIGHT: Maximum height
 *  for a 2D texture bound to linear memory
 * - ::CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_LINEAR_PITCH: Maximum pitch
 *  in bytes for a 2D texture bound to linear memory
 * - ::CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_MIPMAPPED_WIDTH: Maximum
 *  mipmapped 2D texture width
 * - ::CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_MIPMAPPED_HEIGHT: Maximum
 *  mipmapped 2D texture height
 * - ::CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE3D_WIDTH: Maximum 3D
 *  texture width
 * - ::CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE3D_HEIGHT: Maximum 3D
 *  texture height
 * - ::CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE3D_DEPTH: Maximum 3D
 *  texture depth
 * - ::CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE3D_WIDTH_ALTERNATE:
 *  Alternate maximum 3D texture width, 0 if no alternate
 *  maximum 3D texture size is supported
 * - ::CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE3D_HEIGHT_ALTERNATE:
 *  Alternate maximum 3D texture height, 0 if no alternate
 *  maximum 3D texture size is supported
 * - ::CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE3D_DEPTH_ALTERNATE:
 *  Alternate maximum 3D texture depth, 0 if no alternate
 *  maximum 3D texture size is supported
 * - ::CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURECUBEMAP_WIDTH:
 *  Maximum cubemap texture width or height
 * - ::CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE1D_LAYERED_WIDTH:
 *  Maximum 1D layered texture width
 * - ::CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE1D_LAYERED_LAYERS:
 *   Maximum layers in a 1D layered texture
 * - ::CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_LAYERED_WIDTH:
 *  Maximum 2D layered texture width
 * - ::CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_LAYERED_HEIGHT:
 *   Maximum 2D layered texture height
 * - ::CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_LAYERED_LAYERS:
 *   Maximum layers in a 2D layered texture
 * - ::CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURECUBEMAP_LAYERED_WIDTH:
 *   Maximum cubemap layered texture width or height
 * - ::CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURECUBEMAP_LAYERED_LAYERS:
 *   Maximum layers in a cubemap layered texture
 * - ::CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACE1D_WIDTH:
 *   Maximum 1D surface width
 * - ::CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACE2D_WIDTH:
 *   Maximum 2D surface width
 * - ::CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACE2D_HEIGHT:
 *   Maximum 2D surface height
 * - ::CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACE3D_WIDTH:
 *   Maximum 3D surface width
 * - ::CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACE3D_HEIGHT:
 *   Maximum 3D surface height
 * - ::CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACE3D_DEPTH:
 *   Maximum 3D surface depth
 * - ::CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACE1D_LAYERED_WIDTH:
 *   Maximum 1D layered surface width
 * - ::CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACE1D_LAYERED_LAYERS:
 *   Maximum layers in a 1D layered surface
 * - ::CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACE2D_LAYERED_WIDTH:
 *   Maximum 2D layered surface width
 * - ::CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACE2D_LAYERED_HEIGHT:
 *   Maximum 2D layered surface height
 * - ::CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACE2D_LAYERED_LAYERS:
 *   Maximum layers in a 2D layered surface
 * - ::CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACECUBEMAP_WIDTH:
 *   Maximum cubemap surface width
 * - ::CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACECUBEMAP_LAYERED_WIDTH:
 *   Maximum cubemap layered surface width
 * - ::CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACECUBEMAP_LAYERED_LAYERS:
 *   Maximum layers in a cubemap layered surface
 * - ::CU_DEVICE_ATTRIBUTE_MAX_REGISTERS_PER_BLOCK: Maximum number of 32-bit
 *   registers available to a thread block
 * - ::CU_DEVICE_ATTRIBUTE_CLOCK_RATE: The typical clock frequency in kilohertz
 * - ::CU_DEVICE_ATTRIBUTE_TEXTURE_ALIGNMENT: Alignment requirement; texture
 *   base addresses aligned to ::textureAlign bytes do not need an offset
 *   applied to texture fetches
 * - ::CU_DEVICE_ATTRIBUTE_TEXTURE_PITCH_ALIGNMENT: Pitch alignment requirement
 *   for 2D texture references bound to pitched memory
 * - ::CU_DEVICE_ATTRIBUTE_GPU_OVERLAP: 1 if the device can concurrently copy
 *   memory between host and device while executing a kernel, or 0 if not
 * - ::CU_DEVICE_ATTRIBUTE_MULTIPROCESSOR_COUNT: Number of multiprocessors on
 *   the device
 * - ::CU_DEVICE_ATTRIBUTE_KERNEL_EXEC_TIMEOUT: 1 if there is a run time limit
 *   for kernels executed on the device, or 0 if not
 * - ::CU_DEVICE_ATTRIBUTE_INTEGRATED: 1 if the device is integrated with the
 *   memory subsystem, or 0 if not
 * - ::CU_DEVICE_ATTRIBUTE_CAN_MAP_HOST_MEMORY: 1 if the device can map host
 *   memory into the CUDA address space, or 0 if not
 * - ::CU_DEVICE_ATTRIBUTE_COMPUTE_MODE: Compute mode that device is currently
 *   in. Available modes are as follows:
 *   - ::CU_COMPUTEMODE_DEFAULT: Default mode - Device is not restricted and
 *     can have multiple CUDA contexts present at a single time.
 *   - ::CU_COMPUTEMODE_PROHIBITED: Compute-prohibited mode - Device is
 *     prohibited from creating new CUDA contexts.
 *   - ::CU_COMPUTEMODE_EXCLUSIVE_PROCESS:  Compute-exclusive-process mode - Device
 *     can have only one context used by a single process at a time.
 * - ::CU_DEVICE_ATTRIBUTE_CONCURRENT_KERNELS: 1 if the device supports
 *   executing multiple kernels within the same context simultaneously, or 0 if
 *   not. It is not guaranteed that multiple kernels will be resident
 *   on the device concurrently so this feature should not be relied upon for
 *   correctness.
 * - ::CU_DEVICE_ATTRIBUTE_ECC_ENABLED: 1 if error correction is enabled on the
 *    device, 0 if error correction is disabled or not supported by the device
 * - ::CU_DEVICE_ATTRIBUTE_PCI_BUS_ID: PCI bus identifier of the device
 * - ::CU_DEVICE_ATTRIBUTE_PCI_DEVICE_ID: PCI device (also known as slot) identifier
 *   of the device
 * - ::CU_DEVICE_ATTRIBUTE_PCI_DOMAIN_ID: PCI domain identifier of the device
 * - ::CU_DEVICE_ATTRIBUTE_TCC_DRIVER: 1 if the device is using a TCC driver. TCC
 *    is only available on Tesla hardware running Windows Vista or later
 * - ::CU_DEVICE_ATTRIBUTE_MEMORY_CLOCK_RATE: Peak memory clock frequency in kilohertz
 * - ::CU_DEVICE_ATTRIBUTE_GLOBAL_MEMORY_BUS_WIDTH: Global memory bus width in bits
 * - ::CU_DEVICE_ATTRIBUTE_L2_CACHE_SIZE: Size of L2 cache in bytes. 0 if the device doesn't have L2 cache
 * - ::CU_DEVICE_ATTRIBUTE_MAX_THREADS_PER_MULTIPROCESSOR: Maximum resident threads per multiprocessor
 * - ::CU_DEVICE_ATTRIBUTE_UNIFIED_ADDRESSING: 1 if the device shares a unified address space with
 *   the host, or 0 if not
 * - ::CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MAJOR: Major compute capability version number
 * - ::CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MINOR: Minor compute capability version number
 * - ::CU_DEVICE_ATTRIBUTE_GLOBAL_L1_CACHE_SUPPORTED: 1 if device supports caching globals
 *    in L1 cache, 0 if caching globals in L1 cache is not supported by the device
 * - ::CU_DEVICE_ATTRIBUTE_LOCAL_L1_CACHE_SUPPORTED: 1 if device supports caching locals
 *    in L1 cache, 0 if caching locals in L1 cache is not supported by the device
 * - ::CU_DEVICE_ATTRIBUTE_MAX_SHARED_MEMORY_PER_MULTIPROCESSOR: Maximum amount of
 *   shared memory available to a multiprocessor in bytes; this amount is shared
 *   by all thread blocks simultaneously resident on a multiprocessor
 * - ::CU_DEVICE_ATTRIBUTE_MAX_REGISTERS_PER_MULTIPROCESSOR: Maximum number of 32-bit
 *   registers available to a multiprocessor; this number is shared by all thread
 *   blocks simultaneously resident on a multiprocessor
 * - ::CU_DEVICE_ATTRIBUTE_MANAGED_MEMORY: 1 if device supports allocating managed memory
 *   on this system, 0 if allocating managed memory is not supported by the device on this system.
 * - ::CU_DEVICE_ATTRIBUTE_MULTI_GPU_BOARD: 1 if device is on a multi-GPU board, 0 if not.
 * - ::CU_DEVICE_ATTRIBUTE_MULTI_GPU_BOARD_GROUP_ID: Unique identifier for a group of devices
 *   associated with the same board. Devices on the same multi-GPU board will share the same identifier.
 * - ::CU_DEVICE_ATTRIBUTE_HOST_NATIVE_ATOMIC_SUPPORTED: 1 if Link between the device and the host
 *   supports native atomic operations.
 * - ::CU_DEVICE_ATTRIBUTE_SINGLE_TO_DOUBLE_PRECISION_PERF_RATIO: Ratio of single precision performance
 *   (in floating-point operations per second) to double precision performance.
 * - ::CU_DEVICE_ATTRIBUTE_PAGEABLE_MEMORY_ACCESS: Device supports coherently accessing
 *   pageable memory without calling cudaHostRegister on it.
 * - ::CU_DEVICE_ATTRIBUTE_CONCURRENT_MANAGED_ACCESS: Device can coherently access managed memory
 *   concurrently with the CPU.
 * - ::CU_DEVICE_ATTRIBUTE_COMPUTE_PREEMPTION_SUPPORTED: Device supports Compute Preemption.
 * - ::CU_DEVICE_ATTRIBUTE_CAN_USE_HOST_POINTER_FOR_REGISTERED_MEM: Device can access host registered
 *   memory at the same virtual address as the CPU.
 * -  ::CU_DEVICE_ATTRIBUTE_MAX_SHARED_MEMORY_PER_BLOCK_OPTIN: The maximum per block shared memory size
 *    supported on this device. This is the maximum value that can be opted into when using the cuFuncSetAttribute() or cuKernelSetAttribute() call.
 *    For more details see ::CU_FUNC_ATTRIBUTE_MAX_DYNAMIC_SHARED_SIZE_BYTES
 * - ::CU_DEVICE_ATTRIBUTE_PAGEABLE_MEMORY_ACCESS_USES_HOST_PAGE_TABLES: Device accesses pageable memory via the host's
 *   page tables.
 * - ::CU_DEVICE_ATTRIBUTE_DIRECT_MANAGED_MEM_ACCESS_FROM_HOST: The host can directly access managed memory on the device without migration.
 * - ::CU_DEVICE_ATTRIBUTE_VIRTUAL_MEMORY_MANAGEMENT_SUPPORTED:  Device supports virtual memory management APIs like ::cuMemAddressReserve, ::cuMemCreate, ::cuMemMap and related APIs
 * - ::CU_DEVICE_ATTRIBUTE_HANDLE_TYPE_POSIX_FILE_DESCRIPTOR_SUPPORTED: Device supports exporting memory to a posix file descriptor with ::cuMemExportToShareableHandle, if requested via ::cuMemCreate
 * - ::CU_DEVICE_ATTRIBUTE_HANDLE_TYPE_WIN32_HANDLE_SUPPORTED:  Device supports exporting memory to a Win32 NT handle with ::cuMemExportToShareableHandle, if requested via ::cuMemCreate
 * - ::CU_DEVICE_ATTRIBUTE_HANDLE_TYPE_WIN32_KMT_HANDLE_SUPPORTED: Device supports exporting memory to a Win32 KMT handle with ::cuMemExportToShareableHandle, if requested via ::cuMemCreate
 * - ::CU_DEVICE_ATTRIBUTE_MAX_BLOCKS_PER_MULTIPROCESSOR: Maximum number of thread blocks that can reside on a multiprocessor
 * - ::CU_DEVICE_ATTRIBUTE_GENERIC_COMPRESSION_SUPPORTED: Device supports compressible memory allocation via ::cuMemCreate
 * - ::CU_DEVICE_ATTRIBUTE_MAX_PERSISTING_L2_CACHE_SIZE: Maximum L2 persisting lines capacity setting in bytes
 * - ::CU_DEVICE_ATTRIBUTE_MAX_ACCESS_POLICY_WINDOW_SIZE: Maximum value of CUaccessPolicyWindow::num_bytes 
 * - ::CU_DEVICE_ATTRIBUTE_GPU_DIRECT_RDMA_WITH_CUDA_VMM_SUPPORTED: Device supports specifying the GPUDirect RDMA flag with ::cuMemCreate.
 * - ::CU_DEVICE_ATTRIBUTE_RESERVED_SHARED_MEMORY_PER_BLOCK: Amount of shared memory per block reserved by CUDA driver in bytes
 * - ::CU_DEVICE_ATTRIBUTE_SPARSE_CUDA_ARRAY_SUPPORTED: Device supports sparse CUDA arrays and sparse CUDA mipmapped arrays. 
 * - ::CU_DEVICE_ATTRIBUTE_READ_ONLY_HOST_REGISTER_SUPPORTED: Device supports using the ::cuMemHostRegister flag ::CU_MEMHOSTERGISTER_READ_ONLY to register memory that must be mapped as read-only to the GPU
 * - ::CU_DEVICE_ATTRIBUTE_MEMORY_POOLS_SUPPORTED: Device supports using the ::cuMemAllocAsync and ::cuMemPool family of APIs
 * - ::CU_DEVICE_ATTRIBUTE_GPU_DIRECT_RDMA_SUPPORTED: Device supports GPUDirect RDMA APIs, like nvidia_p2p_get_pages (see https://docs.nvidia.com/cuda/gpudirect-rdma for more information)
 * - ::CU_DEVICE_ATTRIBUTE_GPU_DIRECT_RDMA_FLUSH_WRITES_OPTIONS: The returned attribute shall be interpreted as a bitmask, where the individual bits are described by the ::CUflushGPUDirectRDMAWritesOptions enum
 * - ::CU_DEVICE_ATTRIBUTE_GPU_DIRECT_RDMA_WRITES_ORDERING: GPUDirect RDMA writes to the device do not need to be flushed for consumers within the scope indicated by the returned attribute. See ::CUGPUDirectRDMAWritesOrdering for the numerical values returned here.
 * - ::CU_DEVICE_ATTRIBUTE_MEMPOOL_SUPPORTED_HANDLE_TYPES: Bitmask of handle types supported with mempool based IPC
 * - ::CU_DEVICE_ATTRIBUTE_DEFERRED_MAPPING_CUDA_ARRAY_SUPPORTED: Device supports deferred mapping CUDA arrays and CUDA mipmapped arrays.
 * - ::CU_DEVICE_ATTRIBUTE_NUMA_CONFIG: NUMA configuration of a device: value is of type ::CUdeviceNumaConfig enum
 * - ::CU_DEVICE_ATTRIBUTE_NUMA_ID: NUMA node ID of the GPU memory
 * - ::CU_DEVICE_ATTRIBUTE_MULTICAST_SUPPORTED: Device supports switch multicast and reduction operations.
 * - ::CU_DEVICE_ATTRIBUTE_GPU_PCI_DEVICE_ID: The combined 16-bit PCI device ID and 16-bit PCI vendor ID.
 * - ::CU_DEVICE_ATTRIBUTE_GPU_PCI_SUBSYSTEM_ID: The combined 16-bit PCI subsystem ID and 16-bit PCI subsystem vendor ID.
ID.
 *
 * \param pi     - Returned device attribute value
 * \param attrib - Device attribute to query
 * \param dev    - Device handle
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_DEVICE
 * \notefnerr
 *
 * \sa
 * ::cuDeviceGetCount,
 * ::cuDeviceGetName,
 * ::cuDeviceGetUuid,
 * ::cuDeviceGet,
 * ::cuDeviceTotalMem,
 * ::cuDeviceGetExecAffinitySupport,
 * ::cudaDeviceGetAttribute,
 * ::cudaGetDeviceProperties
 */
CUresult CUDAAPI cuDeviceGetAttribute(int *pi, CUdevice_attribute attrib, CUdevice dev);

/**
 * \brief Return NvSciSync attributes that this device can support.
 *
 * Returns in \p nvSciSyncAttrList, the properties of NvSciSync that
 * this CUDA device, \p dev can support. The returned \p nvSciSyncAttrList
 * can be used to create an NvSciSync object that matches this device's capabilities.
 * 
 * If NvSciSyncAttrKey_RequiredPerm field in \p nvSciSyncAttrList is
 * already set this API will return ::CUDA_ERROR_INVALID_VALUE.
 * 
 * The applications should set \p nvSciSyncAttrList to a valid 
 * NvSciSyncAttrList failing which this API will return
 * ::CUDA_ERROR_INVALID_HANDLE.
 * 
 * The \p flags controls how applications intends to use
 * the NvSciSync created from the \p nvSciSyncAttrList. The valid flags are:
 * - ::CUDA_NVSCISYNC_ATTR_SIGNAL, specifies that the applications intends to 
 * signal an NvSciSync on this CUDA device.
 * - ::CUDA_NVSCISYNC_ATTR_WAIT, specifies that the applications intends to 
 * wait on an NvSciSync on this CUDA device.
 *
 * At least one of these flags must be set, failing which the API
 * returns ::CUDA_ERROR_INVALID_VALUE. Both the flags are orthogonal
 * to one another: a developer may set both these flags that allows to
 * set both wait and signal specific attributes in the same \p nvSciSyncAttrList.
 *
 * Note that this API updates the input \p nvSciSyncAttrList with values equivalent
 * to the following public attribute key-values:
 * NvSciSyncAttrKey_RequiredPerm is set to
 * - NvSciSyncAccessPerm_SignalOnly if ::CUDA_NVSCISYNC_ATTR_SIGNAL is set in \p flags.
 * - NvSciSyncAccessPerm_WaitOnly if ::CUDA_NVSCISYNC_ATTR_WAIT is set in \p flags.
 * - NvSciSyncAccessPerm_WaitSignal if both ::CUDA_NVSCISYNC_ATTR_WAIT and
 * ::CUDA_NVSCISYNC_ATTR_SIGNAL are set in \p flags.
 * NvSciSyncAttrKey_PrimitiveInfo is set to
 * - NvSciSyncAttrValPrimitiveType_SysmemSemaphore on any valid \p device.
 * - NvSciSyncAttrValPrimitiveType_Syncpoint if \p device is a Tegra device.
 * - NvSciSyncAttrValPrimitiveType_SysmemSemaphorePayload64b if \p device is GA10X+.
 * NvSciSyncAttrKey_GpuId is set to the same UUID that is returned for this 
 * \p device from ::cuDeviceGetUuid.
 *
 * \param nvSciSyncAttrList     - Return NvSciSync attributes supported.
 * \param dev                   - Valid Cuda Device to get NvSciSync attributes for.
 * \param flags                 - flags describing NvSciSync usage.
 *
 * \return
 *
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_INVALID_DEVICE,
 * ::CUDA_ERROR_NOT_SUPPORTED,
 * ::CUDA_ERROR_OUT_OF_MEMORY
 *
 * \sa
 * ::cuImportExternalSemaphore,
 * ::cuDestroyExternalSemaphore,
 * ::cuSignalExternalSemaphoresAsync,
 * ::cuWaitExternalSemaphoresAsync
 */
CUresult CUDAAPI cuDeviceGetNvSciSyncAttributes(void *nvSciSyncAttrList, CUdevice dev, int flags);

/**
 * \brief Sets the current memory pool of a device
 *
 * The memory pool must be local to the specified device.
 * ::cuMemAllocAsync allocates from the current mempool of the provided stream's device.
 * By default, a device's current memory pool is its default memory pool.
 *
 * \note Use ::cuMemAllocFromPoolAsync to specify asynchronous allocations from a device different
 * than the one the stream runs on. 
 *
 * \returns
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa ::cuDeviceGetDefaultMemPool, ::cuDeviceGetMemPool, ::cuMemPoolCreate, ::cuMemPoolDestroy, ::cuMemAllocFromPoolAsync
 */
CUresult CUDAAPI cuDeviceSetMemPool(CUdevice dev, CUmemoryPool pool);

/**
 * \brief Gets the current mempool for a device
 *
 * Returns the last pool provided to ::cuDeviceSetMemPool for this device
 * or the device's default memory pool if ::cuDeviceSetMemPool has never been called.
 * By default the current mempool is the default mempool for a device.
 * Otherwise the returned pool must have been set with ::cuDeviceSetMemPool.
 *
 * \returns
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa ::cuDeviceGetDefaultMemPool, ::cuMemPoolCreate, ::cuDeviceSetMemPool
 */
CUresult CUDAAPI cuDeviceGetMemPool(CUmemoryPool *pool, CUdevice dev);

/**
 * \brief Returns the default mempool of a device
 *
 * The default mempool of a device contains device memory from that device.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_DEVICE,
 * ::CUDA_ERROR_NOT_SUPPORTED
 * \notefnerr
 *
 * \sa ::cuMemAllocAsync, ::cuMemPoolTrimTo, ::cuMemPoolGetAttribute, ::cuMemPoolSetAttribute, cuMemPoolSetAccess, ::cuDeviceGetMemPool, ::cuMemPoolCreate
 */
CUresult CUDAAPI cuDeviceGetDefaultMemPool(CUmemoryPool *pool_out, CUdevice dev);

/**
 * \brief Returns information about the execution affinity support of the device.
 *
 * Returns in \p *pi whether execution affinity type \p type is supported by device \p dev.
 * The supported types are:
 * - ::CU_EXEC_AFFINITY_TYPE_SM_COUNT: 1 if context with limited SMs is supported by the device,
 *   or 0 if not;
 *
 * \param pi   - 1 if the execution affinity type \p type is supported by the device, or 0 if not
 * \param type - Execution affinity type to query
 * \param dev  - Device handle
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_DEVICE
 * \notefnerr
 *
 * \sa
 * ::cuDeviceGetAttribute,
 * ::cuDeviceGetCount,
 * ::cuDeviceGetName,
 * ::cuDeviceGetUuid,
 * ::cuDeviceGet,
 * ::cuDeviceTotalMem
 */
CUresult CUDAAPI cuDeviceGetExecAffinitySupport(int *pi, CUexecAffinityType type, CUdevice dev);

/**
 * \brief Blocks until remote writes are visible to the specified scope
 *
 * Blocks until GPUDirect RDMA writes to the target context via mappings
 * created through APIs like nvidia_p2p_get_pages (see
 * https://docs.nvidia.com/cuda/gpudirect-rdma for more information), are
 * visible to the specified scope.
 *
 * If the scope equals or lies within the scope indicated by
 * ::CU_DEVICE_ATTRIBUTE_GPU_DIRECT_RDMA_WRITES_ORDERING, the call
 * will be a no-op and can be safely omitted for performance. This can be
 * determined by comparing the numerical values between the two enums, with
 * smaller scopes having smaller values.
 *
 * On platforms that support GPUDirect RDMA writes via more than one path in
 * hardware (see ::CU_MEM_RANGE_FLAG_DMA_BUF_MAPPING_TYPE_PCIE), the user should
 * consider those paths as belonging to separate ordering domains. Note that in
 * such cases CUDA driver will report both RDMA writes ordering and RDMA write
 * scope as ALL_DEVICES and a call to cuFlushGPUDirectRDMA will be a no-op,
 * but when these multiple paths are used simultaneously, it is the user's
 * responsibility to ensure ordering by using mechanisms outside the scope of
 * CUDA.
 *
 * Users may query support for this API via
 * ::CU_DEVICE_ATTRIBUTE_FLUSH_FLUSH_GPU_DIRECT_RDMA_OPTIONS.
 *
 * \param target - The target of the operation, see ::CUflushGPUDirectRDMAWritesTarget
 * \param scope  - The scope of the operation, see ::CUflushGPUDirectRDMAWritesScope
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * \notefnerr
 *
 */
CUresult CUDAAPI cuFlushGPUDirectRDMAWrites(CUflushGPUDirectRDMAWritesTarget target, CUflushGPUDirectRDMAWritesScope scope);

/** @} */ /* END CUDA_DEVICE */

/**
 * \defgroup CUDA_DEVICE_DEPRECATED Device Management [DEPRECATED]
 *
 * ___MANBRIEF___ deprecated device management functions of the low-level CUDA
 * driver API (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the device management functions of the low-level
 * CUDA driver application programming interface.
 *
 * @{
 */

/**
 * \brief Returns properties for a selected device
 *
 * \deprecated
 *
 * This function was deprecated as of CUDA 5.0 and replaced by ::cuDeviceGetAttribute().
 *
 * Returns in \p *prop the properties of device \p dev. The ::CUdevprop
 * structure is defined as:
 *
 * \code
     typedef struct CUdevprop_st {
     int maxThreadsPerBlock;
     int maxThreadsDim[3];
     int maxGridSize[3];
     int sharedMemPerBlock;
     int totalConstantMemory;
     int SIMDWidth;
     int memPitch;
     int regsPerBlock;
     int clockRate;
     int textureAlign
  } CUdevprop;
 * \endcode
 * where:
 *
 * - ::maxThreadsPerBlock is the maximum number of threads per block;
 * - ::maxThreadsDim[3] is the maximum sizes of each dimension of a block;
 * - ::maxGridSize[3] is the maximum sizes of each dimension of a grid;
 * - ::sharedMemPerBlock is the total amount of shared memory available per
 *   block in bytes;
 * - ::totalConstantMemory is the total amount of constant memory available on
 *   the device in bytes;
 * - ::SIMDWidth is the warp size;
 * - ::memPitch is the maximum pitch allowed by the memory copy functions that
 *   involve memory regions allocated through ::cuMemAllocPitch();
 * - ::regsPerBlock is the total number of registers available per block;
 * - ::clockRate is the clock frequency in kilohertz;
 * - ::textureAlign is the alignment requirement; texture base addresses that
 *   are aligned to ::textureAlign bytes do not need an offset applied to
 *   texture fetches.
 *
 * \param prop - Returned properties of device
 * \param dev  - Device to get properties for
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_DEVICE
 * \notefnerr
 *
 * \sa
 * ::cuDeviceGetAttribute,
 * ::cuDeviceGetCount,
 * ::cuDeviceGetName,
 * ::cuDeviceGetUuid,
 * ::cuDeviceGet,
 * ::cuDeviceTotalMem
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuDeviceGetProperties(CUdevprop *prop, CUdevice dev);

/**
 * \brief Returns the compute capability of the device
 *
 * \deprecated
 *
 * This function was deprecated as of CUDA 5.0 and its functionality superseded
 * by ::cuDeviceGetAttribute().
 *
 * Returns in \p *major and \p *minor the major and minor revision numbers that
 * define the compute capability of the device \p dev.
 *
 * \param major - Major revision number
 * \param minor - Minor revision number
 * \param dev   - Device handle
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_DEVICE
 * \notefnerr
 *
 * \sa
 * ::cuDeviceGetAttribute,
 * ::cuDeviceGetCount,
 * ::cuDeviceGetName,
 * ::cuDeviceGetUuid,
 * ::cuDeviceGet,
 * ::cuDeviceTotalMem
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuDeviceComputeCapability(int *major, int *minor, CUdevice dev);

/** @} */ /* END CUDA_DEVICE_DEPRECATED */

/**
 * \defgroup CUDA_PRIMARY_CTX Primary Context Management
 *
 * ___MANBRIEF___ primary context management functions of the low-level CUDA driver
 * API (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the primary context management functions of the low-level
 * CUDA driver application programming interface.
 *
 * The primary context is unique per device and shared with the CUDA runtime API.
 * These functions allow integration with other libraries using CUDA.
 *
 * @{
 */

/**
 * \brief Retain the primary context on the GPU
 *
 * Retains the primary context on the device.
 * Once the user successfully retains the primary context, the primary context
 * will be active and available to the user until the user releases it
 * with ::cuDevicePrimaryCtxRelease() or resets it with ::cuDevicePrimaryCtxReset().
 * Unlike ::cuCtxCreate() the newly retained context is not pushed onto the stack.
 *
 * Retaining the primary context for the first time will fail with ::CUDA_ERROR_UNKNOWN
 * if the compute mode of the device is ::CU_COMPUTEMODE_PROHIBITED. The function
 * ::cuDeviceGetAttribute() can be used with ::CU_DEVICE_ATTRIBUTE_COMPUTE_MODE to
 * determine the compute mode  of the device.
 * The <i>nvidia-smi</i> tool can be used to set the compute mode for
 * devices. Documentation for <i>nvidia-smi</i> can be obtained by passing a
 * -h option to it.
 *
 * Please note that the primary context always supports pinned allocations. Other
 * flags can be specified by ::cuDevicePrimaryCtxSetFlags().
 *
 * \param pctx  - Returned context handle of the new context
 * \param dev   - Device for which primary context is requested
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_DEVICE,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_OUT_OF_MEMORY,
 * ::CUDA_ERROR_UNKNOWN
 * \notefnerr
 *
 * \sa ::cuDevicePrimaryCtxRelease,
 * ::cuDevicePrimaryCtxSetFlags,
 * ::cuCtxCreate,
 * ::cuCtxGetApiVersion,
 * ::cuCtxGetCacheConfig,
 * ::cuCtxGetDevice,
 * ::cuCtxGetFlags,
 * ::cuCtxGetLimit,
 * ::cuCtxPopCurrent,
 * ::cuCtxPushCurrent,
 * ::cuCtxSetCacheConfig,
 * ::cuCtxSetLimit,
 * ::cuCtxSynchronize
 */
CUresult CUDAAPI cuDevicePrimaryCtxRetain(CUcontext *pctx, CUdevice dev);

/**
 * \brief Release the primary context on the GPU
 *
 * Releases the primary context interop on the device.
 * A retained context should always be released once the user is done using
 * it. The context is automatically reset once the last reference to it is
 * released. This behavior is different when the primary context was retained
 * by the CUDA runtime from CUDA 4.0 and earlier. In this case, the primary
 * context remains always active.
 *
 * Releasing a primary context that has not been previously retained will
 * fail with ::CUDA_ERROR_INVALID_CONTEXT.
 *
 * Please note that unlike ::cuCtxDestroy() this method does not pop the context
 * from stack in any circumstances.
 *
 * \param dev - Device which primary context is released
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_DEVICE,
 * ::CUDA_ERROR_INVALID_CONTEXT
 * \notefnerr
 *
 * \sa ::cuDevicePrimaryCtxRetain,
 * ::cuCtxDestroy,
 * ::cuCtxGetApiVersion,
 * ::cuCtxGetCacheConfig,
 * ::cuCtxGetDevice,
 * ::cuCtxGetFlags,
 * ::cuCtxGetLimit,
 * ::cuCtxPopCurrent,
 * ::cuCtxPushCurrent,
 * ::cuCtxSetCacheConfig,
 * ::cuCtxSetLimit,
 * ::cuCtxSynchronize
 */
CUresult CUDAAPI cuDevicePrimaryCtxRelease(CUdevice dev);

/**
 * \brief Set flags for the primary context
 *
 * Sets the flags for the primary context on the device overwriting perviously
 * set ones.
 *
 * The three LSBs of the \p flags parameter can be used to control how the OS
 * thread, which owns the CUDA context at the time of an API call, interacts
 * with the OS scheduler when waiting for results from the GPU. Only one of
 * the scheduling flags can be set when creating a context.
 *
 * - ::CU_CTX_SCHED_SPIN: Instruct CUDA to actively spin when waiting for
 * results from the GPU. This can decrease latency when waiting for the GPU,
 * but may lower the performance of CPU threads if they are performing work in
 * parallel with the CUDA thread.
 *
 * - ::CU_CTX_SCHED_YIELD: Instruct CUDA to yield its thread when waiting for
 * results from the GPU. This can increase latency when waiting for the GPU,
 * but can increase the performance of CPU threads performing work in parallel
 * with the GPU.
 *
 * - ::CU_CTX_SCHED_BLOCKING_SYNC: Instruct CUDA to block the CPU thread on a
 * synchronization primitive when waiting for the GPU to finish work.
 *
 * - ::CU_CTX_BLOCKING_SYNC: Instruct CUDA to block the CPU thread on a
 * synchronization primitive when waiting for the GPU to finish work. <br>
 * <b>Deprecated:</b> This flag was deprecated as of CUDA 4.0 and was
 * replaced with ::CU_CTX_SCHED_BLOCKING_SYNC.
 *
 * - ::CU_CTX_SCHED_AUTO: The default value if the \p flags parameter is zero,
 * uses a heuristic based on the number of active CUDA contexts in the
 * process \e C and the number of logical processors in the system \e P. If
 * \e C > \e P, then CUDA will yield to other OS threads when waiting for
 * the GPU (::CU_CTX_SCHED_YIELD), otherwise CUDA will not yield while
 * waiting for results and actively spin on the processor (::CU_CTX_SCHED_SPIN).
 * Additionally, on Tegra devices, ::CU_CTX_SCHED_AUTO uses a heuristic based on
 * the power profile of the platform and may choose ::CU_CTX_SCHED_BLOCKING_SYNC
 * for low-powered devices.
 *
 * - ::CU_CTX_LMEM_RESIZE_TO_MAX: Instruct CUDA to not reduce local memory
 * after resizing local memory for a kernel. This can prevent thrashing by
 * local memory allocations when launching many kernels with high local
 * memory usage at the cost of potentially increased memory usage. <br>
 * <b>Deprecated:</b> This flag is deprecated and the behavior enabled
 * by this flag is now the default and cannot be disabled.
 *
 * - ::CU_CTX_COREDUMP_ENABLE: If GPU coredumps have not been enabled globally
 * with ::cuCoredumpSetAttributeGlobal or environment variables, this flag can
 * be set during context creation to instruct CUDA to create a coredump if
 * this context raises an exception during execution. These environment variables
 * are described in the CUDA-GDB user guide under the "GPU core dump support"
 * section.
 * The initial settings will be taken from the global settings at the time of
 * context creation. The other settings that control coredump output can be 
 * modified by calling ::cuCoredumpSetAttribute from the created context after
 * it becomes current.
 *
 * - ::CU_CTX_USER_COREDUMP_ENABLE: If user-triggered GPU coredumps have not
 * been enabled globally with ::cuCoredumpSetAttributeGlobal or environment 
 * variables, this flag can be set during context creation to instruct CUDA to
 * create a coredump if data is written to a certain pipe that is present in the
 * OS space. These environment variables are described in the CUDA-GDB user
 * guide under the "GPU core dump support" section.
 * It is important to note that the pipe name *must* be set with
 * ::cuCoredumpSetAttributeGlobal before creating the context if this flag is
 * used. Setting this flag implies that ::CU_CTX_COREDUMP_ENABLE is set.
 * The initial settings will be taken from the global settings at the time of
 * context creation. The other settings that control coredump output can be 
 * modified by calling ::cuCoredumpSetAttribute from the created context after 
 * it becomes current.
 *
 * - ::CU_CTX_SYNC_MEMOPS: Ensures that synchronous memory operations initiated
 * on this context will always synchronize. See further documentation in the
 * section titled "API Synchronization behavior" to learn more about cases when
 * synchronous memory operations can exhibit asynchronous behavior.
 *
 * \param dev   - Device for which the primary context flags are set
 * \param flags - New flags for the device
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_DEVICE,
 * ::CUDA_ERROR_INVALID_VALUE,
 * \notefnerr
 *
 * \sa ::cuDevicePrimaryCtxRetain,
 * ::cuDevicePrimaryCtxGetState,
 * ::cuCtxCreate,
 * ::cuCtxGetFlags,
 * ::cuCtxSetFlags,
 * ::cudaSetDeviceFlags
 */
CUresult CUDAAPI cuDevicePrimaryCtxSetFlags(CUdevice dev, unsigned int flags);

/**
 * \brief Get the state of the primary context
 *
 * Returns in \p *flags the flags for the primary context of \p dev, and in
 * \p *active whether it is active.  See ::cuDevicePrimaryCtxSetFlags for flag
 * values.
 *
 * \param dev    - Device to get primary context flags for
 * \param flags  - Pointer to store flags
 * \param active - Pointer to store context state; 0 = inactive, 1 = active
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_DEVICE,
 * ::CUDA_ERROR_INVALID_VALUE,
 * \notefnerr
 *
 * \sa
 * ::cuDevicePrimaryCtxSetFlags,
 * ::cuCtxGetFlags,
 * ::cuCtxSetFlags,
 * ::cudaGetDeviceFlags
 */
CUresult CUDAAPI cuDevicePrimaryCtxGetState(CUdevice dev, unsigned int *flags, int *active);

/**
 * \brief Destroy all allocations and reset all state on the primary context
 *
 * Explicitly destroys and cleans up all resources associated with the current
 * device in the current process.
 *
 * Note that it is responsibility of the calling function to ensure that no
 * other module in the process is using the device any more. For that reason
 * it is recommended to use ::cuDevicePrimaryCtxRelease() in most cases.
 * However it is safe for other modules to call ::cuDevicePrimaryCtxRelease()
 * even after resetting the device.
 * Resetting the primary context does not release it, an application that has
 * retained the primary context should explicitly release its usage.
 *
 * \param dev - Device for which primary context is destroyed
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_DEVICE,
 * ::CUDA_ERROR_PRIMARY_CONTEXT_ACTIVE
 * \notefnerr
 *
 * \sa ::cuDevicePrimaryCtxRetain,
 * ::cuDevicePrimaryCtxRelease,
 * ::cuCtxGetApiVersion,
 * ::cuCtxGetCacheConfig,
 * ::cuCtxGetDevice,
 * ::cuCtxGetFlags,
 * ::cuCtxGetLimit,
 * ::cuCtxPopCurrent,
 * ::cuCtxPushCurrent,
 * ::cuCtxSetCacheConfig,
 * ::cuCtxSetLimit,
 * ::cuCtxSynchronize,
 * ::cudaDeviceReset
 */
CUresult CUDAAPI cuDevicePrimaryCtxReset(CUdevice dev);

/** @} */ /* END CUDA_PRIMARY_CTX */

/**
 * \defgroup CUDA_CTX Context Management
 *
 * ___MANBRIEF___ context management functions of the low-level CUDA driver
 * API (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the context management functions of the low-level
 * CUDA driver application programming interface.
 *
 * Please note that some functions are described in
 * \ref CUDA_PRIMARY_CTX "Primary Context Management" section.
 *
 * @{
 */

/**
 * \brief Create a CUDA context
 *
 * \note In most cases it is recommended to use ::cuDevicePrimaryCtxRetain.
 *
 * Creates a new CUDA context and associates it with the calling thread. The
 * \p flags parameter is described below. The context is created with a usage
 * count of 1 and the caller of ::cuCtxCreate() must call ::cuCtxDestroy()
 * when done using the context. If a context is already current to the thread,
 * it is supplanted by the newly created context and may be restored by a subsequent
 * call to ::cuCtxPopCurrent().
 *
 * The three LSBs of the \p flags parameter can be used to control how the OS
 * thread, which owns the CUDA context at the time of an API call, interacts
 * with the OS scheduler when waiting for results from the GPU. Only one of
 * the scheduling flags can be set when creating a context.
 *
 * - ::CU_CTX_SCHED_SPIN: Instruct CUDA to actively spin when waiting for
 * results from the GPU. This can decrease latency when waiting for the GPU,
 * but may lower the performance of CPU threads if they are performing work in
 * parallel with the CUDA thread.
 *
 * - ::CU_CTX_SCHED_YIELD: Instruct CUDA to yield its thread when waiting for
 * results from the GPU. This can increase latency when waiting for the GPU,
 * but can increase the performance of CPU threads performing work in parallel
 * with the GPU.
 *
 * - ::CU_CTX_SCHED_BLOCKING_SYNC: Instruct CUDA to block the CPU thread on a
 * synchronization primitive when waiting for the GPU to finish work.
 *
 * - ::CU_CTX_BLOCKING_SYNC: Instruct CUDA to block the CPU thread on a
 * synchronization primitive when waiting for the GPU to finish work. <br>
 * <b>Deprecated:</b> This flag was deprecated as of CUDA 4.0 and was
 * replaced with ::CU_CTX_SCHED_BLOCKING_SYNC.
 *
 * - ::CU_CTX_SCHED_AUTO: The default value if the \p flags parameter is zero,
 * uses a heuristic based on the number of active CUDA contexts in the
 * process \e C and the number of logical processors in the system \e P. If
 * \e C > \e P, then CUDA will yield to other OS threads when waiting for
 * the GPU (::CU_CTX_SCHED_YIELD), otherwise CUDA will not yield while
 * waiting for results and actively spin on the processor (::CU_CTX_SCHED_SPIN).
 * Additionally, on Tegra devices, ::CU_CTX_SCHED_AUTO uses a heuristic based on
 * the power profile of the platform and may choose ::CU_CTX_SCHED_BLOCKING_SYNC
 * for low-powered devices.
 *
 * - ::CU_CTX_MAP_HOST: Instruct CUDA to support mapped pinned allocations.
 * This flag must be set in order to allocate pinned host memory that is
 * accessible to the GPU.
 *
 * - ::CU_CTX_LMEM_RESIZE_TO_MAX: Instruct CUDA to not reduce local memory
 * after resizing local memory for a kernel. This can prevent thrashing by
 * local memory allocations when launching many kernels with high local
 * memory usage at the cost of potentially increased memory usage. <br>
 * <b>Deprecated:</b> This flag is deprecated and the behavior enabled
 * by this flag is now the default and cannot be disabled.
 * Instead, the per-thread stack size can be controlled with ::cuCtxSetLimit().
 *
 * - ::CU_CTX_COREDUMP_ENABLE: If GPU coredumps have not been enabled globally
 * with ::cuCoredumpSetAttributeGlobal or environment variables, this flag can
 * be set during context creation to instruct CUDA to create a coredump if
 * this context raises an exception during execution. These environment variables
 * are described in the CUDA-GDB user guide under the "GPU core dump support"
 * section.
 * The initial attributes will be taken from the global attributes at the time of
 * context creation. The other attributes that control coredump output can be 
 * modified by calling ::cuCoredumpSetAttribute from the created context after
 * it becomes current.
 *
 * - ::CU_CTX_USER_COREDUMP_ENABLE: If user-triggered GPU coredumps have not
 * been enabled globally with ::cuCoredumpSetAttributeGlobal or environment 
 * variables, this flag can be set during context creation to instruct CUDA to
 * create a coredump if data is written to a certain pipe that is present in the
 * OS space. These environment variables are described in the CUDA-GDB user
 * guide under the "GPU core dump support" section.
 * It is important to note that the pipe name *must* be set with
 * ::cuCoredumpSetAttributeGlobal before creating the context if this flag is
 * used. Setting this flag implies that ::CU_CTX_COREDUMP_ENABLE is set.
 * The initial attributes will be taken from the global attributes at the time of
 * context creation. The other attributes that control coredump output can be 
 * modified by calling ::cuCoredumpSetAttribute from the created context after 
 * it becomes current.
 * Setting this flag on any context creation is equivalent to setting the 
 * ::CU_COREDUMP_ENABLE_USER_TRIGGER attribute to \p true globally.
 *
 * - ::CU_CTX_SYNC_MEMOPS: Ensures that synchronous memory operations initiated
 * on this context will always synchronize. See further documentation in the
 * section titled "API Synchronization behavior" to learn more about cases when
 * synchronous memory operations can exhibit asynchronous behavior.
 *
 * Context creation will fail with ::CUDA_ERROR_UNKNOWN if the compute mode of
 * the device is ::CU_COMPUTEMODE_PROHIBITED. The function ::cuDeviceGetAttribute()
 * can be used with ::CU_DEVICE_ATTRIBUTE_COMPUTE_MODE to determine the
 * compute mode of the device. The <i>nvidia-smi</i> tool can be used to set
 * the compute mode for * devices.
 * Documentation for <i>nvidia-smi</i> can be obtained by passing a
 * -h option to it.
 *
 * \param pctx  - Returned context handle of the new context
 * \param flags - Context creation flags
 * \param dev   - Device to create context on
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_DEVICE,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_OUT_OF_MEMORY,
 * ::CUDA_ERROR_UNKNOWN
 * \notefnerr
 *
 * \sa ::cuCtxDestroy,
 * ::cuCtxGetApiVersion,
 * ::cuCtxGetCacheConfig,
 * ::cuCtxGetDevice,
 * ::cuCtxGetFlags,
 * ::cuCtxGetLimit,
 * ::cuCtxPopCurrent,
 * ::cuCtxPushCurrent,
 * ::cuCtxSetCacheConfig,
 * ::cuCtxSetLimit,
 * ::cuCoredumpSetAttributeGlobal,
 * ::cuCoredumpSetAttribute,
 * ::cuCtxSynchronize
 */
CUresult CUDAAPI cuCtxCreate(CUcontext *pctx, unsigned int flags, CUdevice dev);

/**
 * \brief Create a CUDA context with execution affinity
 *
 * Creates a new CUDA context with execution affinity and associates it with
 * the calling thread. The \p paramsArray and \p flags parameter are described below.
 * The context is created with a usage count of 1 and the caller of ::cuCtxCreate() must
 * call ::cuCtxDestroy() when done using the context. If a context is already
 * current to the thread, it is supplanted by the newly created context and may
 * be restored by a subsequent call to ::cuCtxPopCurrent().
 *
 * The type and the amount of execution resource the context can use is limited by \p paramsArray
 * and \p numParams. The \p paramsArray is an array of \p CUexecAffinityParam and the \p numParams
 * describes the size of the array. If two \p CUexecAffinityParam in the array have the same type,
 * the latter execution affinity parameter overrides the former execution affinity parameter.
 * The supported execution affinity types are:
 * - ::CU_EXEC_AFFINITY_TYPE_SM_COUNT limits the portion of SMs that the context can use. The portion
 *   of SMs is specified as the number of SMs via \p CUexecAffinitySmCount. This limit will be internally
 *   rounded up to the next hardware-supported amount. Hence, it is imperative to query the actual execution
 *   affinity of the context via \p cuCtxGetExecAffinity after context creation. Currently, this attribute
 *   is only supported under Volta+ MPS.
 *
 * The three LSBs of the \p flags parameter can be used to control how the OS
 * thread, which owns the CUDA context at the time of an API call, interacts
 * with the OS scheduler when waiting for results from the GPU. Only one of
 * the scheduling flags can be set when creating a context.
 *
 * - ::CU_CTX_SCHED_SPIN: Instruct CUDA to actively spin when waiting for
 * results from the GPU. This can decrease latency when waiting for the GPU,
 * but may lower the performance of CPU threads if they are performing work in
 * parallel with the CUDA thread.
 *
 * - ::CU_CTX_SCHED_YIELD: Instruct CUDA to yield its thread when waiting for
 * results from the GPU. This can increase latency when waiting for the GPU,
 * but can increase the performance of CPU threads performing work in parallel
 * with the GPU.
 *
 * - ::CU_CTX_SCHED_BLOCKING_SYNC: Instruct CUDA to block the CPU thread on a
 * synchronization primitive when waiting for the GPU to finish work.
 *
 * - ::CU_CTX_BLOCKING_SYNC: Instruct CUDA to block the CPU thread on a
 * synchronization primitive when waiting for the GPU to finish work. <br>
 * <b>Deprecated:</b> This flag was deprecated as of CUDA 4.0 and was
 * replaced with ::CU_CTX_SCHED_BLOCKING_SYNC.
 *
 * - ::CU_CTX_SCHED_AUTO: The default value if the \p flags parameter is zero,
 * uses a heuristic based on the number of active CUDA contexts in the
 * process \e C and the number of logical processors in the system \e P. If
 * \e C > \e P, then CUDA will yield to other OS threads when waiting for
 * the GPU (::CU_CTX_SCHED_YIELD), otherwise CUDA will not yield while
 * waiting for results and actively spin on the processor (::CU_CTX_SCHED_SPIN).
 * Additionally, on Tegra devices, ::CU_CTX_SCHED_AUTO uses a heuristic based on
 * the power profile of the platform and may choose ::CU_CTX_SCHED_BLOCKING_SYNC
 * for low-powered devices.
 *
 * - ::CU_CTX_MAP_HOST: Instruct CUDA to support mapped pinned allocations.
 * This flag must be set in order to allocate pinned host memory that is
 * accessible to the GPU.
 *
 * - ::CU_CTX_LMEM_RESIZE_TO_MAX: Instruct CUDA to not reduce local memory
 * after resizing local memory for a kernel. This can prevent thrashing by
 * local memory allocations when launching many kernels with high local
 * memory usage at the cost of potentially increased memory usage. <br>
 * <b>Deprecated:</b> This flag is deprecated and the behavior enabled
 * by this flag is now the default and cannot be disabled.
 * Instead, the per-thread stack size can be controlled with ::cuCtxSetLimit().
 *
 * - ::CU_CTX_COREDUMP_ENABLE: If GPU coredumps have not been enabled globally
 * with ::cuCoredumpSetAttributeGlobal or environment variables, this flag can
 * be set during context creation to instruct CUDA to create a coredump if
 * this context raises an exception during execution. These environment variables
 * are described in the CUDA-GDB user guide under the "GPU core dump support"
 * section.
 * The initial attributes will be taken from the global attributes at the time of
 * context creation. The other attributes that control coredump output can be 
 * modified by calling ::cuCoredumpSetAttribute from the created context after
 * it becomes current.
 *
 * - ::CU_CTX_USER_COREDUMP_ENABLE: If user-triggered GPU coredumps have not
 * been enabled globally with ::cuCoredumpSetAttributeGlobal or environment 
 * variables, this flag can be set during context creation to instruct CUDA to
 * create a coredump if data is written to a certain pipe that is present in the
 * OS space. These environment variables are described in the CUDA-GDB user
 * guide under the "GPU core dump support" section.
 * It is important to note that the pipe name *must* be set with
 * ::cuCoredumpSetAttributeGlobal before creating the context if this flag is
 * used. Setting this flag implies that ::CU_CTX_COREDUMP_ENABLE is set.
 * The initial attributes will be taken from the global attributes at the time of
 * context creation. The other attributes that control coredump output can be 
 * modified by calling ::cuCoredumpSetAttribute from the created context after 
 * it becomes current.
 * Setting this flag on any context creation is equivalent to setting the 
 * ::CU_COREDUMP_ENABLE_USER_TRIGGER attribute to \p true globally.
 *
 * Context creation will fail with ::CUDA_ERROR_UNKNOWN if the compute mode of
 * the device is ::CU_COMPUTEMODE_PROHIBITED. The function ::cuDeviceGetAttribute()
 * can be used with ::CU_DEVICE_ATTRIBUTE_COMPUTE_MODE to determine the
 * compute mode of the device. The <i>nvidia-smi</i> tool can be used to set
 * the compute mode for * devices.
 * Documentation for <i>nvidia-smi</i> can be obtained by passing a
 * -h option to it.
 *
 * \param pctx        - Returned context handle of the new context
 * \param paramsArray - Execution affinity parameters
 * \param numParams   - Number of execution affinity parameters
 * \param flags       - Context creation flags
 * \param dev         - Device to create context on
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_DEVICE,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_OUT_OF_MEMORY,
 * ::CUDA_ERROR_UNSUPPORTED_EXEC_AFFINITY,
 * ::CUDA_ERROR_UNKNOWN
 * \notefnerr
 *
 * \sa ::cuCtxDestroy,
 * ::cuCtxGetApiVersion,
 * ::cuCtxGetCacheConfig,
 * ::cuCtxGetDevice,
 * ::cuCtxGetFlags,
 * ::cuCtxGetLimit,
 * ::cuCtxPopCurrent,
 * ::cuCtxPushCurrent,
 * ::cuCtxSetCacheConfig,
 * ::cuCtxSetLimit,
 * ::cuCtxSynchronize,
 * ::cuCoredumpSetAttributeGlobal,
 * ::cuCoredumpSetAttribute,
 * ::CUexecAffinityParam
 */
CUresult CUDAAPI cuCtxCreate_v3(CUcontext *pctx, CUexecAffinityParam *paramsArray, int numParams, unsigned int flags, CUdevice dev);

/**
 * \brief Create a CUDA context
 *
 * Creates a new CUDA context and associates it with the calling thread. The
 * \p flags parameter is described below. The context is created with a usage
 * count of 1 and the caller of ::cuCtxCreate() must call ::cuCtxDestroy()
 * when done using the context. If a context is already current to the thread,
 * it is supplanted by the newly created context and may be restored by a subsequent
 * call to ::cuCtxPopCurrent().
 * 
 * CUDA context can be created with execution affinity. The type and the amount of 
   execution resource the context can use is limited by \p paramsArray and \p numExecAffinityParams
   in \p execAffinity. The \p paramsArray is an array of \p CUexecAffinityParam and the \p numExecAffinityParams
 * describes the size of the paramsArray. If two \p CUexecAffinityParam in the array have the same type,
 * the latter execution affinity parameter overrides the former execution affinity parameter.
 * The supported execution affinity types are:
 * - ::CU_EXEC_AFFINITY_TYPE_SM_COUNT limits the portion of SMs that the context can use. The portion
 *   of SMs is specified as the number of SMs via \p CUexecAffinitySmCount. This limit will be internally
 *   rounded up to the next hardware-supported amount. Hence, it is imperative to query the actual execution
 *   affinity of the context via \p cuCtxGetExecAffinity after context creation. Currently, this attribute
 *   is only supported under Volta+ MPS.
 * 
 * CUDA context can be created in CIG(CUDA in Graphics) mode by setting \p cigParams. 
 * Data from graphics client is shared with CUDA via the \p sharedData in \p cigParams. 
 * Support for D3D12 graphics client can be determined using ::cuDeviceGetAttribute() with 
 * ::CU_DEVICE_ATTRIBUTE_D3D12_CIG_SUPPORTED. \p sharedData is a ID3D12CommandQueue handle.
 * Either \p execAffinityParams or \p cigParams can be set to a non-null value. Setting both to a 
 * non-null value will result in an undefined behavior.
 * 
 * The three LSBs of the \p flags parameter can be used to control how the OS
 * thread, which owns the CUDA context at the time of an API call, interacts
 * with the OS scheduler when waiting for results from the GPU. Only one of
 * the scheduling flags can be set when creating a context.
 *
 * - ::CU_CTX_SCHED_SPIN: Instruct CUDA to actively spin when waiting for
 * results from the GPU. This can decrease latency when waiting for the GPU,
 * but may lower the performance of CPU threads if they are performing work in
 * parallel with the CUDA thread.
 *
 * - ::CU_CTX_SCHED_YIELD: Instruct CUDA to yield its thread when waiting for
 * results from the GPU. This can increase latency when waiting for the GPU,
 * but can increase the performance of CPU threads performing work in parallel
 * with the GPU.
 *
 * - ::CU_CTX_SCHED_BLOCKING_SYNC: Instruct CUDA to block the CPU thread on a
 * synchronization primitive when waiting for the GPU to finish work.
 *
 * - ::CU_CTX_BLOCKING_SYNC: Instruct CUDA to block the CPU thread on a
 * synchronization primitive when waiting for the GPU to finish work. <br>
 * <b>Deprecated:</b> This flag was deprecated as of CUDA 4.0 and was
 * replaced with ::CU_CTX_SCHED_BLOCKING_SYNC.
 *
 * - ::CU_CTX_SCHED_AUTO: The default value if the \p flags parameter is zero,
 * uses a heuristic based on the number of active CUDA contexts in the
 * process \e C and the number of logical processors in the system \e P. If
 * \e C > \e P, then CUDA will yield to other OS threads when waiting for
 * the GPU (::CU_CTX_SCHED_YIELD), otherwise CUDA will not yield while
 * waiting for results and actively spin on the processor (::CU_CTX_SCHED_SPIN).
 * Additionally, on Tegra devices, ::CU_CTX_SCHED_AUTO uses a heuristic based on
 * the power profile of the platform and may choose ::CU_CTX_SCHED_BLOCKING_SYNC
 * for low-powered devices.
 *
 * - ::CU_CTX_MAP_HOST: Instruct CUDA to support mapped pinned allocations.
 * This flag must be set in order to allocate pinned host memory that is
 * accessible to the GPU.
 *
 * - ::CU_CTX_LMEM_RESIZE_TO_MAX: Instruct CUDA to not reduce local memory
 * after resizing local memory for a kernel. This can prevent thrashing by
 * local memory allocations when launching many kernels with high local
 * memory usage at the cost of potentially increased memory usage. <br>
 * <b>Deprecated:</b> This flag is deprecated and the behavior enabled
 * by this flag is now the default and cannot be disabled.
 * Instead, the per-thread stack size can be controlled with ::cuCtxSetLimit().
 *
 * - ::CU_CTX_COREDUMP_ENABLE: If GPU coredumps have not been enabled globally
 * with ::cuCoredumpSetAttributeGlobal or environment variables, this flag can
 * be set during context creation to instruct CUDA to create a coredump if
 * this context raises an exception during execution. These environment variables
 * are described in the CUDA-GDB user guide under the "GPU core dump support"
 * section.
 * The initial attributes will be taken from the global attributes at the time of
 * context creation. The other attributes that control coredump output can be
 * modified by calling ::cuCoredumpSetAttribute from the created context after
 * it becomes current. This flag is not supported when CUDA context is created in
 * CIG(CUDA in Graphics) mode.
 *
 * - ::CU_CTX_USER_COREDUMP_ENABLE: If user-triggered GPU coredumps have not
 * been enabled globally with ::cuCoredumpSetAttributeGlobal or environment
 * variables, this flag can be set during context creation to instruct CUDA to
 * create a coredump if data is written to a certain pipe that is present in the
 * OS space. These environment variables are described in the CUDA-GDB user
 * guide under the "GPU core dump support" section.
 * It is important to note that the pipe name *must* be set with
 * ::cuCoredumpSetAttributeGlobal before creating the context if this flag is
 * used. Setting this flag implies that ::CU_CTX_COREDUMP_ENABLE is set.
 * The initial attributes will be taken from the global attributes at the time of
 * context creation. The other attributes that control coredump output can be
 * modified by calling ::cuCoredumpSetAttribute from the created context after
 * it becomes current.
 * Setting this flag on any context creation is equivalent to setting the
 * ::CU_COREDUMP_ENABLE_USER_TRIGGER attribute to \p true globally.
 * This flag is not supported when CUDA context is created in
 * CIG(CUDA in Graphics) mode.
 *
 * - ::CU_CTX_SYNC_MEMOPS: Ensures that synchronous memory operations initiated
 * on this context will always synchronize. See further documentation in the
 * section titled "API Synchronization behavior" to learn more about cases when
 * synchronous memory operations can exhibit asynchronous behavior.
 *
 * Context creation will fail with ::CUDA_ERROR_UNKNOWN if the compute mode of
 * the device is ::CU_COMPUTEMODE_PROHIBITED. The function ::cuDeviceGetAttribute()
 * can be used with ::CU_DEVICE_ATTRIBUTE_COMPUTE_MODE to determine the
 * compute mode of the device. The <i>nvidia-smi</i> tool can be used to set
 * the compute mode for * devices.
 * Documentation for <i>nvidia-smi</i> can be obtained by passing a
 * -h option to it.
 *
 * Context creation will fail with :: CUDA_ERROR_INVALID_VALUE if invalid parameter was
 * passed by client to create the CUDA context.
 * 
 * Context creation in CIG mode will fail with ::CUDA_ERROR_NOT_SUPPORTED if CIG is not supported
 * by the device or the driver.
 * \param pctx              - Returned context handle of the new context
 * \param ctxCreateParams   - Context creation parameters
 * \param flags             - Context creation flags
 * \param dev               - Device to create context on
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_DEVICE,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_NOT_SUPPORTED,
 * ::CUDA_ERROR_OUT_OF_MEMORY,
 * ::CUDA_ERROR_UNKNOWN
 * \notefnerr
 *
 * \sa ::cuCtxDestroy,
 * ::cuCtxGetApiVersion,
 * ::cuCtxGetCacheConfig,
 * ::cuCtxGetDevice,
 * ::cuCtxGetFlags,
 * ::cuCtxGetLimit,
 * ::cuCtxPopCurrent,
 * ::cuCtxPushCurrent,
 * ::cuCtxSetCacheConfig,
 * ::cuCtxSetLimit,
 * ::cuCoredumpSetAttributeGlobal,
 * ::cuCoredumpSetAttribute,
 * ::cuCtxSynchronize
 */
CUresult CUDAAPI cuCtxCreate_v4(CUcontext *pctx, CUctxCreateParams *ctxCreateParams, unsigned int flags, CUdevice dev);

/**
 * \brief Destroy a CUDA context
 *
 * Destroys the CUDA context specified by \p ctx.  The context \p ctx will be
 * destroyed regardless of how many threads it is current to.
 * It is the responsibility of the calling function to ensure that no API
 * call issues using \p ctx while ::cuCtxDestroy() is executing.
 *
 * Destroys and cleans up all resources associated with the context.
 * It is the caller's responsibility to ensure that the context or its resources
 * are not accessed or passed in subsequent API calls and doing so will result in undefined behavior.
 * These resources include CUDA types ::CUmodule, ::CUfunction, ::CUstream, ::CUevent,
 * ::CUarray, ::CUmipmappedArray, ::CUtexObject, ::CUsurfObject, ::CUtexref, ::CUsurfref,
 * ::CUgraphicsResource, ::CUlinkState, ::CUexternalMemory and ::CUexternalSemaphore.
 * These resources also include memory allocations by ::cuMemAlloc(), ::cuMemAllocHost(),
 * ::cuMemAllocManaged() and ::cuMemAllocPitch().
 *
 * If \p ctx is current to the calling thread then \p ctx will also be
 * popped from the current thread's context stack (as though ::cuCtxPopCurrent()
 * were called).  If \p ctx is current to other threads, then \p ctx will
 * remain current to those threads, and attempting to access \p ctx from
 * those threads will result in the error ::CUDA_ERROR_CONTEXT_IS_DESTROYED.
 *
 * \note ::cuCtxDestroy() will not destroy memory allocations by ::cuMemCreate(), ::cuMemAllocAsync() and
 * ::cuMemAllocFromPoolAsync(). These memory allocations are not associated with any CUDA context and need to
 * be destroyed explicitly.
 *
 * \param ctx - Context to destroy
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 *
 * \sa ::cuCtxCreate,
 * ::cuCtxGetApiVersion,
 * ::cuCtxGetCacheConfig,
 * ::cuCtxGetDevice,
 * ::cuCtxGetFlags,
 * ::cuCtxGetLimit,
 * ::cuCtxPopCurrent,
 * ::cuCtxPushCurrent,
 * ::cuCtxSetCacheConfig,
 * ::cuCtxSetLimit,
 * ::cuCtxSynchronize
 */
CUresult CUDAAPI cuCtxDestroy(CUcontext ctx);

/**
 * \brief Pushes a context on the current CPU thread
 *
 * Pushes the given context \p ctx onto the CPU thread's stack of current
 * contexts. The specified context becomes the CPU thread's current context, so
 * all CUDA functions that operate on the current context are affected.
 *
 * The previous current context may be made current again by calling
 * ::cuCtxDestroy() or ::cuCtxPopCurrent().
 *
 * \param ctx - Context to push
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 *
 * \sa ::cuCtxCreate,
 * ::cuCtxDestroy,
 * ::cuCtxGetApiVersion,
 * ::cuCtxGetCacheConfig,
 * ::cuCtxGetDevice,
 * ::cuCtxGetFlags,
 * ::cuCtxGetLimit,
 * ::cuCtxPopCurrent,
 * ::cuCtxSetCacheConfig,
 * ::cuCtxSetLimit,
 * ::cuCtxSynchronize
 */
CUresult CUDAAPI cuCtxPushCurrent(CUcontext ctx);

/**
 * \brief Pops the current CUDA context from the current CPU thread.
 *
 * Pops the current CUDA context from the CPU thread and passes back the
 * old context handle in \p *pctx. That context may then be made current
 * to a different CPU thread by calling ::cuCtxPushCurrent().
 *
 * If a context was current to the CPU thread before ::cuCtxCreate() or
 * ::cuCtxPushCurrent() was called, this function makes that context current to
 * the CPU thread again.
 *
 * \param pctx - Returned popped context handle
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT
 * \notefnerr
 *
 * \sa ::cuCtxCreate,
 * ::cuCtxDestroy,
 * ::cuCtxGetApiVersion,
 * ::cuCtxGetCacheConfig,
 * ::cuCtxGetDevice,
 * ::cuCtxGetFlags,
 * ::cuCtxGetLimit,
 * ::cuCtxPushCurrent,
 * ::cuCtxSetCacheConfig,
 * ::cuCtxSetLimit,
 * ::cuCtxSynchronize
 */
CUresult CUDAAPI cuCtxPopCurrent(CUcontext *pctx);

/**
 * \brief Binds the specified CUDA context to the calling CPU thread
 *
 * Binds the specified CUDA context to the calling CPU thread.
 * If \p ctx is NULL then the CUDA context previously bound to the
 * calling CPU thread is unbound and ::CUDA_SUCCESS is returned.
 *
 * If there exists a CUDA context stack on the calling CPU thread, this
 * will replace the top of that stack with \p ctx.
 * If \p ctx is NULL then this will be equivalent to popping the top
 * of the calling CPU thread's CUDA context stack (or a no-op if the
 * calling CPU thread's CUDA context stack is empty).
 *
 * \param ctx - Context to bind to the calling CPU thread
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT
 * \notefnerr
 *
 * \sa
 * ::cuCtxGetCurrent,
 * ::cuCtxCreate,
 * ::cuCtxDestroy,
 * ::cudaSetDevice
 */
CUresult CUDAAPI cuCtxSetCurrent(CUcontext ctx);

/**
 * \brief Returns the CUDA context bound to the calling CPU thread.
 *
 * Returns in \p *pctx the CUDA context bound to the calling CPU thread.
 * If no context is bound to the calling CPU thread then \p *pctx is
 * set to NULL and ::CUDA_SUCCESS is returned.
 *
 * \param pctx - Returned context handle
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * \notefnerr
 *
 * \sa
 * ::cuCtxSetCurrent,
 * ::cuCtxCreate,
 * ::cuCtxDestroy,
 * ::cudaGetDevice
 */
CUresult CUDAAPI cuCtxGetCurrent(CUcontext *pctx);

/**
 * \brief Returns the device handle for the current context
 *
 * Returns in \p *device the handle of the current context's device.
 *
 * \param device - Returned device handle for the current context
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * \notefnerr
 *
 * \sa ::cuCtxCreate,
 * ::cuCtxDestroy,
 * ::cuCtxGetApiVersion,
 * ::cuCtxGetCacheConfig,
 * ::cuCtxGetFlags,
 * ::cuCtxGetLimit,
 * ::cuCtxPopCurrent,
 * ::cuCtxPushCurrent,
 * ::cuCtxSetCacheConfig,
 * ::cuCtxSetLimit,
 * ::cuCtxSynchronize,
 * ::cudaGetDevice
 */
CUresult CUDAAPI cuCtxGetDevice(CUdevice *device);

/**
 * \brief Returns the flags for the current context
 *
 * Returns in \p *flags the flags of the current context. See ::cuCtxCreate
 * for flag values.
 *
 * \param flags - Pointer to store flags of current context
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * \notefnerr
 *
 * \sa ::cuCtxCreate,
 * ::cuCtxGetApiVersion,
 * ::cuCtxGetCacheConfig,
 * ::cuCtxGetCurrent,
 * ::cuCtxGetDevice,
 * ::cuCtxGetLimit,
 * ::cuCtxGetSharedMemConfig,
 * ::cuCtxGetStreamPriorityRange,
 * ::cuCtxSetFlags,
 * ::cudaGetDeviceFlags
 */
CUresult CUDAAPI cuCtxGetFlags(unsigned int *flags);

/**
 * \brief Sets the flags for the current context
 *
 * Sets the flags for the current context overwriting previously set ones. See
 * ::cuDevicePrimaryCtxSetFlags for flag values.
 *
 * \param flags - Flags to set on the current context
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * \notefnerr
 *
 * \sa ::cuCtxCreate,
 * ::cuCtxGetApiVersion,
 * ::cuCtxGetCacheConfig,
 * ::cuCtxGetCurrent,
 * ::cuCtxGetDevice,
 * ::cuCtxGetLimit,
 * ::cuCtxGetSharedMemConfig,
 * ::cuCtxGetStreamPriorityRange,
 * ::cuCtxGetFlags,
 * ::cudaGetDeviceFlags,
 * ::cuDevicePrimaryCtxSetFlags,
 */
CUresult CUDAAPI cuCtxSetFlags(unsigned int flags);

/**
 * \brief Returns the unique Id associated with the context supplied
 *
 * Returns in \p ctxId the unique Id which is associated with a given context.
 * The Id is unique for the life of the program for this instance of CUDA.
 * If context is supplied as NULL and there is one current, the Id of the
 * current context is returned.
 *
 * \param ctx - Context for which to obtain the Id
 * \param ctxId - Pointer to store the Id of the context
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_CONTEXT_IS_DESTROYED,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 *
 * \sa ::cuCtxCreate,
 * ::cuCtxDestroy,
 * ::cuCtxGetApiVersion,
 * ::cuCtxGetCacheConfig,
 * ::cuCtxGetDevice,
 * ::cuCtxGetFlags,
 * ::cuCtxGetLimit,
 * ::cuCtxPushCurrent
 */
CUresult CUDAAPI cuCtxGetId(CUcontext ctx, unsigned long long *ctxId);

/**
 * \brief Block for the current context's tasks to complete
 *
 * Blocks until the current context has completed all preceding requested tasks.
 * If the current context is the primary context, green contexts that have been
 * created will also be synchronized.
 * ::cuCtxSynchronize() returns an error if one of the preceding tasks failed.
 * If the context was created with the ::CU_CTX_SCHED_BLOCKING_SYNC flag, the
 * CPU thread will block until the GPU context has finished its work.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT
 * \notefnerr
 *
 * \sa ::cuCtxCreate,
 * ::cuCtxDestroy,
 * ::cuCtxGetApiVersion,
 * ::cuCtxGetCacheConfig,
 * ::cuCtxGetDevice,
 * ::cuCtxGetFlags,
 * ::cuCtxGetLimit,
 * ::cuCtxPopCurrent,
 * ::cuCtxPushCurrent,
 * ::cuCtxSetCacheConfig,
 * ::cuCtxSetLimit,
 * ::cudaDeviceSynchronize
 */
CUresult CUDAAPI cuCtxSynchronize(void);

/**
 * \brief Set resource limits
 *
 * Setting \p limit to \p value is a request by the application to update
 * the current limit maintained by the context. The driver is free to
 * modify the requested value to meet h/w requirements (this could be
 * clamping to minimum or maximum values, rounding up to nearest element
 * size, etc). The application can use ::cuCtxGetLimit() to find out exactly
 * what the limit has been set to.
 *
 * Setting each ::CUlimit has its own specific restrictions, so each is
 * discussed here.
 *
 * - ::CU_LIMIT_STACK_SIZE controls the stack size in bytes of each GPU thread.
 *   The driver automatically increases the per-thread stack size
 *   for each kernel launch as needed. This size isn't reset back to the
 *   original value after each launch. Setting this value will take effect 
 *   immediately, and if necessary, the device will block until all preceding 
 *   requested tasks are complete.
 *
 * - ::CU_LIMIT_PRINTF_FIFO_SIZE controls the size in bytes of the FIFO used
 *   by the ::printf() device system call. Setting ::CU_LIMIT_PRINTF_FIFO_SIZE
 *   must be performed before launching any kernel that uses the ::printf()
 *   device system call, otherwise ::CUDA_ERROR_INVALID_VALUE will be returned.
 *
 * - ::CU_LIMIT_MALLOC_HEAP_SIZE controls the size in bytes of the heap used
 *   by the ::malloc() and ::free() device system calls. Setting
 *   ::CU_LIMIT_MALLOC_HEAP_SIZE must be performed before launching any kernel
 *   that uses the ::malloc() or ::free() device system calls, otherwise
 *   ::CUDA_ERROR_INVALID_VALUE will be returned.
 *
 * - ::CU_LIMIT_DEV_RUNTIME_SYNC_DEPTH controls the maximum nesting depth of
 *   a grid at which a thread can safely call ::cudaDeviceSynchronize(). Setting
 *   this limit must be performed before any launch of a kernel that uses the
 *   device runtime and calls ::cudaDeviceSynchronize() above the default sync
 *   depth, two levels of grids. Calls to ::cudaDeviceSynchronize() will fail
 *   with error code ::cudaErrorSyncDepthExceeded if the limitation is
 *   violated. This limit can be set smaller than the default or up the maximum
 *   launch depth of 24. When setting this limit, keep in mind that additional
 *   levels of sync depth require the driver to reserve large amounts of device
 *   memory which can no longer be used for user allocations. If these
 *   reservations of device memory fail, ::cuCtxSetLimit() will return
 *   ::CUDA_ERROR_OUT_OF_MEMORY, and the limit can be reset to a lower value.
 *   This limit is only applicable to devices of compute capability < 9.0.
 *   Attempting to set this limit on devices of other compute capability
 *   versions will result in the error ::CUDA_ERROR_UNSUPPORTED_LIMIT being
 *   returned.
 *
 * - ::CU_LIMIT_DEV_RUNTIME_PENDING_LAUNCH_COUNT controls the maximum number of
 *   outstanding device runtime launches that can be made from the current
 *   context. A grid is outstanding from the point of launch up until the grid
 *   is known to have been completed. Device runtime launches which violate
 *   this limitation fail and return ::cudaErrorLaunchPendingCountExceeded when
 *   ::cudaGetLastError() is called after launch. If more pending launches than
 *   the default (2048 launches) are needed for a module using the device
 *   runtime, this limit can be increased. Keep in mind that being able to
 *   sustain additional pending launches will require the driver to reserve
 *   larger amounts of device memory upfront which can no longer be used for
 *   allocations. If these reservations fail, ::cuCtxSetLimit() will return
 *   ::CUDA_ERROR_OUT_OF_MEMORY, and the limit can be reset to a lower value.
 *   This limit is only applicable to devices of compute capability 3.5 and
 *   higher. Attempting to set this limit on devices of compute capability less
 *   than 3.5 will result in the error ::CUDA_ERROR_UNSUPPORTED_LIMIT being
 *   returned.
 *
 * - ::CU_LIMIT_MAX_L2_FETCH_GRANULARITY controls the L2 cache fetch granularity.
 *   Values can range from 0B to 128B. This is purely a performance hint and
 *   it can be ignored or clamped depending on the platform.
 *
 * - ::CU_LIMIT_PERSISTING_L2_CACHE_SIZE controls size in bytes available for
 *   persisting L2 cache. This is purely a performance hint and it can be
 *   ignored or clamped depending on the platform.
 *
 * \param limit - Limit to set
 * \param value - Size of limit
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_UNSUPPORTED_LIMIT,
 * ::CUDA_ERROR_OUT_OF_MEMORY,
 * ::CUDA_ERROR_INVALID_CONTEXT
 * \notefnerr
 *
 * \sa ::cuCtxCreate,
 * ::cuCtxDestroy,
 * ::cuCtxGetApiVersion,
 * ::cuCtxGetCacheConfig,
 * ::cuCtxGetDevice,
 * ::cuCtxGetFlags,
 * ::cuCtxGetLimit,
 * ::cuCtxPopCurrent,
 * ::cuCtxPushCurrent,
 * ::cuCtxSetCacheConfig,
 * ::cuCtxSynchronize,
 * ::cudaDeviceSetLimit
 */
CUresult CUDAAPI cuCtxSetLimit(CUlimit limit, size_t value);

/**
 * \brief Returns resource limits
 *
 * Returns in \p *pvalue the current size of \p limit.  The supported
 * ::CUlimit values are:
 * - ::CU_LIMIT_STACK_SIZE: stack size in bytes of each GPU thread.
 * - ::CU_LIMIT_PRINTF_FIFO_SIZE: size in bytes of the FIFO used by the
 *   ::printf() device system call.
 * - ::CU_LIMIT_MALLOC_HEAP_SIZE: size in bytes of the heap used by the
 *   ::malloc() and ::free() device system calls.
 * - ::CU_LIMIT_DEV_RUNTIME_SYNC_DEPTH: maximum grid depth at which a thread
 *   can issue the device runtime call ::cudaDeviceSynchronize() to wait on
 *   child grid launches to complete.
 * - ::CU_LIMIT_DEV_RUNTIME_PENDING_LAUNCH_COUNT: maximum number of outstanding
 *   device runtime launches that can be made from this context.
 * - ::CU_LIMIT_MAX_L2_FETCH_GRANULARITY: L2 cache fetch granularity.
 * - ::CU_LIMIT_PERSISTING_L2_CACHE_SIZE: Persisting L2 cache size in bytes
 *
 * \param limit  - Limit to query
 * \param pvalue - Returned size of limit
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_UNSUPPORTED_LIMIT
 * \notefnerr
 *
 * \sa ::cuCtxCreate,
 * ::cuCtxDestroy,
 * ::cuCtxGetApiVersion,
 * ::cuCtxGetCacheConfig,
 * ::cuCtxGetDevice,
 * ::cuCtxGetFlags,
 * ::cuCtxPopCurrent,
 * ::cuCtxPushCurrent,
 * ::cuCtxSetCacheConfig,
 * ::cuCtxSetLimit,
 * ::cuCtxSynchronize,
 * ::cudaDeviceGetLimit
 */
CUresult CUDAAPI cuCtxGetLimit(size_t *pvalue, CUlimit limit);

/**
 * \brief Returns the preferred cache configuration for the current context.
 *
 * On devices where the L1 cache and shared memory use the same hardware
 * resources, this function returns through \p pconfig the preferred cache configuration
 * for the current context. This is only a preference. The driver will use
 * the requested configuration if possible, but it is free to choose a different
 * configuration if required to execute functions.
 *
 * This will return a \p pconfig of ::CU_FUNC_CACHE_PREFER_NONE on devices
 * where the size of the L1 cache and shared memory are fixed.
 *
 * The supported cache configurations are:
 * - ::CU_FUNC_CACHE_PREFER_NONE: no preference for shared memory or L1 (default)
 * - ::CU_FUNC_CACHE_PREFER_SHARED: prefer larger shared memory and smaller L1 cache
 * - ::CU_FUNC_CACHE_PREFER_L1: prefer larger L1 cache and smaller shared memory
 * - ::CU_FUNC_CACHE_PREFER_EQUAL: prefer equal sized L1 cache and shared memory
 *
 * \param pconfig - Returned cache configuration
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 *
 * \sa ::cuCtxCreate,
 * ::cuCtxDestroy,
 * ::cuCtxGetApiVersion,
 * ::cuCtxGetDevice,
 * ::cuCtxGetFlags,
 * ::cuCtxGetLimit,
 * ::cuCtxPopCurrent,
 * ::cuCtxPushCurrent,
 * ::cuCtxSetCacheConfig,
 * ::cuCtxSetLimit,
 * ::cuCtxSynchronize,
 * ::cuFuncSetCacheConfig,
 * ::cudaDeviceGetCacheConfig
 */
CUresult CUDAAPI cuCtxGetCacheConfig(CUfunc_cache *pconfig);

/**
 * \brief Sets the preferred cache configuration for the current context.
 *
 * On devices where the L1 cache and shared memory use the same hardware
 * resources, this sets through \p config the preferred cache configuration for
 * the current context. This is only a preference. The driver will use
 * the requested configuration if possible, but it is free to choose a different
 * configuration if required to execute the function. Any function preference
 * set via ::cuFuncSetCacheConfig() or ::cuKernelSetCacheConfig() will be preferred over this context-wide
 * setting. Setting the context-wide cache configuration to
 * ::CU_FUNC_CACHE_PREFER_NONE will cause subsequent kernel launches to prefer
 * to not change the cache configuration unless required to launch the kernel.
 *
 * This setting does nothing on devices where the size of the L1 cache and
 * shared memory are fixed.
 *
 * Launching a kernel with a different preference than the most recent
 * preference setting may insert a device-side synchronization point.
 *
 * The supported cache configurations are:
 * - ::CU_FUNC_CACHE_PREFER_NONE: no preference for shared memory or L1 (default)
 * - ::CU_FUNC_CACHE_PREFER_SHARED: prefer larger shared memory and smaller L1 cache
 * - ::CU_FUNC_CACHE_PREFER_L1: prefer larger L1 cache and smaller shared memory
 * - ::CU_FUNC_CACHE_PREFER_EQUAL: prefer equal sized L1 cache and shared memory
 *
 * \param config - Requested cache configuration
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 *
 * \sa ::cuCtxCreate,
 * ::cuCtxDestroy,
 * ::cuCtxGetApiVersion,
 * ::cuCtxGetCacheConfig,
 * ::cuCtxGetDevice,
 * ::cuCtxGetFlags,
 * ::cuCtxGetLimit,
 * ::cuCtxPopCurrent,
 * ::cuCtxPushCurrent,
 * ::cuCtxSetLimit,
 * ::cuCtxSynchronize,
 * ::cuFuncSetCacheConfig,
 * ::cudaDeviceSetCacheConfig,
 * ::cuKernelSetCacheConfig
 */
CUresult CUDAAPI cuCtxSetCacheConfig(CUfunc_cache config);

/**
 * \brief Gets the context's API version.
 *
 * Returns a version number in \p version corresponding to the capabilities of
 * the context (e.g. 3010 or 3020), which library developers can use to direct
 * callers to a specific API version. If \p ctx is NULL, returns the API version
 * used to create the currently bound context.
 *
 * Note that new API versions are only introduced when context capabilities are
 * changed that break binary compatibility, so the API version and driver version
 * may be different. For example, it is valid for the API version to be 3020 while
 * the driver version is 4020.
 *
 * \param ctx     - Context to check
 * \param version - Pointer to version
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_UNKNOWN
 * \notefnerr
 *
 * \sa ::cuCtxCreate,
 * ::cuCtxDestroy,
 * ::cuCtxGetDevice,
 * ::cuCtxGetFlags,
 * ::cuCtxGetLimit,
 * ::cuCtxPopCurrent,
 * ::cuCtxPushCurrent,
 * ::cuCtxSetCacheConfig,
 * ::cuCtxSetLimit,
 * ::cuCtxSynchronize
 */
CUresult CUDAAPI cuCtxGetApiVersion(CUcontext ctx, unsigned int *version);

/**
 * \brief Returns numerical values that correspond to the least and
 * greatest stream priorities.
 *
 * Returns in \p *leastPriority and \p *greatestPriority the numerical values that correspond
 * to the least and greatest stream priorities respectively. Stream priorities
 * follow a convention where lower numbers imply greater priorities. The range of
 * meaningful stream priorities is given by [\p *greatestPriority, \p *leastPriority].
 * If the user attempts to create a stream with a priority value that is
 * outside the meaningful range as specified by this API, the priority is
 * automatically clamped down or up to either \p *leastPriority or \p *greatestPriority
 * respectively. See ::cuStreamCreateWithPriority for details on creating a
 * priority stream.
 * A NULL may be passed in for \p *leastPriority or \p *greatestPriority if the value
 * is not desired.
 *
 * This function will return '0' in both \p *leastPriority and \p *greatestPriority if
 * the current context's device does not support stream priorities
 * (see ::cuDeviceGetAttribute).
 *
 * \param leastPriority    - Pointer to an int in which the numerical value for least
 *                           stream priority is returned
 * \param greatestPriority - Pointer to an int in which the numerical value for greatest
 *                           stream priority is returned
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * \notefnerr
 *
 * \sa ::cuStreamCreateWithPriority,
 * ::cuStreamGetPriority,
 * ::cuCtxGetDevice,
 * ::cuCtxGetFlags,
 * ::cuCtxSetLimit,
 * ::cuCtxSynchronize,
 * ::cudaDeviceGetStreamPriorityRange
 */
CUresult CUDAAPI cuCtxGetStreamPriorityRange(int *leastPriority, int *greatestPriority);

/**
 * \brief Resets all persisting lines in cache to normal status.
 *
 * ::cuCtxResetPersistingL2Cache Resets all persisting lines in cache to normal
 * status. Takes effect on function return.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_NOT_SUPPORTED
 * \notefnerr
 *
 * \sa
 * ::CUaccessPolicyWindow
 */
CUresult CUDAAPI cuCtxResetPersistingL2Cache(void);

/**
 * \brief Returns the execution affinity setting for the current context.
 *
 * Returns in \p *pExecAffinity the current value of \p type. The supported
 * ::CUexecAffinityType values are:
 * - ::CU_EXEC_AFFINITY_TYPE_SM_COUNT: number of SMs the context is limited to use.
 *
 * \param type          - Execution affinity type to query
 * \param pExecAffinity - Returned execution affinity
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_UNSUPPORTED_EXEC_AFFINITY
 * \notefnerr
 *
 * \sa
 * ::CUexecAffinityParam
 */
CUresult CUDAAPI cuCtxGetExecAffinity(CUexecAffinityParam *pExecAffinity, CUexecAffinityType type);

/**
 * \brief Records an event.
 *
 * Captures in \p hEvent all the activities of the context \p hCtx
 * at the time of this call. \p hEvent and \p hCtx must be from the same
 * CUDA context, otherwise ::CUDA_ERROR_INVALID_HANDLE will be returned.
 * Calls such as ::cuEventQuery() or ::cuCtxWaitEvent() will then examine
 * or wait for completion of the work that was captured.
 * Uses of \p hCtx after this call do not modify \p hEvent.
 * If the context passed to \p hCtx is the primary context, \p hEvent will
 * capture all the activities of the primary context and its green contexts.
 * If the context passed to \p hCtx is a context converted from green context
 * via ::cuCtxFromGreenCtx(), \p hEvent will capture only the activities of the green context.
 *
 * \note The API will return ::CUDA_ERROR_STREAM_CAPTURE_UNSUPPORTED if the
 * specified context \p hCtx has a stream in the capture mode. In such a case,
 * the call will invalidate all the conflicting captures.
 * 
 * \param hCtx - Context to record event for
 * \param hEvent - Event to record
 *
 * \return
 * ::CUDA_SUCCESS
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_STREAM_CAPTURE_UNSUPPORTED
 *
 * \sa
 * ::cuCtxWaitEvent,
 * ::cuGreenCtxRecordEvent,
 * ::cuGreenCtxWaitEvent,
 * ::cuEventRecord
 */
CUresult CUDAAPI cuCtxRecordEvent(CUcontext hCtx, CUevent hEvent);

/**
 * \brief Make a context wait on an event
 *
 * Makes all future work submitted to context \p hCtx wait for all work
 * captured in \p hEvent. The synchronization will be performed on the device
 * and will not block the calling CPU thread. See ::cuCtxRecordEvent()
 * for details on what is captured by an event.
 * If the context passed to \p hCtx is the primary context, the primary context
 * and its green contexts will wait for \p hEvent.
 * If the context passed to \p hCtx is a context converted from green context
 * via ::cuCtxFromGreenCtx(), the green context will wait for \p hEvent.
 *
 * \note \p hEvent may be from a different context or device than \p hCtx.
 *
 * \note The API will return ::CUDA_ERROR_STREAM_CAPTURE_UNSUPPORTED and
 * invalidate the capture if the specified event \p hEvent is part of an ongoing
 * capture sequence or if the specified context \p hCtx has a stream in the capture mode.
 *
 * \param hCtx    - Context to wait
 * \param hEvent  - Event to wait on
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_STREAM_CAPTURE_UNSUPPORTED
 *
 * \sa
 * ::cuCtxRecordEvent,
 * ::cuGreenCtxRecordEvent,
 * ::cuGreenCtxWaitEvent,
 * ::cuStreamWaitEvent
 */
CUresult CUDAAPI cuCtxWaitEvent(CUcontext hCtx, CUevent hEvent);

/** @} */ /* END CUDA_CTX */

/**
 * \defgroup CUDA_CTX_DEPRECATED Context Management [DEPRECATED]
 *
 * ___MANBRIEF___ deprecated context management functions of the low-level CUDA
 * driver API (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the deprecated context management functions of the low-level
 * CUDA driver application programming interface.
 *
 * @{
 */

/**
 * \brief Increment a context's usage-count
 *
 * \deprecated
 *
 * Note that this function is deprecated and should not be used.
 *
 * Increments the usage count of the context and passes back a context handle
 * in \p *pctx that must be passed to ::cuCtxDetach() when the application is
 * done with the context. ::cuCtxAttach() fails if there is no context current
 * to the thread.
 *
 * Currently, the \p flags parameter must be 0.
 *
 * \param pctx  - Returned context handle of the current context
 * \param flags - Context attach flags (must be 0)
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 *
 * \sa ::cuCtxCreate,
 * ::cuCtxDestroy,
 * ::cuCtxDetach,
 * ::cuCtxGetApiVersion,
 * ::cuCtxGetCacheConfig,
 * ::cuCtxGetDevice,
 * ::cuCtxGetFlags,
 * ::cuCtxGetLimit,
 * ::cuCtxPopCurrent,
 * ::cuCtxPushCurrent,
 * ::cuCtxSetCacheConfig,
 * ::cuCtxSetLimit,
 * ::cuCtxSynchronize
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuCtxAttach(CUcontext *pctx, unsigned int flags);

/**
 * \brief Decrement a context's usage-count
 *
 * \deprecated
 *
 * Note that this function is deprecated and should not be used.
 *
 * Decrements the usage count of the context \p ctx, and destroys the context
 * if the usage count goes to 0. The context must be a handle that was passed
 * back by ::cuCtxCreate() or ::cuCtxAttach(), and must be current to the
 * calling thread.
 *
 * \param ctx - Context to destroy
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT
 * \notefnerr
 *
 * \sa ::cuCtxCreate,
 * ::cuCtxDestroy,
 * ::cuCtxGetApiVersion,
 * ::cuCtxGetCacheConfig,
 * ::cuCtxGetDevice,
 * ::cuCtxGetFlags,
 * ::cuCtxGetLimit,
 * ::cuCtxPopCurrent,
 * ::cuCtxPushCurrent,
 * ::cuCtxSetCacheConfig,
 * ::cuCtxSetLimit,
 * ::cuCtxSynchronize
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuCtxDetach(CUcontext ctx);


/**
 * \brief Returns the current shared memory configuration for the current context.
 *
 * \deprecated
 *
 * This function will return in \p pConfig the current size of shared memory banks
 * in the current context. On devices with configurable shared memory banks,
 * ::cuCtxSetSharedMemConfig can be used to change this setting, so that all
 * subsequent kernel launches will by default use the new bank size. When
 * ::cuCtxGetSharedMemConfig is called on devices without configurable shared
 * memory, it will return the fixed bank size of the hardware.
 *
 * The returned bank configurations can be either:
 * - ::CU_SHARED_MEM_CONFIG_FOUR_BYTE_BANK_SIZE:  shared memory bank width is
 *   four bytes.
 * - ::CU_SHARED_MEM_CONFIG_EIGHT_BYTE_BANK_SIZE: shared memory bank width will
 *   eight bytes.
 *
 * \param pConfig - returned shared memory configuration
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 *
 * \sa ::cuCtxCreate,
 * ::cuCtxDestroy,
 * ::cuCtxGetApiVersion,
 * ::cuCtxGetCacheConfig,
 * ::cuCtxGetDevice,
 * ::cuCtxGetFlags,
 * ::cuCtxGetLimit,
 * ::cuCtxPopCurrent,
 * ::cuCtxPushCurrent,
 * ::cuCtxSetLimit,
 * ::cuCtxSynchronize,
 * ::cuCtxGetSharedMemConfig,
 * ::cuFuncSetCacheConfig,
 * ::cudaDeviceGetSharedMemConfig
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuCtxGetSharedMemConfig(CUsharedconfig *pConfig);

/**
 * \brief Sets the shared memory configuration for the current context.
 *
 * \deprecated
 *
 * On devices with configurable shared memory banks, this function will set
 * the context's shared memory bank size which is used for subsequent kernel
 * launches.
 *
 * Changed the shared memory configuration between launches may insert a device
 * side synchronization point between those launches.
 *
 * Changing the shared memory bank size will not increase shared memory usage
 * or affect occupancy of kernels, but may have major effects on performance.
 * Larger bank sizes will allow for greater potential bandwidth to shared memory,
 * but will change what kinds of accesses to shared memory will result in bank
 * conflicts.
 *
 * This function will do nothing on devices with fixed shared memory bank size.
 *
 * The supported bank configurations are:
 * - ::CU_SHARED_MEM_CONFIG_DEFAULT_BANK_SIZE: set bank width to the default initial
 *   setting (currently, four bytes).
 * - ::CU_SHARED_MEM_CONFIG_FOUR_BYTE_BANK_SIZE: set shared memory bank width to
 *   be natively four bytes.
 * - ::CU_SHARED_MEM_CONFIG_EIGHT_BYTE_BANK_SIZE: set shared memory bank width to
 *   be natively eight bytes.
 *
 * \param config - requested shared memory configuration
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 *
 * \sa ::cuCtxCreate,
 * ::cuCtxDestroy,
 * ::cuCtxGetApiVersion,
 * ::cuCtxGetCacheConfig,
 * ::cuCtxGetDevice,
 * ::cuCtxGetFlags,
 * ::cuCtxGetLimit,
 * ::cuCtxPopCurrent,
 * ::cuCtxPushCurrent,
 * ::cuCtxSetLimit,
 * ::cuCtxSynchronize,
 * ::cuCtxGetSharedMemConfig,
 * ::cuFuncSetCacheConfig,
 * ::cudaDeviceSetSharedMemConfig
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuCtxSetSharedMemConfig(CUsharedconfig config);

/** @} */ /* END CUDA_CTX_DEPRECATED */


/**
 * \defgroup CUDA_MODULE Module Management
 *
 * ___MANBRIEF___ module management functions of the low-level CUDA driver API
 * (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the module management functions of the low-level CUDA
 * driver application programming interface.
 *
 * @{
 */

/**
 * \brief Loads a compute module
 *
 * Takes a filename \p fname and loads the corresponding module \p module into
 * the current context. The CUDA driver API does not attempt to lazily
 * allocate the resources needed by a module; if the memory for functions and
 * data (constant and global) needed by the module cannot be allocated,
 * ::cuModuleLoad() fails. The file should be a \e cubin file as output by
 * \b nvcc, or a \e PTX file either as output by \b nvcc or handwritten, or
 * a \e fatbin file as output by \b nvcc from toolchain 4.0 or later.
 *
 * \param module - Returned module
 * \param fname  - Filename of module to load
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_PTX,
 * ::CUDA_ERROR_UNSUPPORTED_PTX_VERSION,
 * ::CUDA_ERROR_NOT_FOUND,
 * ::CUDA_ERROR_OUT_OF_MEMORY,
 * ::CUDA_ERROR_FILE_NOT_FOUND,
 * ::CUDA_ERROR_NO_BINARY_FOR_GPU,
 * ::CUDA_ERROR_SHARED_OBJECT_SYMBOL_NOT_FOUND,
 * ::CUDA_ERROR_SHARED_OBJECT_INIT_FAILED,
 * ::CUDA_ERROR_JIT_COMPILER_NOT_FOUND
 * \notefnerr
 *
 * \sa ::cuModuleGetFunction,
 * ::cuModuleGetGlobal,
 * ::cuModuleGetTexRef,
 * ::cuModuleLoadData,
 * ::cuModuleLoadDataEx,
 * ::cuModuleLoadFatBinary,
 * ::cuModuleUnload
 */
CUresult CUDAAPI cuModuleLoad(CUmodule *module, const char *fname);

/**
 * \brief Load a module's data
 *
 * Takes a pointer \p image and loads the corresponding module \p module into
 * the current context. The \p image may be a \e cubin or \e fatbin
 * as output by \b nvcc, or a NULL-terminated \e PTX, either as output by \b nvcc
 * or hand-written.
 *
 * \param module - Returned module
 * \param image  - Module data to load
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_PTX,
 * ::CUDA_ERROR_UNSUPPORTED_PTX_VERSION,
 * ::CUDA_ERROR_OUT_OF_MEMORY,
 * ::CUDA_ERROR_NO_BINARY_FOR_GPU,
 * ::CUDA_ERROR_SHARED_OBJECT_SYMBOL_NOT_FOUND,
 * ::CUDA_ERROR_SHARED_OBJECT_INIT_FAILED,
 * ::CUDA_ERROR_JIT_COMPILER_NOT_FOUND
 * \notefnerr
 *
 * \sa ::cuModuleGetFunction,
 * ::cuModuleGetGlobal,
 * ::cuModuleGetTexRef,
 * ::cuModuleLoad,
 * ::cuModuleLoadDataEx,
 * ::cuModuleLoadFatBinary,
 * ::cuModuleUnload
 */
CUresult CUDAAPI cuModuleLoadData(CUmodule *module, const void *image);

/**
 * \brief Load a module's data with options
 *
 * Takes a pointer \p image and loads the corresponding module \p module into
 * the current context. The \p image may be a \e cubin or \e fatbin
 * as output by \b nvcc, or a NULL-terminated \e PTX, either as output by \b nvcc
 * or hand-written.
 *
 * \param module       - Returned module
 * \param image        - Module data to load
 * \param numOptions   - Number of options
 * \param options      - Options for JIT
 * \param optionValues - Option values for JIT
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_PTX,
 * ::CUDA_ERROR_UNSUPPORTED_PTX_VERSION,
 * ::CUDA_ERROR_OUT_OF_MEMORY,
 * ::CUDA_ERROR_NO_BINARY_FOR_GPU,
 * ::CUDA_ERROR_SHARED_OBJECT_SYMBOL_NOT_FOUND,
 * ::CUDA_ERROR_SHARED_OBJECT_INIT_FAILED,
 * ::CUDA_ERROR_JIT_COMPILER_NOT_FOUND
 * \notefnerr
 *
 * \sa ::cuModuleGetFunction,
 * ::cuModuleGetGlobal,
 * ::cuModuleGetTexRef,
 * ::cuModuleLoad,
 * ::cuModuleLoadData,
 * ::cuModuleLoadFatBinary,
 * ::cuModuleUnload
 */
CUresult CUDAAPI cuModuleLoadDataEx(CUmodule *module, const void *image, unsigned int numOptions, CUjit_option *options, void **optionValues);

/**
 * \brief Load a module's data
 *
 * Takes a pointer \p fatCubin and loads the corresponding module \p module
 * into the current context. The pointer represents a <i>fat binary</i> object,
 * which is a collection of different \e cubin and/or \e PTX files, all
 * representing the same device code, but compiled and optimized for different
 * architectures.
 *
 * Prior to CUDA 4.0, there was no documented API for constructing and using
 * fat binary objects by programmers.  Starting with CUDA 4.0, fat binary
 * objects can be constructed by providing the <i>-fatbin option</i> to \b nvcc.
 * More information can be found in the \b nvcc document.
 *
 * \param module   - Returned module
 * \param fatCubin - Fat binary to load
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_PTX,
 * ::CUDA_ERROR_UNSUPPORTED_PTX_VERSION,
 * ::CUDA_ERROR_NOT_FOUND,
 * ::CUDA_ERROR_OUT_OF_MEMORY,
 * ::CUDA_ERROR_NO_BINARY_FOR_GPU,
 * ::CUDA_ERROR_SHARED_OBJECT_SYMBOL_NOT_FOUND,
 * ::CUDA_ERROR_SHARED_OBJECT_INIT_FAILED,
 * ::CUDA_ERROR_JIT_COMPILER_NOT_FOUND
 * \notefnerr
 *
 * \sa ::cuModuleGetFunction,
 * ::cuModuleGetGlobal,
 * ::cuModuleGetTexRef,
 * ::cuModuleLoad,
 * ::cuModuleLoadData,
 * ::cuModuleLoadDataEx,
 * ::cuModuleUnload
 */
CUresult CUDAAPI cuModuleLoadFatBinary(CUmodule *module, const void *fatCubin);

/**
 * \brief Unloads a module
 *
 * Unloads a module \p hmod from the current context. Attempting to unload
 * a module which was obtained from the Library Management API such as
 * ::cuLibraryGetModule will return ::CUDA_ERROR_NOT_PERMITTED.
 *
 * \param hmod - Module to unload
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_NOT_PERMITTED
 * \notefnerr
 * \note_destroy_ub
 *
 * \sa ::cuModuleGetFunction,
 * ::cuModuleGetGlobal,
 * ::cuModuleGetTexRef,
 * ::cuModuleLoad,
 * ::cuModuleLoadData,
 * ::cuModuleLoadDataEx,
 * ::cuModuleLoadFatBinary
 */
CUresult CUDAAPI cuModuleUnload(CUmodule hmod);

/**
 * CUDA Lazy Loading status
 */
typedef enum CUmoduleLoadingMode_enum {
    CU_MODULE_EAGER_LOADING = 0x1, /**< Lazy Kernel Loading is not enabled */
    CU_MODULE_LAZY_LOADING  = 0x2, /**< Lazy Kernel Loading is enabled */
} CUmoduleLoadingMode;

/**
 * \brief Query lazy loading mode
 *
 * Returns lazy loading mode
 * Module loading mode is controlled by CUDA_MODULE_LOADING env variable
 *
 * \param mode      - Returns the lazy loading mode
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * \notefnerr
 *
 * \sa
 * ::cuModuleLoad,
 */
CUresult CUDAAPI cuModuleGetLoadingMode(CUmoduleLoadingMode *mode);

/**
 * \brief Returns a function handle
 *
 * Returns in \p *hfunc the handle of the function of name \p name located in
 * module \p hmod. If no function of that name exists, ::cuModuleGetFunction()
 * returns ::CUDA_ERROR_NOT_FOUND.
 *
 * \param hfunc - Returned function handle
 * \param hmod  - Module to retrieve function from
 * \param name  - Name of function to retrieve
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_NOT_FOUND
 * \notefnerr
 *
 * \sa ::cuModuleGetGlobal,
 * ::cuModuleGetTexRef,
 * ::cuModuleLoad,
 * ::cuModuleLoadData,
 * ::cuModuleLoadDataEx,
 * ::cuModuleLoadFatBinary,
 * ::cuModuleUnload
 */
CUresult CUDAAPI cuModuleGetFunction(CUfunction *hfunc, CUmodule hmod, const char *name);

/**
 * \brief Returns the number of functions within a module
 *
 * Returns in \p count the number of functions in \p mod.
 *
 * \param count - Number of functions found within the module
 * \param mod - Module to query
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_INVALID_VALUE
 */
CUresult CUDAAPI cuModuleGetFunctionCount(unsigned int *count, CUmodule mod);

/**
 * \brief Returns the function handles within a module.
 *
 * Returns in \p functions a maximum number of \p numFunctions function handles within \p mod. When
 * function loading mode is set to LAZY the function retrieved may be partially loaded. The loading
 * state of a function can be queried using ::cuFunctionIsLoaded. CUDA APIs may load the function
 * automatically when called with partially loaded function handle which may incur additional
 * latency. Alternatively, ::cuFunctionLoad can be used to explicitly load a function. The returned
 * function handles become invalid when the module is unloaded.
 *
 * \param functions - Buffer where the function handles are returned to
 * \param numFunctions - Maximum number of function handles may be returned to the buffer
 * \param mod - Module to query from
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa ::cuModuleGetFunction,
 * ::cuModuleGetFunctionCount,
 * ::cuFuncIsLoaded,
 * ::cuFuncLoad
 */
CUresult CUDAAPI cuModuleEnumerateFunctions(CUfunction *functions, unsigned int numFunctions, CUmodule mod);

/**
 * \brief Returns a global pointer from a module
 *
 * Returns in \p *dptr and \p *bytes the base pointer and size of the
 * global of name \p name located in module \p hmod. If no variable of that name
 * exists, ::cuModuleGetGlobal() returns ::CUDA_ERROR_NOT_FOUND.
 * One of the parameters \p dptr or \p bytes (not both) can be NULL in which
 * case it is ignored.
 *
 * \param dptr  - Returned global device pointer
 * \param bytes - Returned global size in bytes
 * \param hmod  - Module to retrieve global from
 * \param name  - Name of global to retrieve
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_NOT_FOUND
 * \notefnerr
 *
 * \sa ::cuModuleGetFunction,
 * ::cuModuleGetTexRef,
 * ::cuModuleLoad,
 * ::cuModuleLoadData,
 * ::cuModuleLoadDataEx,
 * ::cuModuleLoadFatBinary,
 * ::cuModuleUnload,
 * ::cudaGetSymbolAddress,
 * ::cudaGetSymbolSize
 */
CUresult CUDAAPI cuModuleGetGlobal(CUdeviceptr *dptr, size_t *bytes, CUmodule hmod, const char *name);

/**
 * \brief Creates a pending JIT linker invocation.
 *
 * If the call is successful, the caller owns the returned CUlinkState, which
 * should eventually be destroyed with ::cuLinkDestroy.  The
 * device code machine size (32 or 64 bit) will match the calling application.
 *
 * Both linker and compiler options may be specified.  Compiler options will
 * be applied to inputs to this linker action which must be compiled from PTX.
 * The options ::CU_JIT_WALL_TIME,
 * ::CU_JIT_INFO_LOG_BUFFER_SIZE_BYTES, and ::CU_JIT_ERROR_LOG_BUFFER_SIZE_BYTES
 * will accumulate data until the CUlinkState is destroyed.
 *
 * The data passed in via ::cuLinkAddData and ::cuLinkAddFile will be treated
 * as relocatable (-rdc=true to nvcc) when linking the final cubin during 
 * ::cuLinkComplete and will have similar consequences as offline relocatable 
 * device code linking.
 *
 * \p optionValues must remain valid for the life of the CUlinkState if output
 * options are used.  No other references to inputs are maintained after this
 * call returns.
 *
 * \note For LTO-IR input, only LTO-IR compiled with toolkits prior to CUDA 12.0 will be accepted
 *
 * \param numOptions   Size of options arrays
 * \param options      Array of linker and compiler options
 * \param optionValues Array of option values, each cast to void *
 * \param stateOut     On success, this will contain a CUlinkState to specify
 *                     and complete this action
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_OUT_OF_MEMORY,
 * ::CUDA_ERROR_JIT_COMPILER_NOT_FOUND
 * \notefnerr
 *
 * \sa ::cuLinkAddData,
 * ::cuLinkAddFile,
 * ::cuLinkComplete,
 * ::cuLinkDestroy
 */
CUresult CUDAAPI
cuLinkCreate(unsigned int numOptions, CUjit_option *options, void **optionValues, CUlinkState *stateOut);

/**
 * \brief Add an input to a pending linker invocation
 *
 * Ownership of \p data is retained by the caller.  No reference is retained to any
 * inputs after this call returns.
 *
 * This method accepts only compiler options, which are used if the data must
 * be compiled from PTX, and does not accept any of
 * ::CU_JIT_WALL_TIME, ::CU_JIT_INFO_LOG_BUFFER, ::CU_JIT_ERROR_LOG_BUFFER,
 * ::CU_JIT_TARGET_FROM_CUCONTEXT, or ::CU_JIT_TARGET.
 *
 * \note For LTO-IR input, only LTO-IR compiled with toolkits prior to CUDA 12.0 will be accepted
 *
 * \param state        A pending linker action.
 * \param type         The type of the input data.
 * \param data         The input data.  PTX must be NULL-terminated.
 * \param size         The length of the input data.
 * \param name         An optional name for this input in log messages.
 * \param numOptions   Size of options.
 * \param options      Options to be applied only for this input (overrides options from ::cuLinkCreate).
 * \param optionValues Array of option values, each cast to void *.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_IMAGE,
 * ::CUDA_ERROR_INVALID_PTX,
 * ::CUDA_ERROR_UNSUPPORTED_PTX_VERSION,
 * ::CUDA_ERROR_OUT_OF_MEMORY,
 * ::CUDA_ERROR_NO_BINARY_FOR_GPU
 *
 * \sa ::cuLinkCreate,
 * ::cuLinkAddFile,
 * ::cuLinkComplete,
 * ::cuLinkDestroy
 */
CUresult CUDAAPI
cuLinkAddData(CUlinkState state, CUjitInputType type, void *data, size_t size, const char *name,
    unsigned int numOptions, CUjit_option *options, void **optionValues);

/**
 * \brief Add a file input to a pending linker invocation
 *
 * No reference is retained to any inputs after this call returns.
 *
 * This method accepts only compiler options, which are used if the input
 * must be compiled from PTX, and does not accept any of
 * ::CU_JIT_WALL_TIME, ::CU_JIT_INFO_LOG_BUFFER, ::CU_JIT_ERROR_LOG_BUFFER,
 * ::CU_JIT_TARGET_FROM_CUCONTEXT, or ::CU_JIT_TARGET.
 *
 * This method is equivalent to invoking ::cuLinkAddData on the contents
 * of the file.
 *
 * \note For LTO-IR input, only LTO-IR compiled with toolkits prior to CUDA 12.0 will be accepted
 *
 * \param state        A pending linker action
 * \param type         The type of the input data
 * \param path         Path to the input file
 * \param numOptions   Size of options
 * \param options      Options to be applied only for this input (overrides options from ::cuLinkCreate)
 * \param optionValues Array of option values, each cast to void *
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_FILE_NOT_FOUND
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_IMAGE,
 * ::CUDA_ERROR_INVALID_PTX,
 * ::CUDA_ERROR_UNSUPPORTED_PTX_VERSION,
 * ::CUDA_ERROR_OUT_OF_MEMORY,
 * ::CUDA_ERROR_NO_BINARY_FOR_GPU
 *
 * \sa ::cuLinkCreate,
 * ::cuLinkAddData,
 * ::cuLinkComplete,
 * ::cuLinkDestroy
 */
CUresult CUDAAPI
cuLinkAddFile(CUlinkState state, CUjitInputType type, const char *path,
    unsigned int numOptions, CUjit_option *options, void **optionValues);

/**
 * \brief Complete a pending linker invocation
 *
 * Completes the pending linker action and returns the cubin image for the linked
 * device code, which can be used with ::cuModuleLoadData.  The cubin is owned by
 * \p state, so it should be loaded before \p state is destroyed via ::cuLinkDestroy.
 * This call does not destroy \p state.
 *
 * \param state    A pending linker invocation
 * \param cubinOut On success, this will point to the output image
 * \param sizeOut  Optional parameter to receive the size of the generated image
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_OUT_OF_MEMORY
 *
 * \sa ::cuLinkCreate,
 * ::cuLinkAddData,
 * ::cuLinkAddFile,
 * ::cuLinkDestroy,
 * ::cuModuleLoadData
 */
CUresult CUDAAPI
cuLinkComplete(CUlinkState state, void **cubinOut, size_t *sizeOut);

/**
 * \brief Destroys state for a JIT linker invocation.
 *
 * \param state State object for the linker invocation
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_HANDLE
 *
 * \sa ::cuLinkCreate
 */
CUresult CUDAAPI
cuLinkDestroy(CUlinkState state);

/** @} */ /* END CUDA_MODULE */

/**
 * \defgroup CUDA_MODULE_DEPRECATED Module Management [DEPRECATED]
 *
 * ___MANBRIEF___ deprecated module management functions of the low-level CUDA
 * driver API (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the deprecated module management functions of the low-level
 * CUDA driver application programming interface.
 *
 * @{
 */

/**
 * \brief Returns a handle to a texture reference
 *
 * \deprecated
 *
 * Returns in \p *pTexRef the handle of the texture reference of name \p name
 * in the module \p hmod. If no texture reference of that name exists,
 * ::cuModuleGetTexRef() returns ::CUDA_ERROR_NOT_FOUND. This texture reference
 * handle should not be destroyed, since it will be destroyed when the module
 * is unloaded.
 *
 * \param pTexRef  - Returned texture reference
 * \param hmod     - Module to retrieve texture reference from
 * \param name     - Name of texture reference to retrieve
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_NOT_FOUND
 * \notefnerr
 *
 * \sa
 * ::cuModuleGetFunction,
 * ::cuModuleGetGlobal,
 * ::cuModuleGetSurfRef,
 * ::cuModuleLoad,
 * ::cuModuleLoadData,
 * ::cuModuleLoadDataEx,
 * ::cuModuleLoadFatBinary,
 * ::cuModuleUnload
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuModuleGetTexRef(CUtexref *pTexRef, CUmodule hmod, const char *name);

/**
 * \brief Returns a handle to a surface reference
 *
 * \deprecated
 *
 * Returns in \p *pSurfRef the handle of the surface reference of name \p name
 * in the module \p hmod. If no surface reference of that name exists,
 * ::cuModuleGetSurfRef() returns ::CUDA_ERROR_NOT_FOUND.
 *
 * \param pSurfRef  - Returned surface reference
 * \param hmod     - Module to retrieve surface reference from
 * \param name     - Name of surface reference to retrieve
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_NOT_FOUND
 * \notefnerr
 *
 * \sa
 * ::cuModuleGetFunction,
 * ::cuModuleGetGlobal,
 * ::cuModuleGetTexRef,
 * ::cuModuleLoad,
 * ::cuModuleLoadData,
 * ::cuModuleLoadDataEx,
 * ::cuModuleLoadFatBinary,
 * ::cuModuleUnload
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuModuleGetSurfRef(CUsurfref *pSurfRef, CUmodule hmod, const char *name);

/** @} */ /* END CUDA_MODULE_DEPRECATED */

/**
 * \defgroup CUDA_LIBRARY Library Management
 *
 * ___MANBRIEF___ library management functions of the low-level CUDA driver API
 * (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the library management functions of the low-level CUDA
 * driver application programming interface.
 *
 * @{
 */

/**
 * \brief Load a library with specified code and options
 *
 * Takes a pointer \p code and loads the corresponding library \p library based on
 * the application defined library loading mode:
 * - If module loading is set to EAGER, via the environment variables described in "Module loading",
 *   \p library is loaded eagerly into all contexts at the time of the call and future contexts
 *   at the time of creation until the library is unloaded with ::cuLibraryUnload().
 * - If the environment variables are set to LAZY, \p library
 *   is not immediately loaded onto all existent contexts and will only be
 *   loaded when a function is needed for that context, such as a kernel launch.
 *
 * These environment variables are described in the CUDA programming guide under the 
 * "CUDA environment variables" section.
 *
 * The \p code may be a \e cubin or \e fatbin as output by \b nvcc,
 * or a NULL-terminated \e PTX, either as output by \b nvcc or hand-written.
 * A fatbin should also contain relocatable code when doing separate compilation.
 *
 * Options are passed as an array via \p jitOptions and any corresponding parameters are passed in
 * \p jitOptionsValues. The number of total JIT options is supplied via \p numJitOptions.
 * Any outputs will be returned via \p jitOptionsValues.
 *
 * Library load options are passed as an array via \p libraryOptions and any corresponding parameters are passed in
 * \p libraryOptionValues. The number of total library load options is supplied via \p numLibraryOptions.
 *
 * \note If the library contains managed variables and no device in the system
 * supports managed variables this call is expected to return ::CUDA_ERROR_NOT_SUPPORTED
 *
 * \param library             - Returned library
 * \param code                - Code to load
 * \param jitOptions          - Options for JIT
 * \param jitOptionsValues    - Option values for JIT
 * \param numJitOptions       - Number of options
 * \param libraryOptions      - Options for loading
 * \param libraryOptionValues - Option values for loading
 * \param numLibraryOptions   - Number of options for loading
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_PTX,
 * ::CUDA_ERROR_UNSUPPORTED_PTX_VERSION,
 * ::CUDA_ERROR_OUT_OF_MEMORY,
 * ::CUDA_ERROR_NO_BINARY_FOR_GPU,
 * ::CUDA_ERROR_SHARED_OBJECT_SYMBOL_NOT_FOUND,
 * ::CUDA_ERROR_SHARED_OBJECT_INIT_FAILED,
 * ::CUDA_ERROR_JIT_COMPILER_NOT_FOUND,
 * ::CUDA_ERROR_NOT_SUPPORTED
 *
 * \sa ::cuLibraryLoadFromFile,
 * ::cuLibraryUnload,
 * ::cuModuleLoad,
 * ::cuModuleLoadData,
 * ::cuModuleLoadDataEx
 */
CUresult CUDAAPI cuLibraryLoadData(CUlibrary *library, const void *code,
                                   CUjit_option *jitOptions, void **jitOptionsValues, unsigned int numJitOptions,
                                   CUlibraryOption *libraryOptions, void** libraryOptionValues, unsigned int numLibraryOptions);

/**
 * \brief Load a library with specified file and options
 *
 * Takes a pointer \p code and loads the corresponding library \p library based on
 * the application defined library loading mode:
 * - If module loading is set to EAGER, via the environment variables described in "Module loading",
 *   \p library is loaded eagerly into all contexts at the time of the call and future contexts
 *   at the time of creation until the library is unloaded with ::cuLibraryUnload().
 * - If the environment variables are set to LAZY, \p library
 *   is not immediately loaded onto all existent contexts and will only be
 *   loaded when a function is needed for that context, such as a kernel launch.
 *
 * These environment variables are described in the CUDA programming guide under the 
 * "CUDA environment variables" section.
 *
 * The file should be a \e cubin file as output by \b nvcc, or a \e PTX file either
 * as output by \b nvcc or handwritten, or a \e fatbin file as output by \b nvcc.
 * A fatbin should also contain relocatable code when doing separate compilation.
 *
 * Options are passed as an array via \p jitOptions and any corresponding parameters are
 * passed in \p jitOptionsValues. The number of total options is supplied via \p numJitOptions.
 * Any outputs will be returned via \p jitOptionsValues.
 *
 * Library load options are passed as an array via \p libraryOptions and any corresponding parameters are passed in
 * \p libraryOptionValues. The number of total library load options is supplied via \p numLibraryOptions.
 *
 * \note If the library contains managed variables and no device in the system
 * supports managed variables this call is expected to return ::CUDA_ERROR_NOT_SUPPORTED
 *
 * \param library             - Returned library
 * \param fileName            - File to load from
 * \param jitOptions          - Options for JIT
 * \param jitOptionsValues    - Option values for JIT
 * \param numJitOptions       - Number of options
 * \param libraryOptions      - Options for loading
 * \param libraryOptionValues - Option values for loading
 * \param numLibraryOptions   - Number of options for loading
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_PTX,
 * ::CUDA_ERROR_UNSUPPORTED_PTX_VERSION,
 * ::CUDA_ERROR_OUT_OF_MEMORY,
 * ::CUDA_ERROR_NO_BINARY_FOR_GPU,
 * ::CUDA_ERROR_SHARED_OBJECT_SYMBOL_NOT_FOUND,
 * ::CUDA_ERROR_SHARED_OBJECT_INIT_FAILED,
 * ::CUDA_ERROR_JIT_COMPILER_NOT_FOUND,
 * ::CUDA_ERROR_NOT_SUPPORTED
 *
 * \sa ::cuLibraryLoadData,
 * ::cuLibraryUnload,
 * ::cuModuleLoad,
 * ::cuModuleLoadData,
 * ::cuModuleLoadDataEx
 */
CUresult CUDAAPI cuLibraryLoadFromFile(CUlibrary *library, const char *fileName,
                                       CUjit_option *jitOptions, void **jitOptionsValues, unsigned int numJitOptions,
                                       CUlibraryOption *libraryOptions, void **libraryOptionValues, unsigned int numLibraryOptions);

/**
 * \brief Unloads a library
 *
 * Unloads the library specified with \p library
 *
 * \param library - Library to unload
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa ::cuLibraryLoadData,
 * ::cuLibraryLoadFromFile,
 * ::cuModuleUnload
 */
CUresult CUDAAPI cuLibraryUnload(CUlibrary library);

/**
 * \brief Returns a kernel handle
 *
 * Returns in \p pKernel the handle of the kernel with name \p name located in library \p library.
 * If kernel handle is not found, the call returns ::CUDA_ERROR_NOT_FOUND.
 *
 * \param pKernel - Returned kernel handle
 * \param library - Library to retrieve kernel from
 * \param name - Name of kernel to retrieve
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_NOT_FOUND
 *
 * \sa ::cuLibraryLoadData,
 * ::cuLibraryLoadFromFile,
 * ::cuLibraryUnload,
 * ::cuKernelGetFunction,
 * ::cuLibraryGetModule,
 * ::cuModuleGetFunction
 */
CUresult CUDAAPI cuLibraryGetKernel(CUkernel *pKernel, CUlibrary library, const char *name);

/**
 * \brief Returns the number of kernels within a library
 *
 * Returns in \p count the number of kernels in \p lib.
 *
 * \param count - Number of kernels found within the library
 * \param lib - Library to query
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_INVALID_VALUE
 */
CUresult CUDAAPI cuLibraryGetKernelCount(unsigned int *count, CUlibrary lib);
 
/**
 * \brief Retrieve the kernel handles within a library.
 *
 * Returns in \p kernels a maximum number of \p numKernels kernel handles within \p lib.
 * The returned kernel handle becomes invalid when the library is unloaded.
 *
 * \param kernels - Buffer where the kernel handles are returned to
 * \param numKernels - Maximum number of kernel handles may be returned to the buffer
 * \param lib - Library to query from
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa ::cuLibraryGetKernelCount
 */
CUresult CUDAAPI cuLibraryEnumerateKernels(CUkernel *kernels, unsigned int numKernels, CUlibrary lib);

/**
 * \brief Returns a module handle
 *
 * Returns in \p pMod the module handle associated with the current context located in
 * library \p library. If module handle is not found, the call returns ::CUDA_ERROR_NOT_FOUND.
 *
 * \param pMod - Returned module handle
 * \param library - Library to retrieve module from
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_NOT_FOUND,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_CONTEXT_IS_DESTROYED
 *
 * \sa ::cuLibraryLoadData,
 * ::cuLibraryLoadFromFile,
 * ::cuLibraryUnload,
 * ::cuModuleGetFunction
 */
CUresult CUDAAPI cuLibraryGetModule(CUmodule *pMod, CUlibrary library);

/**
 * \brief Returns a function handle
 *
 * Returns in \p pFunc the handle of the function for the requested kernel \p kernel and
 * the current context. If function handle is not found, the call returns ::CUDA_ERROR_NOT_FOUND.
 *
 * \param pFunc - Returned function handle
 * \param kernel - Kernel to retrieve function for the requested context
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_NOT_FOUND,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_CONTEXT_IS_DESTROYED
 *
 * \sa ::cuLibraryLoadData,
 * ::cuLibraryLoadFromFile,
 * ::cuLibraryUnload,
 * ::cuLibraryGetKernel,
 * ::cuLibraryGetModule,
 * ::cuModuleGetFunction
 */
CUresult CUDAAPI cuKernelGetFunction(CUfunction *pFunc, CUkernel kernel);

/**
 * \brief Returns a library handle
 *
 * Returns in \p pLib the handle of the library for the requested kernel \p kernel
 *
 * \param pLib - Returned library handle
 * \param kernel - Kernel to retrieve library handle
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_NOT_FOUND
 *
 * \sa ::cuLibraryLoadData,
 * ::cuLibraryLoadFromFile,
 * ::cuLibraryUnload,
 * ::cuLibraryGetKernel
 */
CUresult CUDAAPI cuKernelGetLibrary(CUlibrary *pLib, CUkernel kernel);

/**
 * \brief Returns a global device pointer
 *
 * Returns in \p *dptr and \p *bytes the base pointer and size of the global with
 * name \p name for the requested library \p library and the current context.
 * If no global for the requested name \p name exists, the call returns ::CUDA_ERROR_NOT_FOUND.
 * One of the parameters \p dptr or \p bytes (not both) can be NULL in which
 * case it is ignored.
 *
 * \param dptr - Returned global device pointer for the requested context
 * \param bytes - Returned global size in bytes
 * \param library - Library to retrieve global from
 * \param name - Name of global to retrieve
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_NOT_FOUND,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_CONTEXT_IS_DESTROYED
 *
 * \sa ::cuLibraryLoadData,
 * ::cuLibraryLoadFromFile,
 * ::cuLibraryUnload,
 * ::cuLibraryGetModule,
 * cuModuleGetGlobal
 */
CUresult CUDAAPI cuLibraryGetGlobal(CUdeviceptr *dptr, size_t *bytes, CUlibrary library, const char *name);

/**
 * \brief Returns a pointer to managed memory
 *
 * Returns in \p *dptr and \p *bytes the base pointer and size of the managed memory with
 * name \p name for the requested library \p library. If no managed memory with the
 * requested name \p name exists, the call returns ::CUDA_ERROR_NOT_FOUND. One of the parameters
 * \p dptr or \p bytes (not both) can be NULL in which case it is ignored.
 * Note that managed memory for library \p library is shared across devices and is registered
 * when the library is loaded into atleast one context.
 *
 * \param dptr - Returned pointer to the managed memory
 * \param bytes - Returned memory size in bytes
 * \param library - Library to retrieve managed memory from
 * \param name - Name of managed memory to retrieve
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_NOT_FOUND
 *
 * \sa ::cuLibraryLoadData,
 * ::cuLibraryLoadFromFile,
 * ::cuLibraryUnload
 */
CUresult CUDAAPI cuLibraryGetManaged(CUdeviceptr *dptr, size_t *bytes, CUlibrary library, const char *name);

/**
 * \brief Returns a pointer to a unified function
 *
 * Returns in \p *fptr the function pointer to a unified function denoted by \p symbol.
 * If no unified function with name \p symbol exists, the call returns ::CUDA_ERROR_NOT_FOUND.
 * If there is no device with attribute ::CU_DEVICE_ATTRIBUTE_UNIFIED_FUNCTION_POINTERS present in the system,
 * the call may return ::CUDA_ERROR_NOT_FOUND.
 *
 * \param fptr - Returned pointer to a unified function
 * \param library - Library to retrieve function pointer memory from
 * \param symbol - Name of function pointer to retrieve
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_NOT_FOUND
 *
 * \sa ::cuLibraryLoadData,
 * ::cuLibraryLoadFromFile,
 * ::cuLibraryUnload
 */
CUresult CUDAAPI cuLibraryGetUnifiedFunction(void **fptr, CUlibrary library, const char *symbol);

/**
 * \brief Returns information about a kernel
 *
 * Returns in \p *pi the integer value of the attribute \p attrib for the kernel
 * \p kernel for the requested device \p dev. The supported attributes are:
 * - ::CU_FUNC_ATTRIBUTE_MAX_THREADS_PER_BLOCK: The maximum number of threads
 *   per block, beyond which a launch of the kernel would fail. This number
 *   depends on both the kernel and the requested device.
 * - ::CU_FUNC_ATTRIBUTE_SHARED_SIZE_BYTES: The size in bytes of
 *   statically-allocated shared memory per block required by this kernel.
 *   This does not include dynamically-allocated shared memory requested by
 *   the user at runtime.
 * - ::CU_FUNC_ATTRIBUTE_CONST_SIZE_BYTES: The size in bytes of user-allocated
 *   constant memory required by this kernel.
 * - ::CU_FUNC_ATTRIBUTE_LOCAL_SIZE_BYTES: The size in bytes of local memory
 *   used by each thread of this kernel.
 * - ::CU_FUNC_ATTRIBUTE_NUM_REGS: The number of registers used by each thread
 *   of this kernel.
 * - ::CU_FUNC_ATTRIBUTE_PTX_VERSION: The PTX virtual architecture version for
 *   which the kernel was compiled. This value is the major PTX version * 10
 *   + the minor PTX version, so a PTX version 1.3 function would return the
 *   value 13. Note that this may return the undefined value of 0 for cubins
 *   compiled prior to CUDA 3.0.
 * - ::CU_FUNC_ATTRIBUTE_BINARY_VERSION: The binary architecture version for
 *   which the kernel was compiled. This value is the major binary
 *   version * 10 + the minor binary version, so a binary version 1.3 function
 *   would return the value 13. Note that this will return a value of 10 for
 *   legacy cubins that do not have a properly-encoded binary architecture
 *   version.
 * - ::CU_FUNC_CACHE_MODE_CA: The attribute to indicate whether the kernel has
 *   been compiled with user specified option "-Xptxas --dlcm=ca" set.
 * - ::CU_FUNC_ATTRIBUTE_MAX_DYNAMIC_SHARED_SIZE_BYTES: The maximum size in bytes of
 *   dynamically-allocated shared memory.
 * - ::CU_FUNC_ATTRIBUTE_PREFERRED_SHARED_MEMORY_CARVEOUT: Preferred shared memory-L1
 *   cache split ratio in percent of total shared memory.
 * - ::CU_FUNC_ATTRIBUTE_CLUSTER_SIZE_MUST_BE_SET: If this attribute is set, the
 *   kernel must launch with a valid cluster size specified.
 * - ::CU_FUNC_ATTRIBUTE_REQUIRED_CLUSTER_WIDTH: The required cluster width in
 *   blocks.
 * - ::CU_FUNC_ATTRIBUTE_REQUIRED_CLUSTER_HEIGHT: The required cluster height in
 *   blocks.
 * - ::CU_FUNC_ATTRIBUTE_REQUIRED_CLUSTER_DEPTH: The required cluster depth in
 *   blocks.
 * - ::CU_FUNC_ATTRIBUTE_NON_PORTABLE_CLUSTER_SIZE_ALLOWED: Indicates whether
 *   the function can be launched with non-portable cluster size. 1 is allowed,
 *   0 is disallowed. A non-portable cluster size may only function on the
 *   specific SKUs the program is tested on. The launch might fail if the
 *   program is run on a different hardware platform. CUDA API provides
 *   cudaOccupancyMaxActiveClusters to assist with checking whether the desired
 *   size can be launched on the current device. A portable cluster size is
 *   guaranteed to be functional on all compute capabilities higher than the
 *   target compute capability. The portable cluster size for sm_90 is 8 blocks
 *   per cluster. This value may increase for future compute capabilities. The
 *   specific hardware unit may support higher cluster sizes that’s not
 *   guaranteed to be portable.
 * - ::CU_FUNC_ATTRIBUTE_CLUSTER_SCHEDULING_POLICY_PREFERENCE: The block
 *   scheduling policy of a function. The value type is CUclusterSchedulingPolicy.
 *
 * \note If another thread is trying to set the same attribute on the same device using
 * ::cuKernelSetAttribute() simultaneously, the attribute query will give the old or new
 * value depending on the interleavings chosen by the OS scheduler and memory consistency.
 *
 * \param pi     - Returned attribute value
 * \param attrib - Attribute requested
 * \param kernel  - Kernel to query attribute of
 * \param dev - Device to query attribute of
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_DEVICE
 *
 * \sa ::cuLibraryLoadData,
 * ::cuLibraryLoadFromFile,
 * ::cuLibraryUnload,
 * ::cuKernelSetAttribute,
 * ::cuLibraryGetKernel,
 * ::cuLaunchKernel,
 * ::cuKernelGetFunction,
 * ::cuLibraryGetModule,
 * ::cuModuleGetFunction,
 * ::cuFuncGetAttribute
 */
CUresult CUDAAPI cuKernelGetAttribute(int *pi, CUfunction_attribute attrib, CUkernel kernel, CUdevice dev);

/**
 * \brief Sets information about a kernel
 *
 * This call sets the value of a specified attribute \p attrib on the kernel \p kernel
 * for the requested device \p dev to an integer value specified by \p val.
 * This function returns CUDA_SUCCESS if the new value of the attribute could be
 * successfully set. If the set fails, this call will return an error.
 * Not all attributes can have values set. Attempting to set a value on a read-only
 * attribute will result in an error (CUDA_ERROR_INVALID_VALUE)
 *
 * Note that attributes set using ::cuFuncSetAttribute() will override the attribute
 * set by this API irrespective of whether the call to ::cuFuncSetAttribute() is made
 * before or after this API call. However, ::cuKernelGetAttribute() will always
 * return the attribute value set by this API.
 *
 * Supported attributes are:
 * - ::CU_FUNC_ATTRIBUTE_MAX_DYNAMIC_SHARED_SIZE_BYTES: This is the maximum size in bytes of
 *   dynamically-allocated shared memory. The value should contain the requested
 *   maximum size of dynamically-allocated shared memory. The sum of this value and
 *   the function attribute ::CU_FUNC_ATTRIBUTE_SHARED_SIZE_BYTES cannot exceed the
 *   device attribute ::CU_DEVICE_ATTRIBUTE_MAX_SHARED_MEMORY_PER_BLOCK_OPTIN.
 *   The maximal size of requestable dynamic shared memory may differ by GPU
 *   architecture.
 * - ::CU_FUNC_ATTRIBUTE_PREFERRED_SHARED_MEMORY_CARVEOUT: On devices where the L1
 *   cache and shared memory use the same hardware resources, this sets the shared memory
 *   carveout preference, in percent of the total shared memory.
 *   See ::CU_DEVICE_ATTRIBUTE_MAX_SHARED_MEMORY_PER_MULTIPROCESSOR
 *   This is only a hint, and the driver can choose a different ratio if required to execute the function.
 * - ::CU_FUNC_ATTRIBUTE_REQUIRED_CLUSTER_WIDTH: The required cluster width in
 *   blocks. The width, height, and depth values must either all be 0 or all be
 *   positive. The validity of the cluster dimensions is checked at launch time.
 *   If the value is set during compile time, it cannot be set at runtime.
 *   Setting it at runtime will return CUDA_ERROR_NOT_PERMITTED.
 * - ::CU_FUNC_ATTRIBUTE_REQUIRED_CLUSTER_HEIGHT: The required cluster height in
 *   blocks. The width, height, and depth values must either all be 0 or all be
 *   positive. The validity of the cluster dimensions is checked at launch time.
 *   If the value is set during compile time, it cannot be set at runtime.
 *   Setting it at runtime will return CUDA_ERROR_NOT_PERMITTED.
 * - ::CU_FUNC_ATTRIBUTE_REQUIRED_CLUSTER_DEPTH: The required cluster depth in
 *   blocks. The width, height, and depth values must either all be 0 or all be
 *   positive. The validity of the cluster dimensions is checked at launch time.
 *   If the value is set during compile time, it cannot be set at runtime.
 *   Setting it at runtime will return CUDA_ERROR_NOT_PERMITTED.
 * - ::CU_FUNC_ATTRIBUTE_NON_PORTABLE_CLUSTER_SIZE_ALLOWED: Indicates whether
 *   the function can be launched with non-portable cluster size. 1 is allowed,
 *   0 is disallowed.
 * - ::CU_FUNC_ATTRIBUTE_CLUSTER_SCHEDULING_POLICY_PREFERENCE: The block
 *   scheduling policy of a function. The value type is CUclusterSchedulingPolicy.
 *
 * \note The API has stricter locking requirements in comparison to its legacy counterpart
 * ::cuFuncSetAttribute() due to device-wide semantics. If multiple threads are trying to
 * set the same attribute on the same device simultaneously, the attribute setting will depend
 * on the interleavings chosen by the OS scheduler and memory consistency.
 *
 * \param attrib - Attribute requested
 * \param val - Value to set
 * \param kernel  - Kernel to set attribute of
 * \param dev - Device to set attribute of
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_DEVICE,
 * ::CUDA_ERROR_OUT_OF_MEMORY
 *
 * \sa ::cuLibraryLoadData,
 * ::cuLibraryLoadFromFile,
 * ::cuLibraryUnload,
 * ::cuKernelGetAttribute,
 * ::cuLibraryGetKernel,
 * ::cuLaunchKernel,
 * ::cuKernelGetFunction,
 * ::cuLibraryGetModule,
 * ::cuModuleGetFunction,
 * ::cuFuncSetAttribute
 */
CUresult CUDAAPI cuKernelSetAttribute(CUfunction_attribute attrib, int val, CUkernel kernel, CUdevice dev);

/**
 * \brief Sets the preferred cache configuration for a device kernel.
 *
 * On devices where the L1 cache and shared memory use the same hardware
 * resources, this sets through \p config the preferred cache configuration for
 * the device kernel \p kernel on the requested device \p dev. This is only a preference.
 * The driver will use the requested configuration if possible, but it is free to choose a different
 * configuration if required to execute \p kernel.  Any context-wide preference
 * set via ::cuCtxSetCacheConfig() will be overridden by this per-kernel
 * setting.
 *
 * Note that attributes set using ::cuFuncSetCacheConfig() will override the attribute
 * set by this API irrespective of whether the call to ::cuFuncSetCacheConfig() is made
 * before or after this API call.
 *
 * This setting does nothing on devices where the size of the L1 cache and
 * shared memory are fixed.
 *
 * Launching a kernel with a different preference than the most recent
 * preference setting may insert a device-side synchronization point.
 *
 *
 * The supported cache configurations are:
 * - ::CU_FUNC_CACHE_PREFER_NONE: no preference for shared memory or L1 (default)
 * - ::CU_FUNC_CACHE_PREFER_SHARED: prefer larger shared memory and smaller L1 cache
 * - ::CU_FUNC_CACHE_PREFER_L1: prefer larger L1 cache and smaller shared memory
 * - ::CU_FUNC_CACHE_PREFER_EQUAL: prefer equal sized L1 cache and shared memory
 *
 * \note The API has stricter locking requirements in comparison to its legacy counterpart
 * ::cuFuncSetCacheConfig() due to device-wide semantics. If multiple threads are trying to
 * set a config on the same device simultaneously, the cache config setting will depend
 * on the interleavings chosen by the OS scheduler and memory consistency.
 *
 * \param kernel  - Kernel to configure cache for
 * \param config - Requested cache configuration
 * \param dev - Device to set attribute of
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_DEVICE,
 * ::CUDA_ERROR_OUT_OF_MEMORY
 *
 * \sa ::cuLibraryLoadData,
 * ::cuLibraryLoadFromFile,
 * ::cuLibraryUnload,
 * ::cuLibraryGetKernel,
 * ::cuKernelGetFunction,
 * ::cuLibraryGetModule,
 * ::cuModuleGetFunction,
 * ::cuFuncSetCacheConfig,
 * ::cuCtxSetCacheConfig,
 * ::cuLaunchKernel
 */
CUresult CUDAAPI cuKernelSetCacheConfig(CUkernel kernel, CUfunc_cache config, CUdevice dev);

/**
 * \brief Returns the function name for a ::CUkernel handle
 *
 * Returns in \p **name the function name associated with the kernel handle \p hfunc .
 * The function name is returned as a null-terminated string. The returned name is only 
 * valid when the kernel handle is valid. If the library is unloaded or reloaded, one 
 * must call the API again to get the updated name. This API may return a mangled name if
 * the function is not declared as having C linkage. If either \p **name or \p hfunc 
 * is NULL, ::CUDA_ERROR_INVALID_VALUE is returned.
 *
 * \param name - The returned name of the function
 * \param hfunc - The function handle to retrieve the name for 
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 *
 */
CUresult CUDAAPI cuKernelGetName(const char **name, CUkernel hfunc);

/**
 * \brief Returns the offset and size of a kernel parameter in the device-side parameter layout
 *
 * Queries the kernel parameter at \p paramIndex into \p kernel's list of parameters, and returns
 * in \p paramOffset and \p paramSize the offset and size, respectively, where the parameter
 * will reside in the device-side parameter layout. This information can be used to update kernel
 * node parameters from the device via ::cudaGraphKernelNodeSetParam() and
 * ::cudaGraphKernelNodeUpdatesApply(). \p paramIndex must be less than the number of parameters
 * that \p kernel takes. \p paramSize can be set to NULL if only the parameter offset is desired.
 *
 * \param kernel      - The kernel to query
 * \param paramIndex  - The parameter index to query
 * \param paramOffset - Returns the offset into the device-side parameter layout at which the parameter resides
 * \param paramSize   - Optionally returns the size of the parameter in the device-side parameter layout
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * \notefnerr
 *
* \sa ::cuFuncGetParamInfo
 */
CUresult CUDAAPI cuKernelGetParamInfo(CUkernel kernel, size_t paramIndex, size_t *paramOffset, size_t *paramSize);
/** @} */ /* END CUDA_LIBRARY */

/**
 * \defgroup CUDA_MEM Memory Management
 *
 * ___MANBRIEF___ memory management functions of the low-level CUDA driver API
 * (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the memory management functions of the low-level CUDA
 * driver application programming interface.
 *
 * @{
 */

/**
 * \brief Gets free and total memory
 *
 * Returns in \p *total the total amount of memory available to the the current context.
 * Returns in \p *free the amount of memory on the device that is free according to the OS.
 * CUDA is not guaranteed to be able to allocate all of the memory that the OS reports as free.
 * In a multi-tenet situation, free estimate returned is prone to race condition where
 * a new allocation/free done by a different process or a different thread in the same
 * process between the time when free memory was estimated and reported, will result in
 * deviation in free value reported and actual free memory.
 *
 * The integrated GPU on Tegra shares memory with CPU and other component
 * of the SoC. The free and total values returned by the API excludes
 * the SWAP memory space maintained by the OS on some platforms.
 * The OS may move some of the memory pages into swap area as the GPU or
 * CPU allocate or access memory. See Tegra app note on how to calculate
 * total and free memory on Tegra.
 *
 * \param free  - Returned free memory in bytes
 * \param total - Returned total memory in bytes
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 *
 * \sa ::cuArray3DCreate, ::cuArray3DGetDescriptor, ::cuArrayCreate,
 * ::cuArrayDestroy, ::cuArrayGetDescriptor, ::cuMemAlloc, ::cuMemAllocHost,
 * ::cuMemAllocPitch, ::cuMemcpy2D, ::cuMemcpy2DAsync, ::cuMemcpy2DUnaligned,
 * ::cuMemcpy3D, ::cuMemcpy3DAsync, ::cuMemcpyAtoA, ::cuMemcpyAtoD,
 * ::cuMemcpyAtoH, ::cuMemcpyAtoHAsync, ::cuMemcpyDtoA, ::cuMemcpyDtoD, ::cuMemcpyDtoDAsync,
 * ::cuMemcpyDtoH, ::cuMemcpyDtoHAsync, ::cuMemcpyHtoA, ::cuMemcpyHtoAAsync,
 * ::cuMemcpyHtoD, ::cuMemcpyHtoDAsync, ::cuMemFree, ::cuMemFreeHost,
 * ::cuMemGetAddressRange, ::cuMemHostAlloc,
 * ::cuMemHostGetDevicePointer, ::cuMemsetD2D8, ::cuMemsetD2D16,
 * ::cuMemsetD2D32, ::cuMemsetD8, ::cuMemsetD16, ::cuMemsetD32,
 * ::cudaMemGetInfo
 */
CUresult CUDAAPI cuMemGetInfo(size_t *free, size_t *total);

/**
 * \brief Allocates device memory
 *
 * Allocates \p bytesize bytes of linear memory on the device and returns in
 * \p *dptr a pointer to the allocated memory. The allocated memory is suitably
 * aligned for any kind of variable. The memory is not cleared. If \p bytesize
 * is 0, ::cuMemAlloc() returns ::CUDA_ERROR_INVALID_VALUE.
 *
 * \param dptr     - Returned device pointer
 * \param bytesize - Requested allocation size in bytes
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_OUT_OF_MEMORY
 * \notefnerr
 *
 * \sa ::cuArray3DCreate, ::cuArray3DGetDescriptor, ::cuArrayCreate,
 * ::cuArrayDestroy, ::cuArrayGetDescriptor, ::cuMemAllocHost,
 * ::cuMemAllocPitch, ::cuMemcpy2D, ::cuMemcpy2DAsync, ::cuMemcpy2DUnaligned,
 * ::cuMemcpy3D, ::cuMemcpy3DAsync, ::cuMemcpyAtoA, ::cuMemcpyAtoD,
 * ::cuMemcpyAtoH, ::cuMemcpyAtoHAsync, ::cuMemcpyDtoA, ::cuMemcpyDtoD, ::cuMemcpyDtoDAsync,
 * ::cuMemcpyDtoH, ::cuMemcpyDtoHAsync, ::cuMemcpyHtoA, ::cuMemcpyHtoAAsync,
 * ::cuMemcpyHtoD, ::cuMemcpyHtoDAsync, ::cuMemFree, ::cuMemFreeHost,
 * ::cuMemGetAddressRange, ::cuMemGetInfo, ::cuMemHostAlloc,
 * ::cuMemHostGetDevicePointer, ::cuMemsetD2D8, ::cuMemsetD2D16,
 * ::cuMemsetD2D32, ::cuMemsetD8, ::cuMemsetD16, ::cuMemsetD32,
 * ::cudaMalloc
 */
CUresult CUDAAPI cuMemAlloc(CUdeviceptr *dptr, size_t bytesize);

/**
 * \brief Allocates pitched device memory
 *
 * Allocates at least \p WidthInBytes * \p Height bytes of linear memory on
 * the device and returns in \p *dptr a pointer to the allocated memory. The
 * function may pad the allocation to ensure that corresponding pointers in
 * any given row will continue to meet the alignment requirements for
 * coalescing as the address is updated from row to row. \p ElementSizeBytes
 * specifies the size of the largest reads and writes that will be performed
 * on the memory range. \p ElementSizeBytes may be 4, 8 or 16 (since coalesced
 * memory transactions are not possible on other data sizes). If
 * \p ElementSizeBytes is smaller than the actual read/write size of a kernel,
 * the kernel will run correctly, but possibly at reduced speed. The pitch
 * returned in \p *pPitch by ::cuMemAllocPitch() is the width in bytes of the
 * allocation. The intended usage of pitch is as a separate parameter of the
 * allocation, used to compute addresses within the 2D array. Given the row
 * and column of an array element of type \b T, the address is computed as:
 * \code
   T* pElement = (T*)((char*)BaseAddress + Row * Pitch) + Column;
 * \endcode
 *
 * The pitch returned by ::cuMemAllocPitch() is guaranteed to work with
 * ::cuMemcpy2D() under all circumstances. For allocations of 2D arrays, it is
 * recommended that programmers consider performing pitch allocations using
 * ::cuMemAllocPitch(). Due to alignment restrictions in the hardware, this is
 * especially true if the application will be performing 2D memory copies
 * between different regions of device memory (whether linear memory or CUDA
 * arrays).
 *
 * The byte alignment of the pitch returned by ::cuMemAllocPitch() is guaranteed
 * to match or exceed the alignment requirement for texture binding with
 * ::cuTexRefSetAddress2D().
 *
 * \param dptr             - Returned device pointer
 * \param pPitch           - Returned pitch of allocation in bytes
 * \param WidthInBytes     - Requested allocation width in bytes
 * \param Height           - Requested allocation height in rows
 * \param ElementSizeBytes - Size of largest reads/writes for range
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_OUT_OF_MEMORY
 * \notefnerr
 *
 * \sa ::cuArray3DCreate, ::cuArray3DGetDescriptor, ::cuArrayCreate,
 * ::cuArrayDestroy, ::cuArrayGetDescriptor, ::cuMemAlloc, ::cuMemAllocHost,
 * ::cuMemcpy2D, ::cuMemcpy2DAsync, ::cuMemcpy2DUnaligned,
 * ::cuMemcpy3D, ::cuMemcpy3DAsync, ::cuMemcpyAtoA, ::cuMemcpyAtoD,
 * ::cuMemcpyAtoH, ::cuMemcpyAtoHAsync, ::cuMemcpyDtoA, ::cuMemcpyDtoD, ::cuMemcpyDtoDAsync,
 * ::cuMemcpyDtoH, ::cuMemcpyDtoHAsync, ::cuMemcpyHtoA, ::cuMemcpyHtoAAsync,
 * ::cuMemcpyHtoD, ::cuMemcpyHtoDAsync, ::cuMemFree, ::cuMemFreeHost,
 * ::cuMemGetAddressRange, ::cuMemGetInfo, ::cuMemHostAlloc,
 * ::cuMemHostGetDevicePointer, ::cuMemsetD2D8, ::cuMemsetD2D16,
 * ::cuMemsetD2D32, ::cuMemsetD8, ::cuMemsetD16, ::cuMemsetD32,
 * ::cudaMallocPitch
 */
CUresult CUDAAPI cuMemAllocPitch(CUdeviceptr *dptr, size_t *pPitch, size_t WidthInBytes, size_t Height, unsigned int ElementSizeBytes);

/**
 * \brief Frees device memory
 *
 * Frees the memory space pointed to by \p dptr, which must have been returned
 * by a previous call to one of the following memory allocation APIs - ::cuMemAlloc(), 
 * ::cuMemAllocPitch(), ::cuMemAllocManaged(), ::cuMemAllocAsync(), ::cuMemAllocFromPoolAsync()
 *
 * Note - This API will not perform any implict synchronization when the pointer was allocated with
 * ::cuMemAllocAsync or ::cuMemAllocFromPoolAsync. Callers must ensure that all accesses to these
 * pointer have completed before invoking ::cuMemFree. For best performance and memory reuse, users
 * should use ::cuMemFreeAsync to free memory allocated via the stream ordered memory allocator.
 * For all other pointers, this API may perform implicit synchronization.
 * 
 * \param dptr - Pointer to memory to free
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 *
 * \sa ::cuArray3DCreate, ::cuArray3DGetDescriptor, ::cuArrayCreate,
 * ::cuArrayDestroy, ::cuArrayGetDescriptor, ::cuMemAlloc, ::cuMemAllocHost,
 * ::cuMemAllocPitch, ::cuMemAllocManaged, ::cuMemAllocAsync, ::cuMemAllocFromPoolAsync, 
 * ::cuMemcpy2D, ::cuMemcpy2DAsync, ::cuMemcpy2DUnaligned, ::cuMemcpy3D, ::cuMemcpy3DAsync,
 * ::cuMemcpyAtoA, ::cuMemcpyAtoD, ::cuMemcpyAtoH, ::cuMemcpyAtoHAsync, ::cuMemcpyDtoA,
 * ::cuMemcpyDtoD, ::cuMemcpyDtoDAsync, ::cuMemcpyDtoH, ::cuMemcpyDtoHAsync, ::cuMemcpyHtoA,
 * ::cuMemcpyHtoAAsync, ::cuMemcpyHtoD, ::cuMemcpyHtoDAsync, ::cuMemFreeHost,
 * ::cuMemGetAddressRange, ::cuMemGetInfo, ::cuMemHostAlloc, ::cuMemFreeAsync,
 * ::cuMemHostGetDevicePointer, ::cuMemsetD2D8, ::cuMemsetD2D16,
 * ::cuMemsetD2D32, ::cuMemsetD8, ::cuMemsetD16, ::cuMemsetD32,
 * ::cudaFree
 */
CUresult CUDAAPI cuMemFree(CUdeviceptr dptr);

/**
 * \brief Get information on memory allocations
 *
 * Returns the base address in \p *pbase and size in \p *psize of the
 * allocation by ::cuMemAlloc() or ::cuMemAllocPitch() that contains the input
 * pointer \p dptr. Both parameters \p pbase and \p psize are optional. If one
 * of them is NULL, it is ignored.
 *
 * \param pbase - Returned base address
 * \param psize - Returned size of device memory allocation
 * \param dptr  - Device pointer to query
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_NOT_FOUND,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 *
 * \sa ::cuArray3DCreate, ::cuArray3DGetDescriptor, ::cuArrayCreate,
 * ::cuArrayDestroy, ::cuArrayGetDescriptor, ::cuMemAlloc, ::cuMemAllocHost,
 * ::cuMemAllocPitch, ::cuMemcpy2D, ::cuMemcpy2DAsync, ::cuMemcpy2DUnaligned,
 * ::cuMemcpy3D, ::cuMemcpy3DAsync, ::cuMemcpyAtoA, ::cuMemcpyAtoD,
 * ::cuMemcpyAtoH, ::cuMemcpyAtoHAsync, ::cuMemcpyDtoA, ::cuMemcpyDtoD, ::cuMemcpyDtoDAsync,
 * ::cuMemcpyDtoH, ::cuMemcpyDtoHAsync, ::cuMemcpyHtoA, ::cuMemcpyHtoAAsync,
 * ::cuMemcpyHtoD, ::cuMemcpyHtoDAsync, ::cuMemFree, ::cuMemFreeHost,
 * ::cuMemGetInfo, ::cuMemHostAlloc,
 * ::cuMemHostGetDevicePointer, ::cuMemsetD2D8, ::cuMemsetD2D16,
 * ::cuMemsetD2D32, ::cuMemsetD8, ::cuMemsetD16, ::cuMemsetD32
 */
CUresult CUDAAPI cuMemGetAddressRange(CUdeviceptr *pbase, size_t *psize, CUdeviceptr dptr);

/**
 * \brief Allocates page-locked host memory
 *
 * Allocates \p bytesize bytes of host memory that is page-locked and
 * accessible to the device. The driver tracks the virtual memory ranges
 * allocated with this function and automatically accelerates calls to
 * functions such as ::cuMemcpy(). Since the memory can be accessed directly by
 * the device, it can be read or written with much higher bandwidth than
 * pageable memory obtained with functions such as ::malloc(). 
 *
 * On systems where ::CU_DEVICE_ATTRIBUTE_PAGEABLE_MEMORY_ACCESS_USES_HOST_PAGE_TABLES 
 * is true, ::cuMemAllocHost may not page-lock the allocated memory.
 *
 * Page-locking excessive amounts of memory with ::cuMemAllocHost() may degrade system
 * performance, since it reduces the amount of memory available to the system
 * for paging. As a result, this function is best used sparingly to allocate
 * staging areas for data exchange between host and device.
 *
 * Note all host memory allocated using ::cuMemAllocHost() will automatically
 * be immediately accessible to all contexts on all devices which support unified
 * addressing (as may be queried using ::CU_DEVICE_ATTRIBUTE_UNIFIED_ADDRESSING).
 * The device pointer that may be used to access this host memory from those
 * contexts is always equal to the returned host pointer \p *pp.
 * See \ref CUDA_UNIFIED for additional details.
 *
 * \param pp       - Returned pointer to host memory
 * \param bytesize - Requested allocation size in bytes
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_OUT_OF_MEMORY
 * \notefnerr
 *
 * \sa ::cuArray3DCreate, ::cuArray3DGetDescriptor, ::cuArrayCreate,
 * ::cuArrayDestroy, ::cuArrayGetDescriptor, ::cuMemAlloc,
 * ::cuMemAllocPitch, ::cuMemcpy2D, ::cuMemcpy2DAsync, ::cuMemcpy2DUnaligned,
 * ::cuMemcpy3D, ::cuMemcpy3DAsync, ::cuMemcpyAtoA, ::cuMemcpyAtoD,
 * ::cuMemcpyAtoH, ::cuMemcpyAtoHAsync, ::cuMemcpyDtoA, ::cuMemcpyDtoD, ::cuMemcpyDtoDAsync,
 * ::cuMemcpyDtoH, ::cuMemcpyDtoHAsync, ::cuMemcpyHtoA, ::cuMemcpyHtoAAsync,
 * ::cuMemcpyHtoD, ::cuMemcpyHtoDAsync, ::cuMemFree, ::cuMemFreeHost,
 * ::cuMemGetAddressRange, ::cuMemGetInfo, ::cuMemHostAlloc,
 * ::cuMemHostGetDevicePointer, ::cuMemsetD2D8, ::cuMemsetD2D16,
 * ::cuMemsetD2D32, ::cuMemsetD8, ::cuMemsetD16, ::cuMemsetD32,
 * ::cudaMallocHost
 */
CUresult CUDAAPI cuMemAllocHost(void **pp, size_t bytesize);

/**
 * \brief Frees page-locked host memory
 *
 * Frees the memory space pointed to by \p p, which must have been returned by
 * a previous call to ::cuMemAllocHost().
 *
 * \param p - Pointer to memory to free
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 *
 * \sa ::cuArray3DCreate, ::cuArray3DGetDescriptor, ::cuArrayCreate,
 * ::cuArrayDestroy, ::cuArrayGetDescriptor, ::cuMemAlloc, ::cuMemAllocHost,
 * ::cuMemAllocPitch, ::cuMemcpy2D, ::cuMemcpy2DAsync, ::cuMemcpy2DUnaligned,
 * ::cuMemcpy3D, ::cuMemcpy3DAsync, ::cuMemcpyAtoA, ::cuMemcpyAtoD,
 * ::cuMemcpyAtoH, ::cuMemcpyAtoHAsync, ::cuMemcpyDtoA, ::cuMemcpyDtoD, ::cuMemcpyDtoDAsync,
 * ::cuMemcpyDtoH, ::cuMemcpyDtoHAsync, ::cuMemcpyHtoA, ::cuMemcpyHtoAAsync,
 * ::cuMemcpyHtoD, ::cuMemcpyHtoDAsync, ::cuMemFree,
 * ::cuMemGetAddressRange, ::cuMemGetInfo, ::cuMemHostAlloc,
 * ::cuMemHostGetDevicePointer, ::cuMemsetD2D8, ::cuMemsetD2D16,
 * ::cuMemsetD2D32, ::cuMemsetD8, ::cuMemsetD16, ::cuMemsetD32,
 * ::cudaFreeHost
 */
CUresult CUDAAPI cuMemFreeHost(void *p);

/**
 * \brief Allocates page-locked host memory
 *
 * Allocates \p bytesize bytes of host memory that is page-locked and accessible
 * to the device. The driver tracks the virtual memory ranges allocated with
 * this function and automatically accelerates calls to functions such as
 * ::cuMemcpyHtoD(). Since the memory can be accessed directly by the device,
 * it can be read or written with much higher bandwidth than pageable memory
 * obtained with functions such as ::malloc(). 
 *
 * On systems where ::CU_DEVICE_ATTRIBUTE_PAGEABLE_MEMORY_ACCESS_USES_HOST_PAGE_TABLES 
 * is true, ::cuMemHostAlloc may not page-lock the allocated memory.
 *
 * Page-locking excessive amounts of memory may degrade system performance, 
 * since it reduces the amount of memory available to the system for paging. 
 * As a result, this function is best used sparingly to allocate staging areas 
 * for data exchange between host and device.
 *
 * The \p Flags parameter enables different options to be specified that
 * affect the allocation, as follows.
 *
 * - ::CU_MEMHOSTALLOC_PORTABLE: The memory returned by this call will be
 *   considered as pinned memory by all CUDA contexts, not just the one that
 *   performed the allocation.
 *
 * - ::CU_MEMHOSTALLOC_DEVICEMAP: Maps the allocation into the CUDA address
 *   space. The device pointer to the memory may be obtained by calling
 *   ::cuMemHostGetDevicePointer().
 *
 * - ::CU_MEMHOSTALLOC_WRITECOMBINED: Allocates the memory as write-combined
 *   (WC). WC memory can be transferred across the PCI Express bus more
 *   quickly on some system configurations, but cannot be read efficiently by
 *   most CPUs. WC memory is a good option for buffers that will be written by
 *   the CPU and read by the GPU via mapped pinned memory or host->device
 *   transfers.
 *
 * All of these flags are orthogonal to one another: a developer may allocate
 * memory that is portable, mapped and/or write-combined with no restrictions.
 *
 * The ::CU_MEMHOSTALLOC_DEVICEMAP flag may be specified on CUDA contexts for
 * devices that do not support mapped pinned memory. The failure is deferred
 * to ::cuMemHostGetDevicePointer() because the memory may be mapped into
 * other CUDA contexts via the ::CU_MEMHOSTALLOC_PORTABLE flag.
 *
 * The memory allocated by this function must be freed with ::cuMemFreeHost().
 *
 * Note all host memory allocated using ::cuMemHostAlloc() will automatically
 * be immediately accessible to all contexts on all devices which support unified
 * addressing (as may be queried using ::CU_DEVICE_ATTRIBUTE_UNIFIED_ADDRESSING).
 * Unless the flag ::CU_MEMHOSTALLOC_WRITECOMBINED is specified, the device pointer
 * that may be used to access this host memory from those contexts is always equal
 * to the returned host pointer \p *pp.  If the flag ::CU_MEMHOSTALLOC_WRITECOMBINED
 * is specified, then the function ::cuMemHostGetDevicePointer() must be used
 * to query the device pointer, even if the context supports unified addressing.
 * See \ref CUDA_UNIFIED for additional details.
 *
 * \param pp       - Returned pointer to host memory
 * \param bytesize - Requested allocation size in bytes
 * \param Flags    - Flags for allocation request
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_OUT_OF_MEMORY
 * \notefnerr
 *
 * \sa ::cuArray3DCreate, ::cuArray3DGetDescriptor, ::cuArrayCreate,
 * ::cuArrayDestroy, ::cuArrayGetDescriptor, ::cuMemAlloc, ::cuMemAllocHost,
 * ::cuMemAllocPitch, ::cuMemcpy2D, ::cuMemcpy2DAsync, ::cuMemcpy2DUnaligned,
 * ::cuMemcpy3D, ::cuMemcpy3DAsync, ::cuMemcpyAtoA, ::cuMemcpyAtoD,
 * ::cuMemcpyAtoH, ::cuMemcpyAtoHAsync, ::cuMemcpyDtoA, ::cuMemcpyDtoD, ::cuMemcpyDtoDAsync,
 * ::cuMemcpyDtoH, ::cuMemcpyDtoHAsync, ::cuMemcpyHtoA, ::cuMemcpyHtoAAsync,
 * ::cuMemcpyHtoD, ::cuMemcpyHtoDAsync, ::cuMemFree, ::cuMemFreeHost,
 * ::cuMemGetAddressRange, ::cuMemGetInfo,
 * ::cuMemHostGetDevicePointer, ::cuMemsetD2D8, ::cuMemsetD2D16,
 * ::cuMemsetD2D32, ::cuMemsetD8, ::cuMemsetD16, ::cuMemsetD32,
 * ::cudaHostAlloc
 */
CUresult CUDAAPI cuMemHostAlloc(void **pp, size_t bytesize, unsigned int Flags);

/**
 * \brief Passes back device pointer of mapped pinned memory
 *
 * Passes back the device pointer \p pdptr corresponding to the mapped, pinned
 * host buffer \p p allocated by ::cuMemHostAlloc.
 *
 * ::cuMemHostGetDevicePointer() will fail if the ::CU_MEMHOSTALLOC_DEVICEMAP
 * flag was not specified at the time the memory was allocated, or if the
 * function is called on a GPU that does not support mapped pinned memory.
 *
 * For devices that have a non-zero value for the device attribute
 * ::CU_DEVICE_ATTRIBUTE_CAN_USE_HOST_POINTER_FOR_REGISTERED_MEM, the memory
 * can also be accessed from the device using the host pointer \p p.
 * The device pointer returned by ::cuMemHostGetDevicePointer() may or may not
 * match the original host pointer \p p and depends on the devices visible to the
 * application. If all devices visible to the application have a non-zero value for the
 * device attribute, the device pointer returned by ::cuMemHostGetDevicePointer()
 * will match the original pointer \p p. If any device visible to the application
 * has a zero value for the device attribute, the device pointer returned by
 * ::cuMemHostGetDevicePointer() will not match the original host pointer \p p,
 * but it will be suitable for use on all devices provided Unified Virtual Addressing
 * is enabled. In such systems, it is valid to access the memory using either pointer
 * on devices that have a non-zero value for the device attribute. Note however that
 * such devices should access the memory using only one of the two pointers and not both.
 *
 * \p Flags provides for future releases. For now, it must be set to 0.
 *
 * \param pdptr - Returned device pointer
 * \param p     - Host pointer
 * \param Flags - Options (must be 0)
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 *
 * \sa ::cuArray3DCreate, ::cuArray3DGetDescriptor, ::cuArrayCreate,
 * ::cuArrayDestroy, ::cuArrayGetDescriptor, ::cuMemAlloc, ::cuMemAllocHost,
 * ::cuMemAllocPitch, ::cuMemcpy2D, ::cuMemcpy2DAsync, ::cuMemcpy2DUnaligned,
 * ::cuMemcpy3D, ::cuMemcpy3DAsync, ::cuMemcpyAtoA, ::cuMemcpyAtoD,
 * ::cuMemcpyAtoH, ::cuMemcpyAtoHAsync, ::cuMemcpyDtoA, ::cuMemcpyDtoD, ::cuMemcpyDtoDAsync,
 * ::cuMemcpyDtoH, ::cuMemcpyDtoHAsync, ::cuMemcpyHtoA, ::cuMemcpyHtoAAsync,
 * ::cuMemcpyHtoD, ::cuMemcpyHtoDAsync, ::cuMemFree, ::cuMemFreeHost,
 * ::cuMemGetAddressRange, ::cuMemGetInfo, ::cuMemHostAlloc,
 * ::cuMemsetD2D8, ::cuMemsetD2D16,
 * ::cuMemsetD2D32, ::cuMemsetD8, ::cuMemsetD16, ::cuMemsetD32,
 * ::cudaHostGetDevicePointer
 */
CUresult CUDAAPI cuMemHostGetDevicePointer(CUdeviceptr *pdptr, void *p, unsigned int Flags);

/**
 * \brief Passes back flags that were used for a pinned allocation
 *
 * Passes back the flags \p pFlags that were specified when allocating
 * the pinned host buffer \p p allocated by ::cuMemHostAlloc.
 *
 * ::cuMemHostGetFlags() will fail if the pointer does not reside in
 * an allocation performed by ::cuMemAllocHost() or ::cuMemHostAlloc().
 *
 * \param pFlags - Returned flags word
 * \param p     - Host pointer
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 *
 * \sa
 * ::cuMemAllocHost,
 * ::cuMemHostAlloc,
 * ::cudaHostGetFlags
 */
CUresult CUDAAPI cuMemHostGetFlags(unsigned int *pFlags, void *p);

/**
 * \brief Allocates memory that will be automatically managed by the Unified Memory system
 *
 * Allocates \p bytesize bytes of managed memory on the device and returns in
 * \p *dptr a pointer to the allocated memory. If the device doesn't support
 * allocating managed memory, ::CUDA_ERROR_NOT_SUPPORTED is returned. Support
 * for managed memory can be queried using the device attribute
 * ::CU_DEVICE_ATTRIBUTE_MANAGED_MEMORY. The allocated memory is suitably
 * aligned for any kind of variable. The memory is not cleared. If \p bytesize
 * is 0, ::cuMemAllocManaged returns ::CUDA_ERROR_INVALID_VALUE. The pointer
 * is valid on the CPU and on all GPUs in the system that support managed memory.
 * All accesses to this pointer must obey the Unified Memory programming model.
 *
 * \p flags specifies the default stream association for this allocation.
 * \p flags must be one of ::CU_MEM_ATTACH_GLOBAL or ::CU_MEM_ATTACH_HOST. If
 * ::CU_MEM_ATTACH_GLOBAL is specified, then this memory is accessible from
 * any stream on any device. If ::CU_MEM_ATTACH_HOST is specified, then the
 * allocation should not be accessed from devices that have a zero value for the
 * device attribute ::CU_DEVICE_ATTRIBUTE_CONCURRENT_MANAGED_ACCESS; an explicit call to
 * ::cuStreamAttachMemAsync will be required to enable access on such devices.
 *
 * If the association is later changed via ::cuStreamAttachMemAsync to
 * a single stream, the default association as specified during ::cuMemAllocManaged
 * is restored when that stream is destroyed. For __managed__ variables, the
 * default association is always ::CU_MEM_ATTACH_GLOBAL. Note that destroying a
 * stream is an asynchronous operation, and as a result, the change to default
 * association won't happen until all work in the stream has completed.
 *
 * Memory allocated with ::cuMemAllocManaged should be released with ::cuMemFree.
 *
 * Device memory oversubscription is possible for GPUs that have a non-zero value for the
 * device attribute ::CU_DEVICE_ATTRIBUTE_CONCURRENT_MANAGED_ACCESS. Managed memory on
 * such GPUs may be evicted from device memory to host memory at any time by the Unified
 * Memory driver in order to make room for other allocations.
 *
 * In a system where all GPUs have a non-zero value for the device attribute
 * ::CU_DEVICE_ATTRIBUTE_CONCURRENT_MANAGED_ACCESS, managed memory may not be populated when this
 * API returns and instead may be populated on access. In such systems, managed memory can
 * migrate to any processor's memory at any time. The Unified Memory driver will employ heuristics to
 * maintain data locality and prevent excessive page faults to the extent possible. The application
 * can also guide the driver about memory usage patterns via ::cuMemAdvise. The application
 * can also explicitly migrate memory to a desired processor's memory via
 * ::cuMemPrefetchAsync.
 *
 * In a multi-GPU system where all of the GPUs have a zero value for the device attribute
 * ::CU_DEVICE_ATTRIBUTE_CONCURRENT_MANAGED_ACCESS and all the GPUs have peer-to-peer support
 * with each other, the physical storage for managed memory is created on the GPU which is active
 * at the time ::cuMemAllocManaged is called. All other GPUs will reference the data at reduced
 * bandwidth via peer mappings over the PCIe bus. The Unified Memory driver does not migrate
 * memory among such GPUs.
 *
 * In a multi-GPU system where not all GPUs have peer-to-peer support with each other and
 * where the value of the device attribute ::CU_DEVICE_ATTRIBUTE_CONCURRENT_MANAGED_ACCESS
 * is zero for at least one of those GPUs, the location chosen for physical storage of managed
 * memory is system-dependent.
 * - On Linux, the location chosen will be device memory as long as the current set of active
 * contexts are on devices that either have peer-to-peer support with each other or have a
 * non-zero value for the device attribute ::CU_DEVICE_ATTRIBUTE_CONCURRENT_MANAGED_ACCESS.
 * If there is an active context on a GPU that does not have a non-zero value for that device
 * attribute and it does not have peer-to-peer support with the other devices that have active
 * contexts on them, then the location for physical storage will be 'zero-copy' or host memory.
 * Note that this means that managed memory that is located in device memory is migrated to
 * host memory if a new context is created on a GPU that doesn't have a non-zero value for
 * the device attribute and does not support peer-to-peer with at least one of the other devices
 * that has an active context. This in turn implies that context creation may fail if there is
 * insufficient host memory to migrate all managed allocations.
 * - On Windows, the physical storage is always created in 'zero-copy' or host memory.
 * All GPUs will reference the data at reduced bandwidth over the PCIe bus. In these
 * circumstances, use of the environment variable CUDA_VISIBLE_DEVICES is recommended to
 * restrict CUDA to only use those GPUs that have peer-to-peer support.
 * Alternatively, users can also set CUDA_MANAGED_FORCE_DEVICE_ALLOC to a
 * non-zero value to force the driver to always use device memory for physical storage.
 * When this environment variable is set to a non-zero value, all contexts created in
 * that process on devices that support managed memory have to be peer-to-peer compatible
 * with each other. Context creation will fail if a context is created on a device that
 * supports managed memory and is not peer-to-peer compatible with any of the other
 * managed memory supporting devices on which contexts were previously created, even if
 * those contexts have been destroyed. These environment variables are described
 * in the CUDA programming guide under the "CUDA environment variables" section.
 * - On ARM, managed memory is not available on discrete gpu with Drive PX-2.
 *
 * \param dptr     - Returned device pointer
 * \param bytesize - Requested allocation size in bytes
 * \param flags    - Must be one of ::CU_MEM_ATTACH_GLOBAL or ::CU_MEM_ATTACH_HOST
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_NOT_SUPPORTED,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_OUT_OF_MEMORY
 * \notefnerr
 *
 * \sa ::cuArray3DCreate, ::cuArray3DGetDescriptor, ::cuArrayCreate,
 * ::cuArrayDestroy, ::cuArrayGetDescriptor, ::cuMemAllocHost,
 * ::cuMemAllocPitch, ::cuMemcpy2D, ::cuMemcpy2DAsync, ::cuMemcpy2DUnaligned,
 * ::cuMemcpy3D, ::cuMemcpy3DAsync, ::cuMemcpyAtoA, ::cuMemcpyAtoD,
 * ::cuMemcpyAtoH, ::cuMemcpyAtoHAsync, ::cuMemcpyDtoA, ::cuMemcpyDtoD, ::cuMemcpyDtoDAsync,
 * ::cuMemcpyDtoH, ::cuMemcpyDtoHAsync, ::cuMemcpyHtoA, ::cuMemcpyHtoAAsync,
 * ::cuMemcpyHtoD, ::cuMemcpyHtoDAsync, ::cuMemFree, ::cuMemFreeHost,
 * ::cuMemGetAddressRange, ::cuMemGetInfo, ::cuMemHostAlloc,
 * ::cuMemHostGetDevicePointer, ::cuMemsetD2D8, ::cuMemsetD2D16,
 * ::cuMemsetD2D32, ::cuMemsetD8, ::cuMemsetD16, ::cuMemsetD32,
 * ::cuDeviceGetAttribute, ::cuStreamAttachMemAsync,
 * ::cudaMallocManaged
 */
CUresult CUDAAPI cuMemAllocManaged(CUdeviceptr *dptr, size_t bytesize, unsigned int flags);

/**
* \brief Registers a callback function to receive async notifications
* 
* Registers \p callbackFunc to receive async notifications.
* 
* The \p userData parameter is passed to the callback function at async notification time.  
* Likewise, \p callback is also passed to the callback function to distinguish between
* multiple registered callbacks.
* 
* The callback function being registered should be designed to return quickly (~10ms).  
* Any long running tasks should be queued for execution on an application thread.
* 
* Callbacks may not call cuDeviceRegisterAsyncNotification or cuDeviceUnregisterAsyncNotification.
* Doing so will result in ::CUDA_ERROR_NOT_PERMITTED. Async notification callbacks execute
* in an undefined order and may be serialized.
* 
* Returns in \p *callback a handle representing the registered callback instance.
* 
* \param device - The device on which to register the callback
* \param callbackFunc - The function to register as a callback
* \param userData - A generic pointer to user data. This is passed into the callback function.
* \param callback - A handle representing the registered callback instance
* 
* \return
* ::CUDA_SUCCESS
* ::CUDA_ERROR_NOT_SUPPORTED
* ::CUDA_ERROR_INVALID_DEVICE
* ::CUDA_ERROR_INVALID_VALUE
* ::CUDA_ERROR_NOT_PERMITTED
* ::CUDA_ERROR_UNKNOWN
* \notefnerr
* 
* \sa
* ::cuDeviceUnregisterAsyncNotification
*/
CUresult CUDAAPI cuDeviceRegisterAsyncNotification(CUdevice device, CUasyncCallback callbackFunc, void *userData, CUasyncCallbackHandle *callback);

/**
* \brief Unregisters an async notification callback
* 
* Unregisters \p callback so that the corresponding callback function will stop receiving
* async notifications.
* 
* \param device - The device from which to remove \p callback.
* \param callback - The callback instance to unregister from receiving async notifications.
* 
* \return
* ::CUDA_SUCCESS
* ::CUDA_ERROR_NOT_SUPPORTED
* ::CUDA_ERROR_INVALID_DEVICE
* ::CUDA_ERROR_INVALID_VALUE
* ::CUDA_ERROR_NOT_PERMITTED
* ::CUDA_ERROR_UNKNOWN
* \notefnerr
* 
* \sa
* ::cuDeviceRegisterAsyncNotification
*/
CUresult CUDAAPI cuDeviceUnregisterAsyncNotification(CUdevice device, CUasyncCallbackHandle callback);

/**
 * \brief Returns a handle to a compute device
 *
 * Returns in \p *device a device handle given a PCI bus ID string.
 *
 * \param dev      - Returned device handle
 *
 * \param pciBusId - String in one of the following forms:
 * [domain]:[bus]:[device].[function]
 * [domain]:[bus]:[device]
 * [bus]:[device].[function]
 * where \p domain, \p bus, \p device, and \p function are all hexadecimal values
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_DEVICE
 * \notefnerr
 *
 * \sa
 * ::cuDeviceGet,
 * ::cuDeviceGetAttribute,
 * ::cuDeviceGetPCIBusId,
 * ::cudaDeviceGetByPCIBusId
 */
CUresult CUDAAPI cuDeviceGetByPCIBusId(CUdevice *dev, const char *pciBusId);

/**
 * \brief Returns a PCI Bus Id string for the device
 *
 * Returns an ASCII string identifying the device \p dev in the NULL-terminated
 * string pointed to by \p pciBusId. \p len specifies the maximum length of the
 * string that may be returned.
 *
 * \param pciBusId - Returned identifier string for the device in the following format
 * [domain]:[bus]:[device].[function]
 * where \p domain, \p bus, \p device, and \p function are all hexadecimal values.
 * pciBusId should be large enough to store 13 characters including the NULL-terminator.
 *
 * \param len      - Maximum length of string to store in \p name
 *
 * \param dev      - Device to get identifier string for
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_DEVICE
 * \notefnerr
 *
 * \sa
 * ::cuDeviceGet,
 * ::cuDeviceGetAttribute,
 * ::cuDeviceGetByPCIBusId,
 * ::cudaDeviceGetPCIBusId
 */
CUresult CUDAAPI cuDeviceGetPCIBusId(char *pciBusId, int len, CUdevice dev);

/**
 * \brief Gets an interprocess handle for a previously allocated event
 *
 * Takes as input a previously allocated event. This event must have been
 * created with the ::CU_EVENT_INTERPROCESS and ::CU_EVENT_DISABLE_TIMING
 * flags set. This opaque handle may be copied into other processes and
 * opened with ::cuIpcOpenEventHandle to allow efficient hardware
 * synchronization between GPU work in different processes.
 *
 * After the event has been opened in the importing process,
 * ::cuEventRecord, ::cuEventSynchronize, ::cuStreamWaitEvent and
 * ::cuEventQuery may be used in either process. Performing operations
 * on the imported event after the exported event has been freed
 * with ::cuEventDestroy will result in undefined behavior.
 *
 * IPC functionality is restricted to devices with support for unified
 * addressing on Linux and Windows operating systems.
 * IPC functionality on Windows is supported for compatibility purposes
 * but not recommended as it comes with performance cost.
 * Users can test their device for IPC functionality by calling
 * ::cuapiDeviceGetAttribute with ::CU_DEVICE_ATTRIBUTE_IPC_EVENT_SUPPORTED
 *
 * \param pHandle - Pointer to a user allocated CUipcEventHandle
 *                    in which to return the opaque event handle
 * \param event   - Event allocated with ::CU_EVENT_INTERPROCESS and
 *                    ::CU_EVENT_DISABLE_TIMING flags.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_OUT_OF_MEMORY,
 * ::CUDA_ERROR_MAP_FAILED,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa
 * ::cuEventCreate,
 * ::cuEventDestroy,
 * ::cuEventSynchronize,
 * ::cuEventQuery,
 * ::cuStreamWaitEvent,
 * ::cuIpcOpenEventHandle,
 * ::cuIpcGetMemHandle,
 * ::cuIpcOpenMemHandle,
 * ::cuIpcCloseMemHandle,
 * ::cudaIpcGetEventHandle
 */
CUresult CUDAAPI cuIpcGetEventHandle(CUipcEventHandle *pHandle, CUevent event);

/**
 * \brief Opens an interprocess event handle for use in the current process
 *
 * Opens an interprocess event handle exported from another process with
 * ::cuIpcGetEventHandle. This function returns a ::CUevent that behaves like
 * a locally created event with the ::CU_EVENT_DISABLE_TIMING flag specified.
 * This event must be freed with ::cuEventDestroy.
 *
 * Performing operations on the imported event after the exported event has
 * been freed with ::cuEventDestroy will result in undefined behavior.
 *
 * IPC functionality is restricted to devices with support for unified
 * addressing on Linux and Windows operating systems.
 * IPC functionality on Windows is supported for compatibility purposes
 * but not recommended as it comes with performance cost.
 * Users can test their device for IPC functionality by calling
 * ::cuapiDeviceGetAttribute with ::CU_DEVICE_ATTRIBUTE_IPC_EVENT_SUPPORTED
 *
 * \param phEvent - Returns the imported event
 * \param handle  - Interprocess handle to open
 *
 * \returns
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_MAP_FAILED,
 * ::CUDA_ERROR_PEER_ACCESS_UNSUPPORTED,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa
 * ::cuEventCreate,
 * ::cuEventDestroy,
 * ::cuEventSynchronize,
 * ::cuEventQuery,
 * ::cuStreamWaitEvent,
 * ::cuIpcGetEventHandle,
 * ::cuIpcGetMemHandle,
 * ::cuIpcOpenMemHandle,
 * ::cuIpcCloseMemHandle,
 * ::cudaIpcOpenEventHandle
 */
CUresult CUDAAPI cuIpcOpenEventHandle(CUevent *phEvent, CUipcEventHandle handle);

/**
 * \brief Gets an interprocess memory handle for an existing device memory
 * allocation
 *
 * Takes a pointer to the base of an existing device memory allocation created
 * with ::cuMemAlloc and exports it for use in another process. This is a
 * lightweight operation and may be called multiple times on an allocation
 * without adverse effects.
 *
 * If a region of memory is freed with ::cuMemFree and a subsequent call
 * to ::cuMemAlloc returns memory with the same device address,
 * ::cuIpcGetMemHandle will return a unique handle for the
 * new memory.
 *
 * IPC functionality is restricted to devices with support for unified
 * addressing on Linux and Windows operating systems.
 * IPC functionality on Windows is supported for compatibility purposes
 * but not recommended as it comes with performance cost.
 * Users can test their device for IPC functionality by calling
 * ::cuapiDeviceGetAttribute with ::CU_DEVICE_ATTRIBUTE_IPC_EVENT_SUPPORTED
 *
 * \param pHandle - Pointer to user allocated ::CUipcMemHandle to return
 *                    the handle in.
 * \param dptr    - Base pointer to previously allocated device memory
 *
 * \returns
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_OUT_OF_MEMORY,
 * ::CUDA_ERROR_MAP_FAILED,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa
 * ::cuMemAlloc,
 * ::cuMemFree,
 * ::cuIpcGetEventHandle,
 * ::cuIpcOpenEventHandle,
 * ::cuIpcOpenMemHandle,
 * ::cuIpcCloseMemHandle,
 * ::cudaIpcGetMemHandle
 */
CUresult CUDAAPI cuIpcGetMemHandle(CUipcMemHandle *pHandle, CUdeviceptr dptr);

/**
 * \brief Opens an interprocess memory handle exported from another process
 * and returns a device pointer usable in the local process.
 *
 * Maps memory exported from another process with ::cuIpcGetMemHandle into
 * the current device address space. For contexts on different devices
 * ::cuIpcOpenMemHandle can attempt to enable peer access between the
 * devices as if the user called ::cuCtxEnablePeerAccess. This behavior is
 * controlled by the ::CU_IPC_MEM_LAZY_ENABLE_PEER_ACCESS flag.
 * ::cuDeviceCanAccessPeer can determine if a mapping is possible.
 *
 * Contexts that may open ::CUipcMemHandles are restricted in the following way.
 * ::CUipcMemHandles from each ::CUdevice in a given process may only be opened
 * by one ::CUcontext per ::CUdevice per other process.
 *
 * If the memory handle has already been opened by the current context, the
 * reference count on the handle is incremented by 1 and the existing device pointer
 * is returned.
 *
 * Memory returned from ::cuIpcOpenMemHandle must be freed with
 * ::cuIpcCloseMemHandle.
 *
 * Calling ::cuMemFree on an exported memory region before calling
 * ::cuIpcCloseMemHandle in the importing context will result in undefined
 * behavior.
 *
 * IPC functionality is restricted to devices with support for unified
 * addressing on Linux and Windows operating systems.
 * IPC functionality on Windows is supported for compatibility purposes
 * but not recommended as it comes with performance cost.
 * Users can test their device for IPC functionality by calling
 * ::cuapiDeviceGetAttribute with ::CU_DEVICE_ATTRIBUTE_IPC_EVENT_SUPPORTED
 *
 * \param pdptr  - Returned device pointer
 * \param handle - ::CUipcMemHandle to open
 * \param Flags  - Flags for this operation. Must be specified as ::CU_IPC_MEM_LAZY_ENABLE_PEER_ACCESS
 *
 * \returns
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_MAP_FAILED,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_TOO_MANY_PEERS,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \note No guarantees are made about the address returned in \p *pdptr.
 * In particular, multiple processes may not receive the same address for the same \p handle.
 *
 * \sa
 * ::cuMemAlloc,
 * ::cuMemFree,
 * ::cuIpcGetEventHandle,
 * ::cuIpcOpenEventHandle,
 * ::cuIpcGetMemHandle,
 * ::cuIpcCloseMemHandle,
 * ::cuCtxEnablePeerAccess,
 * ::cuDeviceCanAccessPeer,
 * ::cudaIpcOpenMemHandle
 */
CUresult CUDAAPI cuIpcOpenMemHandle(CUdeviceptr *pdptr, CUipcMemHandle handle, unsigned int Flags);

/**
 * \brief Attempts to close memory mapped with ::cuIpcOpenMemHandle
 *
 * Decrements the reference count of the memory returned by ::cuIpcOpenMemHandle by 1.
 * When the reference count reaches 0, this API unmaps the memory. The original allocation
 * in the exporting process as well as imported mappings in other processes
 * will be unaffected.
 *
 * Any resources used to enable peer access will be freed if this is the
 * last mapping using them.
 *
 * IPC functionality is restricted to devices with support for unified
 * addressing on Linux and Windows operating systems.
 * IPC functionality on Windows is supported for compatibility purposes
 * but not recommended as it comes with performance cost.
 * Users can test their device for IPC functionality by calling
 * ::cuapiDeviceGetAttribute with ::CU_DEVICE_ATTRIBUTE_IPC_EVENT_SUPPORTED
 *
 * \param dptr - Device pointer returned by ::cuIpcOpenMemHandle
 *
 * \returns
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_MAP_FAILED,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_INVALID_VALUE
 * \sa
 * ::cuMemAlloc,
 * ::cuMemFree,
 * ::cuIpcGetEventHandle,
 * ::cuIpcOpenEventHandle,
 * ::cuIpcGetMemHandle,
 * ::cuIpcOpenMemHandle,
 * ::cudaIpcCloseMemHandle
 */
CUresult CUDAAPI cuIpcCloseMemHandle(CUdeviceptr dptr);

/**
 * \brief Registers an existing host memory range for use by CUDA
 *
 * Page-locks the memory range specified by \p p and \p bytesize and maps it
 * for the device(s) as specified by \p Flags. This memory range also is added
 * to the same tracking mechanism as ::cuMemHostAlloc to automatically accelerate
 * calls to functions such as ::cuMemcpyHtoD(). Since the memory can be accessed
 * directly by the device, it can be read or written with much higher bandwidth
 * than pageable memory that has not been registered.  Page-locking excessive
 * amounts of memory may degrade system performance, since it reduces the amount
 * of memory available to the system for paging. As a result, this function is
 * best used sparingly to register staging areas for data exchange between
 * host and device.
 *
 * On systems where ::CU_DEVICE_ATTRIBUTE_PAGEABLE_MEMORY_ACCESS_USES_HOST_PAGE_TABLES 
 * is true, ::cuMemHostRegister will not page-lock the memory range specified 
 * by \p ptr but only populate unpopulated pages.
 *
 * The \p Flags parameter enables different options to be specified that
 * affect the allocation, as follows.
 *
 * - ::CU_MEMHOSTREGISTER_PORTABLE: The memory returned by this call will be
 *   considered as pinned memory by all CUDA contexts, not just the one that
 *   performed the allocation.
 *
 * - ::CU_MEMHOSTREGISTER_DEVICEMAP: Maps the allocation into the CUDA address
 *   space. The device pointer to the memory may be obtained by calling
 *   ::cuMemHostGetDevicePointer().
 *
 * - ::CU_MEMHOSTREGISTER_IOMEMORY: The pointer is treated as pointing to some
 *   I/O memory space, e.g. the PCI Express resource of a 3rd party device.
 *
 * - ::CU_MEMHOSTREGISTER_READ_ONLY: The pointer is treated as pointing to memory
 *   that is considered read-only by the device.  On platforms without
 *   ::CU_DEVICE_ATTRIBUTE_PAGEABLE_MEMORY_ACCESS_USES_HOST_PAGE_TABLES, this flag is
 *   required in order to register memory mapped to the CPU as read-only.  Support
 *   for the use of this flag can be queried from the device attribute
 *   ::CU_DEVICE_ATTRIBUTE_READ_ONLY_HOST_REGISTER_SUPPORTED.  Using this flag with
 *   a current context associated with a device that does not have this attribute
 *   set will cause ::cuMemHostRegister to error with CUDA_ERROR_NOT_SUPPORTED.
 *
 * All of these flags are orthogonal to one another: a developer may page-lock
 * memory that is portable or mapped with no restrictions.
 *
 * The ::CU_MEMHOSTREGISTER_DEVICEMAP flag may be specified on CUDA contexts for
 * devices that do not support mapped pinned memory. The failure is deferred
 * to ::cuMemHostGetDevicePointer() because the memory may be mapped into
 * other CUDA contexts via the ::CU_MEMHOSTREGISTER_PORTABLE flag.
 *
 * For devices that have a non-zero value for the device attribute
 * ::CU_DEVICE_ATTRIBUTE_CAN_USE_HOST_POINTER_FOR_REGISTERED_MEM, the memory
 * can also be accessed from the device using the host pointer \p p.
 * The device pointer returned by ::cuMemHostGetDevicePointer() may or may not
 * match the original host pointer \p ptr and depends on the devices visible to the
 * application. If all devices visible to the application have a non-zero value for the
 * device attribute, the device pointer returned by ::cuMemHostGetDevicePointer()
 * will match the original pointer \p ptr. If any device visible to the application
 * has a zero value for the device attribute, the device pointer returned by
 * ::cuMemHostGetDevicePointer() will not match the original host pointer \p ptr,
 * but it will be suitable for use on all devices provided Unified Virtual Addressing
 * is enabled. In such systems, it is valid to access the memory using either pointer
 * on devices that have a non-zero value for the device attribute. Note however that
 * such devices should access the memory using only of the two pointers and not both.
 *
 * The memory page-locked by this function must be unregistered with
 * ::cuMemHostUnregister().
 *
 * \param p        - Host pointer to memory to page-lock
 * \param bytesize - Size in bytes of the address range to page-lock
 * \param Flags    - Flags for allocation request
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_OUT_OF_MEMORY,
 * ::CUDA_ERROR_HOST_MEMORY_ALREADY_REGISTERED,
 * ::CUDA_ERROR_NOT_PERMITTED,
 * ::CUDA_ERROR_NOT_SUPPORTED
 * \notefnerr
 *
 * \sa
 * ::cuMemHostUnregister,
 * ::cuMemHostGetFlags,
 * ::cuMemHostGetDevicePointer,
 * ::cudaHostRegister
 */
CUresult CUDAAPI cuMemHostRegister(void *p, size_t bytesize, unsigned int Flags);

/**
 * \brief Unregisters a memory range that was registered with cuMemHostRegister.
 *
 * Unmaps the memory range whose base address is specified by \p p, and makes
 * it pageable again.
 *
 * The base address must be the same one specified to ::cuMemHostRegister().
 *
 * \param p - Host pointer to memory to unregister
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_OUT_OF_MEMORY,
 * ::CUDA_ERROR_HOST_MEMORY_NOT_REGISTERED,
 * \notefnerr
 *
 * \sa
 * ::cuMemHostRegister,
 * ::cudaHostUnregister
 */
CUresult CUDAAPI cuMemHostUnregister(void *p);

/**
 * \brief Copies memory
 *
 * Copies data between two pointers.
 * \p dst and \p src are base pointers of the destination and source, respectively.
 * \p ByteCount specifies the number of bytes to copy.
 * Note that this function infers the type of the transfer (host to host, host to
 *   device, device to device, or device to host) from the pointer values.  This
 *   function is only allowed in contexts which support unified addressing.
 *
 * \param dst - Destination unified virtual address space pointer
 * \param src - Source unified virtual address space pointer
 * \param ByteCount - Size of memory copy in bytes
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 * \note_sync
 * \note_memcpy
 *
 * \sa ::cuArray3DCreate, ::cuArray3DGetDescriptor, ::cuArrayCreate,
 * ::cuArrayDestroy, ::cuArrayGetDescriptor, ::cuMemAlloc, ::cuMemAllocHost,
 * ::cuMemAllocPitch, ::cuMemcpy2D, ::cuMemcpy2DAsync, ::cuMemcpy2DUnaligned,
 * ::cuMemcpy3D, ::cuMemcpy3DAsync, ::cuMemcpyAtoA, ::cuMemcpyAtoD,
 * ::cuMemcpyAtoH, ::cuMemcpyAtoHAsync, ::cuMemcpyDtoA,
 * ::cuMemcpyDtoH, ::cuMemcpyDtoHAsync, ::cuMemcpyHtoA, ::cuMemcpyHtoAAsync,
 * ::cuMemcpyHtoD, ::cuMemcpyHtoDAsync, ::cuMemFree, ::cuMemFreeHost,
 * ::cuMemGetAddressRange, ::cuMemGetInfo, ::cuMemHostAlloc,
 * ::cuMemHostGetDevicePointer, ::cuMemsetD2D8, ::cuMemsetD2D16,
 * ::cuMemsetD2D32, ::cuMemsetD8, ::cuMemsetD16, ::cuMemsetD32,
 * ::cudaMemcpy,
 * ::cudaMemcpyToSymbol,
 * ::cudaMemcpyFromSymbol
 */
CUresult CUDAAPI cuMemcpy(CUdeviceptr dst, CUdeviceptr src, size_t ByteCount);

/**
 * \brief Copies device memory between two contexts
 *
 * Copies from device memory in one context to device memory in another
 * context. \p dstDevice is the base device pointer of the destination memory
 * and \p dstContext is the destination context.  \p srcDevice is the base
 * device pointer of the source memory and \p srcContext is the source pointer.
 * \p ByteCount specifies the number of bytes to copy.
 *
 * \param dstDevice  - Destination device pointer
 * \param dstContext - Destination context
 * \param srcDevice  - Source device pointer
 * \param srcContext - Source context
 * \param ByteCount  - Size of memory copy in bytes
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 * \note_sync
 *
 * \sa ::cuMemcpyDtoD, ::cuMemcpy3DPeer, ::cuMemcpyDtoDAsync, ::cuMemcpyPeerAsync,
 * ::cuMemcpy3DPeerAsync,
 * ::cudaMemcpyPeer
 */
CUresult CUDAAPI cuMemcpyPeer(CUdeviceptr dstDevice, CUcontext dstContext, CUdeviceptr srcDevice, CUcontext srcContext, size_t ByteCount);

/**
 * \brief Copies memory from Host to Device
 *
 * Copies from host memory to device memory. \p dstDevice and \p srcHost are
 * the base addresses of the destination and source, respectively. \p ByteCount
 * specifies the number of bytes to copy.
 *
 * \param dstDevice - Destination device pointer
 * \param srcHost   - Source host pointer
 * \param ByteCount - Size of memory copy in bytes
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 * \note_sync
 * \note_memcpy
 *
 * \sa ::cuArray3DCreate, ::cuArray3DGetDescriptor, ::cuArrayCreate,
 * ::cuArrayDestroy, ::cuArrayGetDescriptor, ::cuMemAlloc, ::cuMemAllocHost,
 * ::cuMemAllocPitch, ::cuMemcpy2D, ::cuMemcpy2DAsync, ::cuMemcpy2DUnaligned,
 * ::cuMemcpy3D, ::cuMemcpy3DAsync, ::cuMemcpyAtoA, ::cuMemcpyAtoD,
 * ::cuMemcpyAtoH, ::cuMemcpyAtoHAsync, ::cuMemcpyDtoA, ::cuMemcpyDtoD, ::cuMemcpyDtoDAsync,
 * ::cuMemcpyDtoH, ::cuMemcpyDtoHAsync, ::cuMemcpyHtoA, ::cuMemcpyHtoAAsync,
 * ::cuMemcpyHtoDAsync, ::cuMemFree, ::cuMemFreeHost,
 * ::cuMemGetAddressRange, ::cuMemGetInfo, ::cuMemHostAlloc,
 * ::cuMemHostGetDevicePointer, ::cuMemsetD2D8, ::cuMemsetD2D16,
 * ::cuMemsetD2D32, ::cuMemsetD8, ::cuMemsetD16, ::cuMemsetD32,
 * ::cudaMemcpy,
 * ::cudaMemcpyToSymbol
 */
CUresult CUDAAPI cuMemcpyHtoD(CUdeviceptr dstDevice, const void *srcHost, size_t ByteCount);

/**
 * \brief Copies memory from Device to Host
 *
 * Copies from device to host memory. \p dstHost and \p srcDevice specify the
 * base pointers of the destination and source, respectively. \p ByteCount
 * specifies the number of bytes to copy.
 *
 * \param dstHost   - Destination host pointer
 * \param srcDevice - Source device pointer
 * \param ByteCount - Size of memory copy in bytes
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 * \note_sync
 * \note_memcpy
 *
 * \sa ::cuArray3DCreate, ::cuArray3DGetDescriptor, ::cuArrayCreate,
 * ::cuArrayDestroy, ::cuArrayGetDescriptor, ::cuMemAlloc, ::cuMemAllocHost,
 * ::cuMemAllocPitch, ::cuMemcpy2D, ::cuMemcpy2DAsync, ::cuMemcpy2DUnaligned,
 * ::cuMemcpy3D, ::cuMemcpy3DAsync, ::cuMemcpyAtoA, ::cuMemcpyAtoD,
 * ::cuMemcpyAtoH, ::cuMemcpyAtoHAsync, ::cuMemcpyDtoA, ::cuMemcpyDtoD, ::cuMemcpyDtoDAsync,
 * ::cuMemcpyDtoHAsync, ::cuMemcpyHtoA, ::cuMemcpyHtoAAsync,
 * ::cuMemcpyHtoD, ::cuMemcpyHtoDAsync, ::cuMemFree, ::cuMemFreeHost,
 * ::cuMemGetAddressRange, ::cuMemGetInfo, ::cuMemHostAlloc,
 * ::cuMemHostGetDevicePointer, ::cuMemsetD2D8, ::cuMemsetD2D16,
 * ::cuMemsetD2D32, ::cuMemsetD8, ::cuMemsetD16, ::cuMemsetD32,
 * ::cudaMemcpy,
 * ::cudaMemcpyFromSymbol
 */
CUresult CUDAAPI cuMemcpyDtoH(void *dstHost, CUdeviceptr srcDevice, size_t ByteCount);

/**
 * \brief Copies memory from Device to Device
 *
 * Copies from device memory to device memory. \p dstDevice and \p srcDevice
 * are the base pointers of the destination and source, respectively.
 * \p ByteCount specifies the number of bytes to copy.
 *
 * \param dstDevice - Destination device pointer
 * \param srcDevice - Source device pointer
 * \param ByteCount - Size of memory copy in bytes
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 * \note_sync
 *
 * \sa ::cuArray3DCreate, ::cuArray3DGetDescriptor, ::cuArrayCreate,
 * ::cuArrayDestroy, ::cuArrayGetDescriptor, ::cuMemAlloc, ::cuMemAllocHost,
 * ::cuMemAllocPitch, ::cuMemcpy2D, ::cuMemcpy2DAsync, ::cuMemcpy2DUnaligned,
 * ::cuMemcpy3D, ::cuMemcpy3DAsync, ::cuMemcpyAtoA, ::cuMemcpyAtoD,
 * ::cuMemcpyAtoH, ::cuMemcpyAtoHAsync, ::cuMemcpyDtoA,
 * ::cuMemcpyDtoH, ::cuMemcpyDtoHAsync, ::cuMemcpyHtoA, ::cuMemcpyHtoAAsync,
 * ::cuMemcpyHtoD, ::cuMemcpyHtoDAsync, ::cuMemFree, ::cuMemFreeHost,
 * ::cuMemGetAddressRange, ::cuMemGetInfo, ::cuMemHostAlloc,
 * ::cuMemHostGetDevicePointer, ::cuMemsetD2D8, ::cuMemsetD2D16,
 * ::cuMemsetD2D32, ::cuMemsetD8, ::cuMemsetD16, ::cuMemsetD32,
 * ::cudaMemcpy,
 * ::cudaMemcpyToSymbol,
 * ::cudaMemcpyFromSymbol
 */
CUresult CUDAAPI cuMemcpyDtoD(CUdeviceptr dstDevice, CUdeviceptr srcDevice, size_t ByteCount);

/**
 * \brief Copies memory from Device to Array
 *
 * Copies from device memory to a 1D CUDA array. \p dstArray and \p dstOffset
 * specify the CUDA array handle and starting index of the destination data.
 * \p srcDevice specifies the base pointer of the source. \p ByteCount
 * specifies the number of bytes to copy.
 *
 * \param dstArray  - Destination array
 * \param dstOffset - Offset in bytes of destination array
 * \param srcDevice - Source device pointer
 * \param ByteCount - Size of memory copy in bytes
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 * \note_sync
 *
 * \sa ::cuArray3DCreate, ::cuArray3DGetDescriptor, ::cuArrayCreate,
 * ::cuArrayDestroy, ::cuArrayGetDescriptor, ::cuMemAlloc, ::cuMemAllocHost,
 * ::cuMemAllocPitch, ::cuMemcpy2D, ::cuMemcpy2DAsync, ::cuMemcpy2DUnaligned,
 * ::cuMemcpy3D, ::cuMemcpy3DAsync, ::cuMemcpyAtoA, ::cuMemcpyAtoD,
 * ::cuMemcpyAtoH, ::cuMemcpyAtoHAsync, ::cuMemcpyDtoD, ::cuMemcpyDtoDAsync,
 * ::cuMemcpyDtoH, ::cuMemcpyDtoHAsync, ::cuMemcpyHtoA, ::cuMemcpyHtoAAsync,
 * ::cuMemcpyHtoD, ::cuMemcpyHtoDAsync, ::cuMemFree, ::cuMemFreeHost,
 * ::cuMemGetAddressRange, ::cuMemGetInfo, ::cuMemHostAlloc,
 * ::cuMemHostGetDevicePointer, ::cuMemsetD2D8, ::cuMemsetD2D16,
 * ::cuMemsetD2D32, ::cuMemsetD8, ::cuMemsetD16, ::cuMemsetD32,
 * ::cudaMemcpyToArray
 */
CUresult CUDAAPI cuMemcpyDtoA(CUarray dstArray, size_t dstOffset, CUdeviceptr srcDevice, size_t ByteCount);

/**
 * \brief Copies memory from Array to Device
 *
 * Copies from one 1D CUDA array to device memory. \p dstDevice specifies the
 * base pointer of the destination and must be naturally aligned with the CUDA
 * array elements. \p srcArray and \p srcOffset specify the CUDA array handle
 * and the offset in bytes into the array where the copy is to begin.
 * \p ByteCount specifies the number of bytes to copy and must be evenly
 * divisible by the array element size.
 *
 * \param dstDevice - Destination device pointer
 * \param srcArray  - Source array
 * \param srcOffset - Offset in bytes of source array
 * \param ByteCount - Size of memory copy in bytes
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 * \note_sync
 *
 * \sa ::cuArray3DCreate, ::cuArray3DGetDescriptor, ::cuArrayCreate,
 * ::cuArrayDestroy, ::cuArrayGetDescriptor, ::cuMemAlloc, ::cuMemAllocHost,
 * ::cuMemAllocPitch, ::cuMemcpy2D, ::cuMemcpy2DAsync, ::cuMemcpy2DUnaligned,
 * ::cuMemcpy3D, ::cuMemcpy3DAsync, ::cuMemcpyAtoA,
 * ::cuMemcpyAtoH, ::cuMemcpyAtoHAsync, ::cuMemcpyDtoA, ::cuMemcpyDtoD, ::cuMemcpyDtoDAsync,
 * ::cuMemcpyDtoH, ::cuMemcpyDtoHAsync, ::cuMemcpyHtoA, ::cuMemcpyHtoAAsync,
 * ::cuMemcpyHtoD, ::cuMemcpyHtoDAsync, ::cuMemFree, ::cuMemFreeHost,
 * ::cuMemGetAddressRange, ::cuMemGetInfo, ::cuMemHostAlloc,
 * ::cuMemHostGetDevicePointer, ::cuMemsetD2D8, ::cuMemsetD2D16,
 * ::cuMemsetD2D32, ::cuMemsetD8, ::cuMemsetD16, ::cuMemsetD32,
 * ::cudaMemcpyFromArray
 */
CUresult CUDAAPI cuMemcpyAtoD(CUdeviceptr dstDevice, CUarray srcArray, size_t srcOffset, size_t ByteCount);

/**
 * \brief Copies memory from Host to Array
 *
 * Copies from host memory to a 1D CUDA array. \p dstArray and \p dstOffset
 * specify the CUDA array handle and starting offset in bytes of the destination
 * data.  \p pSrc specifies the base address of the source. \p ByteCount specifies
 * the number of bytes to copy.
 *
 * \param dstArray  - Destination array
 * \param dstOffset - Offset in bytes of destination array
 * \param srcHost   - Source host pointer
 * \param ByteCount - Size of memory copy in bytes
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 * \note_sync
 * \note_memcpy
 *
 * \sa ::cuArray3DCreate, ::cuArray3DGetDescriptor, ::cuArrayCreate,
 * ::cuArrayDestroy, ::cuArrayGetDescriptor, ::cuMemAlloc, ::cuMemAllocHost,
 * ::cuMemAllocPitch, ::cuMemcpy2D, ::cuMemcpy2DAsync, ::cuMemcpy2DUnaligned,
 * ::cuMemcpy3D, ::cuMemcpy3DAsync, ::cuMemcpyAtoA, ::cuMemcpyAtoD,
 * ::cuMemcpyAtoH, ::cuMemcpyAtoHAsync, ::cuMemcpyDtoA, ::cuMemcpyDtoD, ::cuMemcpyDtoDAsync,
 * ::cuMemcpyDtoH, ::cuMemcpyDtoHAsync, ::cuMemcpyHtoAAsync,
 * ::cuMemcpyHtoD, ::cuMemcpyHtoDAsync, ::cuMemFree, ::cuMemFreeHost,
 * ::cuMemGetAddressRange, ::cuMemGetInfo, ::cuMemHostAlloc,
 * ::cuMemHostGetDevicePointer, ::cuMemsetD2D8, ::cuMemsetD2D16,
 * ::cuMemsetD2D32, ::cuMemsetD8, ::cuMemsetD16, ::cuMemsetD32,
 * ::cudaMemcpyToArray
 */
CUresult CUDAAPI cuMemcpyHtoA(CUarray dstArray, size_t dstOffset, const void *srcHost, size_t ByteCount);

/**
 * \brief Copies memory from Array to Host
 *
 * Copies from one 1D CUDA array to host memory. \p dstHost specifies the base
 * pointer of the destination. \p srcArray and \p srcOffset specify the CUDA
 * array handle and starting offset in bytes of the source data.
 * \p ByteCount specifies the number of bytes to copy.
 *
 * \param dstHost   - Destination device pointer
 * \param srcArray  - Source array
 * \param srcOffset - Offset in bytes of source array
 * \param ByteCount - Size of memory copy in bytes
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 * \note_sync
 * \note_memcpy
 *
 * \sa ::cuArray3DCreate, ::cuArray3DGetDescriptor, ::cuArrayCreate,
 * ::cuArrayDestroy, ::cuArrayGetDescriptor, ::cuMemAlloc, ::cuMemAllocHost,
 * ::cuMemAllocPitch, ::cuMemcpy2D, ::cuMemcpy2DAsync, ::cuMemcpy2DUnaligned,
 * ::cuMemcpy3D, ::cuMemcpy3DAsync, ::cuMemcpyAtoA, ::cuMemcpyAtoD,
 * ::cuMemcpyAtoHAsync, ::cuMemcpyDtoA, ::cuMemcpyDtoD, ::cuMemcpyDtoDAsync,
 * ::cuMemcpyDtoH, ::cuMemcpyDtoHAsync, ::cuMemcpyHtoA, ::cuMemcpyHtoAAsync,
 * ::cuMemcpyHtoD, ::cuMemcpyHtoDAsync, ::cuMemFree, ::cuMemFreeHost,
 * ::cuMemGetAddressRange, ::cuMemGetInfo, ::cuMemHostAlloc,
 * ::cuMemHostGetDevicePointer, ::cuMemsetD2D8, ::cuMemsetD2D16,
 * ::cuMemsetD2D32, ::cuMemsetD8, ::cuMemsetD16, ::cuMemsetD32,
 * ::cudaMemcpyFromArray
 */
CUresult CUDAAPI cuMemcpyAtoH(void *dstHost, CUarray srcArray, size_t srcOffset, size_t ByteCount);

/**
 * \brief Copies memory from Array to Array
 *
 * Copies from one 1D CUDA array to another. \p dstArray and \p srcArray
 * specify the handles of the destination and source CUDA arrays for the copy,
 * respectively. \p dstOffset and \p srcOffset specify the destination and
 * source offsets in bytes into the CUDA arrays. \p ByteCount is the number of
 * bytes to be copied. The size of the elements in the CUDA arrays need not be
 * the same format, but the elements must be the same size; and count must be
 * evenly divisible by that size.
 *
 * \param dstArray  - Destination array
 * \param dstOffset - Offset in bytes of destination array
 * \param srcArray  - Source array
 * \param srcOffset - Offset in bytes of source array
 * \param ByteCount - Size of memory copy in bytes
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 * \note_sync
 *
 * \sa ::cuArray3DCreate, ::cuArray3DGetDescriptor, ::cuArrayCreate,
 * ::cuArrayDestroy, ::cuArrayGetDescriptor, ::cuMemAlloc, ::cuMemAllocHost,
 * ::cuMemAllocPitch, ::cuMemcpy2D, ::cuMemcpy2DAsync, ::cuMemcpy2DUnaligned,
 * ::cuMemcpy3D, ::cuMemcpy3DAsync, ::cuMemcpyAtoD,
 * ::cuMemcpyAtoH, ::cuMemcpyAtoHAsync, ::cuMemcpyDtoA, ::cuMemcpyDtoD, ::cuMemcpyDtoDAsync,
 * ::cuMemcpyDtoH, ::cuMemcpyDtoHAsync, ::cuMemcpyHtoA, ::cuMemcpyHtoAAsync,
 * ::cuMemcpyHtoD, ::cuMemcpyHtoDAsync, ::cuMemFree, ::cuMemFreeHost,
 * ::cuMemGetAddressRange, ::cuMemGetInfo, ::cuMemHostAlloc,
 * ::cuMemHostGetDevicePointer, ::cuMemsetD2D8, ::cuMemsetD2D16,
 * ::cuMemsetD2D32, ::cuMemsetD8, ::cuMemsetD16, ::cuMemsetD32,
 * ::cudaMemcpyArrayToArray
 */
CUresult CUDAAPI cuMemcpyAtoA(CUarray dstArray, size_t dstOffset, CUarray srcArray, size_t srcOffset, size_t ByteCount);

/**
 * \brief Copies memory for 2D arrays
 *
 * Perform a 2D memory copy according to the parameters specified in \p pCopy.
 * The ::CUDA_MEMCPY2D structure is defined as:
 *
 * \code
   typedef struct CUDA_MEMCPY2D_st {
      unsigned int srcXInBytes, srcY;
      CUmemorytype srcMemoryType;
          const void *srcHost;
          CUdeviceptr srcDevice;
          CUarray srcArray;
          unsigned int srcPitch;

      unsigned int dstXInBytes, dstY;
      CUmemorytype dstMemoryType;
          void *dstHost;
          CUdeviceptr dstDevice;
          CUarray dstArray;
          unsigned int dstPitch;

      unsigned int WidthInBytes;
      unsigned int Height;
   } CUDA_MEMCPY2D;
 * \endcode
 * where:
 * - ::srcMemoryType and ::dstMemoryType specify the type of memory of the
 *   source and destination, respectively; ::CUmemorytype_enum is defined as:
 *
 * \code
   typedef enum CUmemorytype_enum {
      CU_MEMORYTYPE_HOST = 0x01,
      CU_MEMORYTYPE_DEVICE = 0x02,
      CU_MEMORYTYPE_ARRAY = 0x03,
      CU_MEMORYTYPE_UNIFIED = 0x04
   } CUmemorytype;
 * \endcode
 *
 * \par
 * If ::srcMemoryType is ::CU_MEMORYTYPE_UNIFIED, ::srcDevice and ::srcPitch
 *   specify the (unified virtual address space) base address of the source data
 *   and the bytes per row to apply.  ::srcArray is ignored.
 * This value may be used only if unified addressing is supported in the calling
 *   context.
 *
 * \par
 * If ::srcMemoryType is ::CU_MEMORYTYPE_HOST, ::srcHost and ::srcPitch
 * specify the (host) base address of the source data and the bytes per row to
 * apply. ::srcArray is ignored.
 *
 * \par
 * If ::srcMemoryType is ::CU_MEMORYTYPE_DEVICE, ::srcDevice and ::srcPitch
 * specify the (device) base address of the source data and the bytes per row
 * to apply. ::srcArray is ignored.
 *
 * \par
 * If ::srcMemoryType is ::CU_MEMORYTYPE_ARRAY, ::srcArray specifies the
 * handle of the source data. ::srcHost, ::srcDevice and ::srcPitch are
 * ignored.
 *
 * \par
 * If ::dstMemoryType is ::CU_MEMORYTYPE_HOST, ::dstHost and ::dstPitch
 * specify the (host) base address of the destination data and the bytes per
 * row to apply. ::dstArray is ignored.
 *
 * \par
 * If ::dstMemoryType is ::CU_MEMORYTYPE_UNIFIED, ::dstDevice and ::dstPitch
 *   specify the (unified virtual address space) base address of the source data
 *   and the bytes per row to apply.  ::dstArray is ignored.
 * This value may be used only if unified addressing is supported in the calling
 *   context.
 *
 * \par
 * If ::dstMemoryType is ::CU_MEMORYTYPE_DEVICE, ::dstDevice and ::dstPitch
 * specify the (device) base address of the destination data and the bytes per
 * row to apply. ::dstArray is ignored.
 *
 * \par
 * If ::dstMemoryType is ::CU_MEMORYTYPE_ARRAY, ::dstArray specifies the
 * handle of the destination data. ::dstHost, ::dstDevice and ::dstPitch are
 * ignored.
 *
 * - ::srcXInBytes and ::srcY specify the base address of the source data for
 *   the copy.
 *
 * \par
 * For host pointers, the starting address is
 * \code
  void* Start = (void*)((char*)srcHost+srcY*srcPitch + srcXInBytes);
 * \endcode
 *
 * \par
 * For device pointers, the starting address is
 * \code
  CUdeviceptr Start = srcDevice+srcY*srcPitch+srcXInBytes;
 * \endcode
 *
 * \par
 * For CUDA arrays, ::srcXInBytes must be evenly divisible by the array
 * element size.
 *
 * - ::dstXInBytes and ::dstY specify the base address of the destination data
 *   for the copy.
 *
 * \par
 * For host pointers, the base address is
 * \code
  void* dstStart = (void*)((char*)dstHost+dstY*dstPitch + dstXInBytes);
 * \endcode
 *
 * \par
 * For device pointers, the starting address is
 * \code
  CUdeviceptr dstStart = dstDevice+dstY*dstPitch+dstXInBytes;
 * \endcode
 *
 * \par
 * For CUDA arrays, ::dstXInBytes must be evenly divisible by the array
 * element size.
 *
 * - ::WidthInBytes and ::Height specify the width (in bytes) and height of
 *   the 2D copy being performed.
 * - If specified, ::srcPitch must be greater than or equal to ::WidthInBytes +
 *   ::srcXInBytes, and ::dstPitch must be greater than or equal to
 *   ::WidthInBytes + dstXInBytes.
 *
 * \par
 * ::cuMemcpy2D() returns an error if any pitch is greater than the maximum
 * allowed (::CU_DEVICE_ATTRIBUTE_MAX_PITCH). ::cuMemAllocPitch() passes back
 * pitches that always work with ::cuMemcpy2D(). On intra-device memory copies
 * (device to device, CUDA array to device, CUDA array to CUDA array),
 * ::cuMemcpy2D() may fail for pitches not computed by ::cuMemAllocPitch().
 * ::cuMemcpy2DUnaligned() does not have this restriction, but may run
 * significantly slower in the cases where ::cuMemcpy2D() would have returned
 * an error code.
 *
 * \param pCopy - Parameters for the memory copy
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 * \note_sync
 *
 * \sa ::cuArray3DCreate, ::cuArray3DGetDescriptor, ::cuArrayCreate,
 * ::cuArrayDestroy, ::cuArrayGetDescriptor, ::cuMemAlloc, ::cuMemAllocHost,
 * ::cuMemAllocPitch, ::cuMemcpy2DAsync, ::cuMemcpy2DUnaligned,
 * ::cuMemcpy3D, ::cuMemcpy3DAsync, ::cuMemcpyAtoA, ::cuMemcpyAtoD,
 * ::cuMemcpyAtoH, ::cuMemcpyAtoHAsync, ::cuMemcpyDtoA, ::cuMemcpyDtoD, ::cuMemcpyDtoDAsync,
 * ::cuMemcpyDtoH, ::cuMemcpyDtoHAsync, ::cuMemcpyHtoA, ::cuMemcpyHtoAAsync,
 * ::cuMemcpyHtoD, ::cuMemcpyHtoDAsync, ::cuMemFree, ::cuMemFreeHost,
 * ::cuMemGetAddressRange, ::cuMemGetInfo, ::cuMemHostAlloc,
 * ::cuMemHostGetDevicePointer, ::cuMemsetD2D8, ::cuMemsetD2D16,
 * ::cuMemsetD2D32, ::cuMemsetD8, ::cuMemsetD16, ::cuMemsetD32,
 * ::cudaMemcpy2D,
 * ::cudaMemcpy2DToArray,
 * ::cudaMemcpy2DFromArray
 */
CUresult CUDAAPI cuMemcpy2D(const CUDA_MEMCPY2D *pCopy);

/**
 * \brief Copies memory for 2D arrays
 *
 * Perform a 2D memory copy according to the parameters specified in \p pCopy.
 * The ::CUDA_MEMCPY2D structure is defined as:
 *
 * \code
   typedef struct CUDA_MEMCPY2D_st {
      unsigned int srcXInBytes, srcY;
      CUmemorytype srcMemoryType;
      const void *srcHost;
      CUdeviceptr srcDevice;
      CUarray srcArray;
      unsigned int srcPitch;
      unsigned int dstXInBytes, dstY;
      CUmemorytype dstMemoryType;
      void *dstHost;
      CUdeviceptr dstDevice;
      CUarray dstArray;
      unsigned int dstPitch;
      unsigned int WidthInBytes;
      unsigned int Height;
   } CUDA_MEMCPY2D;
 * \endcode
 * where:
 * - ::srcMemoryType and ::dstMemoryType specify the type of memory of the
 *   source and destination, respectively; ::CUmemorytype_enum is defined as:
 *
 * \code
   typedef enum CUmemorytype_enum {
      CU_MEMORYTYPE_HOST = 0x01,
      CU_MEMORYTYPE_DEVICE = 0x02,
      CU_MEMORYTYPE_ARRAY = 0x03,
      CU_MEMORYTYPE_UNIFIED = 0x04
   } CUmemorytype;
 * \endcode
 *
 * \par
 * If ::srcMemoryType is ::CU_MEMORYTYPE_UNIFIED, ::srcDevice and ::srcPitch
 *   specify the (unified virtual address space) base address of the source data
 *   and the bytes per row to apply.  ::srcArray is ignored.
 * This value may be used only if unified addressing is supported in the calling
 *   context.
 *
 * \par
 * If ::srcMemoryType is ::CU_MEMORYTYPE_HOST, ::srcHost and ::srcPitch
 * specify the (host) base address of the source data and the bytes per row to
 * apply. ::srcArray is ignored.
 *
 * \par
 * If ::srcMemoryType is ::CU_MEMORYTYPE_DEVICE, ::srcDevice and ::srcPitch
 * specify the (device) base address of the source data and the bytes per row
 * to apply. ::srcArray is ignored.
 *
 * \par
 * If ::srcMemoryType is ::CU_MEMORYTYPE_ARRAY, ::srcArray specifies the
 * handle of the source data. ::srcHost, ::srcDevice and ::srcPitch are
 * ignored.
 *
 * \par
 * If ::dstMemoryType is ::CU_MEMORYTYPE_UNIFIED, ::dstDevice and ::dstPitch
 *   specify the (unified virtual address space) base address of the source data
 *   and the bytes per row to apply.  ::dstArray is ignored.
 * This value may be used only if unified addressing is supported in the calling
 *   context.
 *
 * \par
 * If ::dstMemoryType is ::CU_MEMORYTYPE_HOST, ::dstHost and ::dstPitch
 * specify the (host) base address of the destination data and the bytes per
 * row to apply. ::dstArray is ignored.
 *
 * \par
 * If ::dstMemoryType is ::CU_MEMORYTYPE_DEVICE, ::dstDevice and ::dstPitch
 * specify the (device) base address of the destination data and the bytes per
 * row to apply. ::dstArray is ignored.
 *
 * \par
 * If ::dstMemoryType is ::CU_MEMORYTYPE_ARRAY, ::dstArray specifies the
 * handle of the destination data. ::dstHost, ::dstDevice and ::dstPitch are
 * ignored.
 *
 * - ::srcXInBytes and ::srcY specify the base address of the source data for
 *   the copy.
 *
 * \par
 * For host pointers, the starting address is
 * \code
  void* Start = (void*)((char*)srcHost+srcY*srcPitch + srcXInBytes);
 * \endcode
 *
 * \par
 * For device pointers, the starting address is
 * \code
  CUdeviceptr Start = srcDevice+srcY*srcPitch+srcXInBytes;
 * \endcode
 *
 * \par
 * For CUDA arrays, ::srcXInBytes must be evenly divisible by the array
 * element size.
 *
 * - ::dstXInBytes and ::dstY specify the base address of the destination data
 *   for the copy.
 *
 * \par
 * For host pointers, the base address is
 * \code
  void* dstStart = (void*)((char*)dstHost+dstY*dstPitch + dstXInBytes);
 * \endcode
 *
 * \par
 * For device pointers, the starting address is
 * \code
  CUdeviceptr dstStart = dstDevice+dstY*dstPitch+dstXInBytes;
 * \endcode
 *
 * \par
 * For CUDA arrays, ::dstXInBytes must be evenly divisible by the array
 * element size.
 *
 * - ::WidthInBytes and ::Height specify the width (in bytes) and height of
 *   the 2D copy being performed.
 * - If specified, ::srcPitch must be greater than or equal to ::WidthInBytes +
 *   ::srcXInBytes, and ::dstPitch must be greater than or equal to
 *   ::WidthInBytes + dstXInBytes.
 *
 * \par
 * ::cuMemcpy2D() returns an error if any pitch is greater than the maximum
 * allowed (::CU_DEVICE_ATTRIBUTE_MAX_PITCH). ::cuMemAllocPitch() passes back
 * pitches that always work with ::cuMemcpy2D(). On intra-device memory copies
 * (device to device, CUDA array to device, CUDA array to CUDA array),
 * ::cuMemcpy2D() may fail for pitches not computed by ::cuMemAllocPitch().
 * ::cuMemcpy2DUnaligned() does not have this restriction, but may run
 * significantly slower in the cases where ::cuMemcpy2D() would have returned
 * an error code.
 *
 * \param pCopy - Parameters for the memory copy
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 * \note_sync
 *
 * \sa ::cuArray3DCreate, ::cuArray3DGetDescriptor, ::cuArrayCreate,
 * ::cuArrayDestroy, ::cuArrayGetDescriptor, ::cuMemAlloc, ::cuMemAllocHost,
 * ::cuMemAllocPitch, ::cuMemcpy2D, ::cuMemcpy2DAsync,
 * ::cuMemcpy3D, ::cuMemcpy3DAsync, ::cuMemcpyAtoA, ::cuMemcpyAtoD,
 * ::cuMemcpyAtoH, ::cuMemcpyAtoHAsync, ::cuMemcpyDtoA, ::cuMemcpyDtoD, ::cuMemcpyDtoDAsync,
 * ::cuMemcpyDtoH, ::cuMemcpyDtoHAsync, ::cuMemcpyHtoA, ::cuMemcpyHtoAAsync,
 * ::cuMemcpyHtoD, ::cuMemcpyHtoDAsync, ::cuMemFree, ::cuMemFreeHost,
 * ::cuMemGetAddressRange, ::cuMemGetInfo, ::cuMemHostAlloc,
 * ::cuMemHostGetDevicePointer, ::cuMemsetD2D8, ::cuMemsetD2D16,
 * ::cuMemsetD2D32, ::cuMemsetD8, ::cuMemsetD16, ::cuMemsetD32,
 * ::cudaMemcpy2D,
 * ::cudaMemcpy2DToArray,
 * ::cudaMemcpy2DFromArray
 */
CUresult CUDAAPI cuMemcpy2DUnaligned(const CUDA_MEMCPY2D *pCopy);

/**
 * \brief Copies memory for 3D arrays
 *
 * Perform a 3D memory copy according to the parameters specified in
 * \p pCopy. The ::CUDA_MEMCPY3D structure is defined as:
 *
 * \code
        typedef struct CUDA_MEMCPY3D_st {

            unsigned int srcXInBytes, srcY, srcZ;
            unsigned int srcLOD;
            CUmemorytype srcMemoryType;
                const void *srcHost;
                CUdeviceptr srcDevice;
                CUarray srcArray;
                unsigned int srcPitch;  // ignored when src is array
                unsigned int srcHeight; // ignored when src is array; may be 0 if Depth==1

            unsigned int dstXInBytes, dstY, dstZ;
            unsigned int dstLOD;
            CUmemorytype dstMemoryType;
                void *dstHost;
                CUdeviceptr dstDevice;
                CUarray dstArray;
                unsigned int dstPitch;  // ignored when dst is array
                unsigned int dstHeight; // ignored when dst is array; may be 0 if Depth==1

            unsigned int WidthInBytes;
            unsigned int Height;
            unsigned int Depth;
        } CUDA_MEMCPY3D;
 * \endcode
 * where:
 * - ::srcMemoryType and ::dstMemoryType specify the type of memory of the
 *   source and destination, respectively; ::CUmemorytype_enum is defined as:
 *
 * \code
   typedef enum CUmemorytype_enum {
      CU_MEMORYTYPE_HOST = 0x01,
      CU_MEMORYTYPE_DEVICE = 0x02,
      CU_MEMORYTYPE_ARRAY = 0x03,
      CU_MEMORYTYPE_UNIFIED = 0x04
   } CUmemorytype;
 * \endcode
 *
 * \par
 * If ::srcMemoryType is ::CU_MEMORYTYPE_UNIFIED, ::srcDevice and ::srcPitch
 *   specify the (unified virtual address space) base address of the source data
 *   and the bytes per row to apply.  ::srcArray is ignored.
 * This value may be used only if unified addressing is supported in the calling
 *   context.
 *
 * \par
 * If ::srcMemoryType is ::CU_MEMORYTYPE_HOST, ::srcHost, ::srcPitch and
 * ::srcHeight specify the (host) base address of the source data, the bytes
 * per row, and the height of each 2D slice of the 3D array. ::srcArray is
 * ignored.
 *
 * \par
 * If ::srcMemoryType is ::CU_MEMORYTYPE_DEVICE, ::srcDevice, ::srcPitch and
 * ::srcHeight specify the (device) base address of the source data, the bytes
 * per row, and the height of each 2D slice of the 3D array. ::srcArray is
 * ignored.
 *
 * \par
 * If ::srcMemoryType is ::CU_MEMORYTYPE_ARRAY, ::srcArray specifies the
 * handle of the source data. ::srcHost, ::srcDevice, ::srcPitch and
 * ::srcHeight are ignored.
 *
 * \par
 * If ::dstMemoryType is ::CU_MEMORYTYPE_UNIFIED, ::dstDevice and ::dstPitch
 *   specify the (unified virtual address space) base address of the source data
 *   and the bytes per row to apply.  ::dstArray is ignored.
 * This value may be used only if unified addressing is supported in the calling
 *   context.
 *
 * \par
 * If ::dstMemoryType is ::CU_MEMORYTYPE_HOST, ::dstHost and ::dstPitch
 * specify the (host) base address of the destination data, the bytes per row,
 * and the height of each 2D slice of the 3D array. ::dstArray is ignored.
 *
 * \par
 * If ::dstMemoryType is ::CU_MEMORYTYPE_DEVICE, ::dstDevice and ::dstPitch
 * specify the (device) base address of the destination data, the bytes per
 * row, and the height of each 2D slice of the 3D array. ::dstArray is ignored.
 *
 * \par
 * If ::dstMemoryType is ::CU_MEMORYTYPE_ARRAY, ::dstArray specifies the
 * handle of the destination data. ::dstHost, ::dstDevice, ::dstPitch and
 * ::dstHeight are ignored.
 *
 * - ::srcXInBytes, ::srcY and ::srcZ specify the base address of the source
 *   data for the copy.
 *
 * \par
 * For host pointers, the starting address is
 * \code
  void* Start = (void*)((char*)srcHost+(srcZ*srcHeight+srcY)*srcPitch + srcXInBytes);
 * \endcode
 *
 * \par
 * For device pointers, the starting address is
 * \code
  CUdeviceptr Start = srcDevice+(srcZ*srcHeight+srcY)*srcPitch+srcXInBytes;
 * \endcode
 *
 * \par
 * For CUDA arrays, ::srcXInBytes must be evenly divisible by the array
 * element size.
 *
 * - dstXInBytes, ::dstY and ::dstZ specify the base address of the
 *   destination data for the copy.
 *
 * \par
 * For host pointers, the base address is
 * \code
  void* dstStart = (void*)((char*)dstHost+(dstZ*dstHeight+dstY)*dstPitch + dstXInBytes);
 * \endcode
 *
 * \par
 * For device pointers, the starting address is
 * \code
  CUdeviceptr dstStart = dstDevice+(dstZ*dstHeight+dstY)*dstPitch+dstXInBytes;
 * \endcode
 *
 * \par
 * For CUDA arrays, ::dstXInBytes must be evenly divisible by the array
 * element size.
 *
 * - ::WidthInBytes, ::Height and ::Depth specify the width (in bytes), height
 *   and depth of the 3D copy being performed.
 * - If specified, ::srcPitch must be greater than or equal to ::WidthInBytes +
 *   ::srcXInBytes, and ::dstPitch must be greater than or equal to
 *   ::WidthInBytes + dstXInBytes.
 * - If specified, ::srcHeight must be greater than or equal to ::Height +
 *   ::srcY, and ::dstHeight must be greater than or equal to ::Height + ::dstY.
 *
 * \par
 * ::cuMemcpy3D() returns an error if any pitch is greater than the maximum
 * allowed (::CU_DEVICE_ATTRIBUTE_MAX_PITCH).
 *
 * The ::srcLOD and ::dstLOD members of the ::CUDA_MEMCPY3D structure must be
 * set to 0.
 *
 * \param pCopy - Parameters for the memory copy
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 * \note_sync
 *
 * \sa ::cuArray3DCreate, ::cuArray3DGetDescriptor, ::cuArrayCreate,
 * ::cuArrayDestroy, ::cuArrayGetDescriptor, ::cuMemAlloc, ::cuMemAllocHost,
 * ::cuMemAllocPitch, ::cuMemcpy2D, ::cuMemcpy2DAsync, ::cuMemcpy2DUnaligned,
 * ::cuMemcpy3DAsync, ::cuMemcpyAtoA, ::cuMemcpyAtoD,
 * ::cuMemcpyAtoH, ::cuMemcpyAtoHAsync, ::cuMemcpyDtoA, ::cuMemcpyDtoD, ::cuMemcpyDtoDAsync,
 * ::cuMemcpyDtoH, ::cuMemcpyDtoHAsync, ::cuMemcpyHtoA, ::cuMemcpyHtoAAsync,
 * ::cuMemcpyHtoD, ::cuMemcpyHtoDAsync, ::cuMemFree, ::cuMemFreeHost,
 * ::cuMemGetAddressRange, ::cuMemGetInfo, ::cuMemHostAlloc,
 * ::cuMemHostGetDevicePointer, ::cuMemsetD2D8, ::cuMemsetD2D16,
 * ::cuMemsetD2D32, ::cuMemsetD8, ::cuMemsetD16, ::cuMemsetD32,
 * ::cudaMemcpy3D
 */
CUresult CUDAAPI cuMemcpy3D(const CUDA_MEMCPY3D *pCopy);

/**
 * \brief Copies memory between contexts
 *
 * Perform a 3D memory copy according to the parameters specified in
 * \p pCopy.  See the definition of the ::CUDA_MEMCPY3D_PEER structure
 * for documentation of its parameters.
 *
 * \param pCopy - Parameters for the memory copy
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 * \note_sync
 *
 * \sa ::cuMemcpyDtoD, ::cuMemcpyPeer, ::cuMemcpyDtoDAsync, ::cuMemcpyPeerAsync,
 * ::cuMemcpy3DPeerAsync,
 * ::cudaMemcpy3DPeer
 */
CUresult CUDAAPI cuMemcpy3DPeer(const CUDA_MEMCPY3D_PEER *pCopy);

/**
 * \brief Copies memory asynchronously
 *
 * Copies data between two pointers.
 * \p dst and \p src are base pointers of the destination and source, respectively.
 * \p ByteCount specifies the number of bytes to copy.
 * Note that this function infers the type of the transfer (host to host, host to
 *   device, device to device, or device to host) from the pointer values.  This
 *   function is only allowed in contexts which support unified addressing.
 *
 * \param dst       - Destination unified virtual address space pointer
 * \param src       - Source unified virtual address space pointer
 * \param ByteCount - Size of memory copy in bytes
 * \param hStream   - Stream identifier
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_HANDLE
 * \notefnerr
 * \note_async
 * \note_null_stream
 * \note_memcpy
 *
 * \sa ::cuArray3DCreate, ::cuArray3DGetDescriptor, ::cuArrayCreate,
 * ::cuArrayDestroy, ::cuArrayGetDescriptor, ::cuMemAlloc, ::cuMemAllocHost,
 * ::cuMemAllocPitch, ::cuMemcpy2D, ::cuMemcpy2DAsync, ::cuMemcpy2DUnaligned,
 * ::cuMemcpy3D, ::cuMemcpy3DAsync, ::cuMemcpyAtoA, ::cuMemcpyAtoD,
 * ::cuMemcpyAtoH, ::cuMemcpyAtoHAsync, ::cuMemcpyDtoA, ::cuMemcpyDtoD,
 * ::cuMemcpyDtoH, ::cuMemcpyDtoHAsync, ::cuMemcpyHtoA, ::cuMemcpyHtoAAsync,
 * ::cuMemcpyHtoD, ::cuMemcpyHtoDAsync, ::cuMemFree, ::cuMemFreeHost,
 * ::cuMemGetAddressRange, ::cuMemGetInfo, ::cuMemHostAlloc,
 * ::cuMemHostGetDevicePointer, ::cuMemsetD2D8, ::cuMemsetD2D8Async,
 * ::cuMemsetD2D16, ::cuMemsetD2D16Async, ::cuMemsetD2D32, ::cuMemsetD2D32Async,
 * ::cuMemsetD8, ::cuMemsetD8Async, ::cuMemsetD16, ::cuMemsetD16Async,
 * ::cuMemsetD32, ::cuMemsetD32Async,
 * ::cudaMemcpyAsync,
 * ::cudaMemcpyToSymbolAsync,
 * ::cudaMemcpyFromSymbolAsync
 */
CUresult CUDAAPI cuMemcpyAsync(CUdeviceptr dst, CUdeviceptr src, size_t ByteCount, CUstream hStream);

/**
 * \brief Copies device memory between two contexts asynchronously.
 *
 * Copies from device memory in one context to device memory in another
 * context. \p dstDevice is the base device pointer of the destination memory
 * and \p dstContext is the destination context.  \p srcDevice is the base
 * device pointer of the source memory and \p srcContext is the source pointer.
 * \p ByteCount specifies the number of bytes to copy.
 *
 * \param dstDevice  - Destination device pointer
 * \param dstContext - Destination context
 * \param srcDevice  - Source device pointer
 * \param srcContext - Source context
 * \param ByteCount  - Size of memory copy in bytes
 * \param hStream    - Stream identifier
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_HANDLE
 * \notefnerr
 * \note_async
 * \note_null_stream
 *
 * \sa ::cuMemcpyDtoD, ::cuMemcpyPeer, ::cuMemcpy3DPeer, ::cuMemcpyDtoDAsync,
 * ::cuMemcpy3DPeerAsync,
 * ::cudaMemcpyPeerAsync
 */
CUresult CUDAAPI cuMemcpyPeerAsync(CUdeviceptr dstDevice, CUcontext dstContext, CUdeviceptr srcDevice, CUcontext srcContext, size_t ByteCount, CUstream hStream);

/**
 * \brief Copies memory from Host to Device
 *
 * Copies from host memory to device memory. \p dstDevice and \p srcHost are
 * the base addresses of the destination and source, respectively. \p ByteCount
 * specifies the number of bytes to copy.
 *
 * \param dstDevice - Destination device pointer
 * \param srcHost   - Source host pointer
 * \param ByteCount - Size of memory copy in bytes
 * \param hStream   - Stream identifier
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_HANDLE
 * \notefnerr
 * \note_async
 * \note_null_stream
 * \note_memcpy
 *
 * \sa ::cuArray3DCreate, ::cuArray3DGetDescriptor, ::cuArrayCreate,
 * ::cuArrayDestroy, ::cuArrayGetDescriptor, ::cuMemAlloc, ::cuMemAllocHost,
 * ::cuMemAllocPitch, ::cuMemcpy2D, ::cuMemcpy2DAsync, ::cuMemcpy2DUnaligned,
 * ::cuMemcpy3D, ::cuMemcpy3DAsync, ::cuMemcpyAtoA, ::cuMemcpyAtoD,
 * ::cuMemcpyAtoH, ::cuMemcpyAtoHAsync, ::cuMemcpyDtoA, ::cuMemcpyDtoD, ::cuMemcpyDtoDAsync,
 * ::cuMemcpyDtoH, ::cuMemcpyDtoHAsync, ::cuMemcpyHtoA, ::cuMemcpyHtoAAsync,
 * ::cuMemcpyHtoD, ::cuMemFree, ::cuMemFreeHost,
 * ::cuMemGetAddressRange, ::cuMemGetInfo, ::cuMemHostAlloc,
 * ::cuMemHostGetDevicePointer, ::cuMemsetD2D8, ::cuMemsetD2D8Async,
 * ::cuMemsetD2D16, ::cuMemsetD2D16Async, ::cuMemsetD2D32, ::cuMemsetD2D32Async,
 * ::cuMemsetD8, ::cuMemsetD8Async, ::cuMemsetD16, ::cuMemsetD16Async,
 * ::cuMemsetD32, ::cuMemsetD32Async,
 * ::cudaMemcpyAsync,
 * ::cudaMemcpyToSymbolAsync
 */
CUresult CUDAAPI cuMemcpyHtoDAsync(CUdeviceptr dstDevice, const void *srcHost, size_t ByteCount, CUstream hStream);

/**
 * \brief Copies memory from Device to Host
 *
 * Copies from device to host memory. \p dstHost and \p srcDevice specify the
 * base pointers of the destination and source, respectively. \p ByteCount
 * specifies the number of bytes to copy.
 *
 * \param dstHost   - Destination host pointer
 * \param srcDevice - Source device pointer
 * \param ByteCount - Size of memory copy in bytes
 * \param hStream   - Stream identifier
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_HANDLE
 * \notefnerr
 * \note_async
 * \note_null_stream
 * \note_memcpy
 *
 * \sa ::cuArray3DCreate, ::cuArray3DGetDescriptor, ::cuArrayCreate,
 * ::cuArrayDestroy, ::cuArrayGetDescriptor, ::cuMemAlloc, ::cuMemAllocHost,
 * ::cuMemAllocPitch, ::cuMemcpy2D, ::cuMemcpy2DAsync, ::cuMemcpy2DUnaligned,
 * ::cuMemcpy3D, ::cuMemcpy3DAsync, ::cuMemcpyAtoA, ::cuMemcpyAtoD,
 * ::cuMemcpyAtoH, ::cuMemcpyAtoHAsync, ::cuMemcpyDtoA, ::cuMemcpyDtoD, ::cuMemcpyDtoDAsync,
 * ::cuMemcpyDtoH, ::cuMemcpyHtoA, ::cuMemcpyHtoAAsync,
 * ::cuMemcpyHtoD, ::cuMemcpyHtoDAsync, ::cuMemFree, ::cuMemFreeHost,
 * ::cuMemGetAddressRange, ::cuMemGetInfo, ::cuMemHostAlloc,
 * ::cuMemHostGetDevicePointer, ::cuMemsetD2D8, ::cuMemsetD2D8Async,
 * ::cuMemsetD2D16, ::cuMemsetD2D16Async, ::cuMemsetD2D32, ::cuMemsetD2D32Async,
 * ::cuMemsetD8, ::cuMemsetD8Async, ::cuMemsetD16, ::cuMemsetD16Async,
 * ::cuMemsetD32, ::cuMemsetD32Async,
 * ::cudaMemcpyAsync,
 * ::cudaMemcpyFromSymbolAsync
 */
CUresult CUDAAPI cuMemcpyDtoHAsync(void *dstHost, CUdeviceptr srcDevice, size_t ByteCount, CUstream hStream);

/**
 * \brief Copies memory from Device to Device
 *
 * Copies from device memory to device memory. \p dstDevice and \p srcDevice
 * are the base pointers of the destination and source, respectively.
 * \p ByteCount specifies the number of bytes to copy.
 *
 * \param dstDevice - Destination device pointer
 * \param srcDevice - Source device pointer
 * \param ByteCount - Size of memory copy in bytes
 * \param hStream   - Stream identifier
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_HANDLE
 * \notefnerr
 * \note_async
 * \note_null_stream
 *
 * \sa ::cuArray3DCreate, ::cuArray3DGetDescriptor, ::cuArrayCreate,
 * ::cuArrayDestroy, ::cuArrayGetDescriptor, ::cuMemAlloc, ::cuMemAllocHost,
 * ::cuMemAllocPitch, ::cuMemcpy2D, ::cuMemcpy2DAsync, ::cuMemcpy2DUnaligned,
 * ::cuMemcpy3D, ::cuMemcpy3DAsync, ::cuMemcpyAtoA, ::cuMemcpyAtoD,
 * ::cuMemcpyAtoH, ::cuMemcpyAtoHAsync, ::cuMemcpyDtoA, ::cuMemcpyDtoD,
 * ::cuMemcpyDtoH, ::cuMemcpyDtoHAsync, ::cuMemcpyHtoA, ::cuMemcpyHtoAAsync,
 * ::cuMemcpyHtoD, ::cuMemcpyHtoDAsync, ::cuMemFree, ::cuMemFreeHost,
 * ::cuMemGetAddressRange, ::cuMemGetInfo, ::cuMemHostAlloc,
 * ::cuMemHostGetDevicePointer, ::cuMemsetD2D8, ::cuMemsetD2D8Async,
 * ::cuMemsetD2D16, ::cuMemsetD2D16Async, ::cuMemsetD2D32, ::cuMemsetD2D32Async,
 * ::cuMemsetD8, ::cuMemsetD8Async, ::cuMemsetD16, ::cuMemsetD16Async,
 * ::cuMemsetD32, ::cuMemsetD32Async,
 * ::cudaMemcpyAsync,
 * ::cudaMemcpyToSymbolAsync,
 * ::cudaMemcpyFromSymbolAsync
 */
CUresult CUDAAPI cuMemcpyDtoDAsync(CUdeviceptr dstDevice, CUdeviceptr srcDevice, size_t ByteCount, CUstream hStream);

/**
 * \brief Copies memory from Host to Array
 *
 * Copies from host memory to a 1D CUDA array. \p dstArray and \p dstOffset
 * specify the CUDA array handle and starting offset in bytes of the
 * destination data. \p srcHost specifies the base address of the source.
 * \p ByteCount specifies the number of bytes to copy.
 *
 * \param dstArray  - Destination array
 * \param dstOffset - Offset in bytes of destination array
 * \param srcHost   - Source host pointer
 * \param ByteCount - Size of memory copy in bytes
 * \param hStream   - Stream identifier
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_HANDLE
 * \notefnerr
 * \note_async
 * \note_null_stream
 * \note_memcpy
 *
 * \sa ::cuArray3DCreate, ::cuArray3DGetDescriptor, ::cuArrayCreate,
 * ::cuArrayDestroy, ::cuArrayGetDescriptor, ::cuMemAlloc, ::cuMemAllocHost,
 * ::cuMemAllocPitch, ::cuMemcpy2D, ::cuMemcpy2DAsync, ::cuMemcpy2DUnaligned,
 * ::cuMemcpy3D, ::cuMemcpy3DAsync, ::cuMemcpyAtoA, ::cuMemcpyAtoD,
 * ::cuMemcpyAtoH, ::cuMemcpyAtoHAsync, ::cuMemcpyDtoA, ::cuMemcpyDtoD, ::cuMemcpyDtoDAsync,
 * ::cuMemcpyDtoH, ::cuMemcpyDtoHAsync, ::cuMemcpyHtoA,
 * ::cuMemcpyHtoD, ::cuMemcpyHtoDAsync, ::cuMemFree, ::cuMemFreeHost,
 * ::cuMemGetAddressRange, ::cuMemGetInfo, ::cuMemHostAlloc,
 * ::cuMemHostGetDevicePointer, ::cuMemsetD2D8, ::cuMemsetD2D8Async,
 * ::cuMemsetD2D16, ::cuMemsetD2D16Async, ::cuMemsetD2D32, ::cuMemsetD2D32Async,
 * ::cuMemsetD8, ::cuMemsetD8Async, ::cuMemsetD16, ::cuMemsetD16Async,
 * ::cuMemsetD32, ::cuMemsetD32Async,
 * ::cudaMemcpyToArrayAsync
 */
CUresult CUDAAPI cuMemcpyHtoAAsync(CUarray dstArray, size_t dstOffset, const void *srcHost, size_t ByteCount, CUstream hStream);

/**
 * \brief Copies memory from Array to Host
 *
 * Copies from one 1D CUDA array to host memory. \p dstHost specifies the base
 * pointer of the destination. \p srcArray and \p srcOffset specify the CUDA
 * array handle and starting offset in bytes of the source data.
 * \p ByteCount specifies the number of bytes to copy.
 *
 * \param dstHost   - Destination pointer
 * \param srcArray  - Source array
 * \param srcOffset - Offset in bytes of source array
 * \param ByteCount - Size of memory copy in bytes
 * \param hStream   - Stream identifier
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_HANDLE
 * \notefnerr
 * \note_async
 * \note_null_stream
 * \note_memcpy
 *
 * \sa ::cuArray3DCreate, ::cuArray3DGetDescriptor, ::cuArrayCreate,
 * ::cuArrayDestroy, ::cuArrayGetDescriptor, ::cuMemAlloc, ::cuMemAllocHost,
 * ::cuMemAllocPitch, ::cuMemcpy2D, ::cuMemcpy2DAsync, ::cuMemcpy2DUnaligned,
 * ::cuMemcpy3D, ::cuMemcpy3DAsync, ::cuMemcpyAtoA, ::cuMemcpyAtoD,
 * ::cuMemcpyAtoH, ::cuMemcpyDtoA, ::cuMemcpyDtoD, ::cuMemcpyDtoDAsync,
 * ::cuMemcpyDtoH, ::cuMemcpyDtoHAsync, ::cuMemcpyHtoA, ::cuMemcpyHtoAAsync,
 * ::cuMemcpyHtoD, ::cuMemcpyHtoDAsync, ::cuMemFree, ::cuMemFreeHost,
 * ::cuMemGetAddressRange, ::cuMemGetInfo, ::cuMemHostAlloc,
 * ::cuMemHostGetDevicePointer, ::cuMemsetD2D8, ::cuMemsetD2D8Async,
 * ::cuMemsetD2D16, ::cuMemsetD2D16Async, ::cuMemsetD2D32, ::cuMemsetD2D32Async,
 * ::cuMemsetD8, ::cuMemsetD8Async, ::cuMemsetD16, ::cuMemsetD16Async,
 * ::cuMemsetD32, ::cuMemsetD32Async,
 * ::cudaMemcpyFromArrayAsync
 */
CUresult CUDAAPI cuMemcpyAtoHAsync(void *dstHost, CUarray srcArray, size_t srcOffset, size_t ByteCount, CUstream hStream);

/**
 * \brief Copies memory for 2D arrays
 *
 * Perform a 2D memory copy according to the parameters specified in \p pCopy.
 * The ::CUDA_MEMCPY2D structure is defined as:
 *
 * \code
   typedef struct CUDA_MEMCPY2D_st {
      unsigned int srcXInBytes, srcY;
      CUmemorytype srcMemoryType;
      const void *srcHost;
      CUdeviceptr srcDevice;
      CUarray srcArray;
      unsigned int srcPitch;
      unsigned int dstXInBytes, dstY;
      CUmemorytype dstMemoryType;
      void *dstHost;
      CUdeviceptr dstDevice;
      CUarray dstArray;
      unsigned int dstPitch;
      unsigned int WidthInBytes;
      unsigned int Height;
   } CUDA_MEMCPY2D;
 * \endcode
 * where:
 * - ::srcMemoryType and ::dstMemoryType specify the type of memory of the
 *   source and destination, respectively; ::CUmemorytype_enum is defined as:
 *
 * \code
   typedef enum CUmemorytype_enum {
      CU_MEMORYTYPE_HOST = 0x01,
      CU_MEMORYTYPE_DEVICE = 0x02,
      CU_MEMORYTYPE_ARRAY = 0x03,
      CU_MEMORYTYPE_UNIFIED = 0x04
   } CUmemorytype;
 * \endcode
 *
 * \par
 * If ::srcMemoryType is ::CU_MEMORYTYPE_HOST, ::srcHost and ::srcPitch
 * specify the (host) base address of the source data and the bytes per row to
 * apply. ::srcArray is ignored.
 *
 * \par
 * If ::srcMemoryType is ::CU_MEMORYTYPE_UNIFIED, ::srcDevice and ::srcPitch
 *   specify the (unified virtual address space) base address of the source data
 *   and the bytes per row to apply.  ::srcArray is ignored.
 * This value may be used only if unified addressing is supported in the calling
 *   context.
 *
 * \par
 * If ::srcMemoryType is ::CU_MEMORYTYPE_DEVICE, ::srcDevice and ::srcPitch
 * specify the (device) base address of the source data and the bytes per row
 * to apply. ::srcArray is ignored.
 *
 * \par
 * If ::srcMemoryType is ::CU_MEMORYTYPE_ARRAY, ::srcArray specifies the
 * handle of the source data. ::srcHost, ::srcDevice and ::srcPitch are
 * ignored.
 *
 * \par
 * If ::dstMemoryType is ::CU_MEMORYTYPE_UNIFIED, ::dstDevice and ::dstPitch
 *   specify the (unified virtual address space) base address of the source data
 *   and the bytes per row to apply.  ::dstArray is ignored.
 * This value may be used only if unified addressing is supported in the calling
 *   context.
 *
 * \par
 * If ::dstMemoryType is ::CU_MEMORYTYPE_HOST, ::dstHost and ::dstPitch
 * specify the (host) base address of the destination data and the bytes per
 * row to apply. ::dstArray is ignored.
 *
 * \par
 * If ::dstMemoryType is ::CU_MEMORYTYPE_DEVICE, ::dstDevice and ::dstPitch
 * specify the (device) base address of the destination data and the bytes per
 * row to apply. ::dstArray is ignored.
 *
 * \par
 * If ::dstMemoryType is ::CU_MEMORYTYPE_ARRAY, ::dstArray specifies the
 * handle of the destination data. ::dstHost, ::dstDevice and ::dstPitch are
 * ignored.
 *
 * - ::srcXInBytes and ::srcY specify the base address of the source data for
 *   the copy.
 *
 * \par
 * For host pointers, the starting address is
 * \code
  void* Start = (void*)((char*)srcHost+srcY*srcPitch + srcXInBytes);
 * \endcode
 *
 * \par
 * For device pointers, the starting address is
 * \code
  CUdeviceptr Start = srcDevice+srcY*srcPitch+srcXInBytes;
 * \endcode
 *
 * \par
 * For CUDA arrays, ::srcXInBytes must be evenly divisible by the array
 * element size.
 *
 * - ::dstXInBytes and ::dstY specify the base address of the destination data
 *   for the copy.
 *
 * \par
 * For host pointers, the base address is
 * \code
  void* dstStart = (void*)((char*)dstHost+dstY*dstPitch + dstXInBytes);
 * \endcode
 *
 * \par
 * For device pointers, the starting address is
 * \code
  CUdeviceptr dstStart = dstDevice+dstY*dstPitch+dstXInBytes;
 * \endcode
 *
 * \par
 * For CUDA arrays, ::dstXInBytes must be evenly divisible by the array
 * element size.
 *
 * - ::WidthInBytes and ::Height specify the width (in bytes) and height of
 *   the 2D copy being performed.
 * - If specified, ::srcPitch must be greater than or equal to ::WidthInBytes +
 *   ::srcXInBytes, and ::dstPitch must be greater than or equal to
 *   ::WidthInBytes + dstXInBytes.
 * - If specified, ::srcPitch must be greater than or equal to ::WidthInBytes +
 *   ::srcXInBytes, and ::dstPitch must be greater than or equal to
 *   ::WidthInBytes + dstXInBytes.
 * - If specified, ::srcHeight must be greater than or equal to ::Height +
 *   ::srcY, and ::dstHeight must be greater than or equal to ::Height + ::dstY.
 *
 * \par
 * ::cuMemcpy2DAsync() returns an error if any pitch is greater than the maximum
 * allowed (::CU_DEVICE_ATTRIBUTE_MAX_PITCH). ::cuMemAllocPitch() passes back
 * pitches that always work with ::cuMemcpy2D(). On intra-device memory copies
 * (device to device, CUDA array to device, CUDA array to CUDA array),
 * ::cuMemcpy2DAsync() may fail for pitches not computed by ::cuMemAllocPitch().
 *
 * \param pCopy   - Parameters for the memory copy
 * \param hStream - Stream identifier
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_HANDLE
 * \notefnerr
 * \note_async
 * \note_null_stream
 *
 * \sa ::cuArray3DCreate, ::cuArray3DGetDescriptor, ::cuArrayCreate,
 * ::cuArrayDestroy, ::cuArrayGetDescriptor, ::cuMemAlloc, ::cuMemAllocHost,
 * ::cuMemAllocPitch, ::cuMemcpy2D, ::cuMemcpy2DUnaligned,
 * ::cuMemcpy3D, ::cuMemcpy3DAsync, ::cuMemcpyAtoA, ::cuMemcpyAtoD,
 * ::cuMemcpyAtoH, ::cuMemcpyAtoHAsync, ::cuMemcpyDtoA, ::cuMemcpyDtoD, ::cuMemcpyDtoDAsync,
 * ::cuMemcpyDtoH, ::cuMemcpyDtoHAsync, ::cuMemcpyHtoA, ::cuMemcpyHtoAAsync,
 * ::cuMemcpyHtoD, ::cuMemcpyHtoDAsync, ::cuMemFree, ::cuMemFreeHost,
 * ::cuMemGetAddressRange, ::cuMemGetInfo, ::cuMemHostAlloc,
 * ::cuMemHostGetDevicePointer, ::cuMemsetD2D8, ::cuMemsetD2D8Async,
 * ::cuMemsetD2D16, ::cuMemsetD2D16Async, ::cuMemsetD2D32, ::cuMemsetD2D32Async,
 * ::cuMemsetD8, ::cuMemsetD8Async, ::cuMemsetD16, ::cuMemsetD16Async,
 * ::cuMemsetD32, ::cuMemsetD32Async,
 * ::cudaMemcpy2DAsync,
 * ::cudaMemcpy2DToArrayAsync,
 * ::cudaMemcpy2DFromArrayAsync
 */
CUresult CUDAAPI cuMemcpy2DAsync(const CUDA_MEMCPY2D *pCopy, CUstream hStream);

/**
 * \brief Copies memory for 3D arrays
 *
 * Perform a 3D memory copy according to the parameters specified in
 * \p pCopy. The ::CUDA_MEMCPY3D structure is defined as:
 *
 * \code
        typedef struct CUDA_MEMCPY3D_st {

            unsigned int srcXInBytes, srcY, srcZ;
            unsigned int srcLOD;
            CUmemorytype srcMemoryType;
                const void *srcHost;
                CUdeviceptr srcDevice;
                CUarray srcArray;
                unsigned int srcPitch;  // ignored when src is array
                unsigned int srcHeight; // ignored when src is array; may be 0 if Depth==1

            unsigned int dstXInBytes, dstY, dstZ;
            unsigned int dstLOD;
            CUmemorytype dstMemoryType;
                void *dstHost;
                CUdeviceptr dstDevice;
                CUarray dstArray;
                unsigned int dstPitch;  // ignored when dst is array
                unsigned int dstHeight; // ignored when dst is array; may be 0 if Depth==1

            unsigned int WidthInBytes;
            unsigned int Height;
            unsigned int Depth;
        } CUDA_MEMCPY3D;
 * \endcode
 * where:
 * - ::srcMemoryType and ::dstMemoryType specify the type of memory of the
 *   source and destination, respectively; ::CUmemorytype_enum is defined as:
 *
 * \code
   typedef enum CUmemorytype_enum {
      CU_MEMORYTYPE_HOST = 0x01,
      CU_MEMORYTYPE_DEVICE = 0x02,
      CU_MEMORYTYPE_ARRAY = 0x03,
      CU_MEMORYTYPE_UNIFIED = 0x04
   } CUmemorytype;
 * \endcode
 *
 * \par
 * If ::srcMemoryType is ::CU_MEMORYTYPE_UNIFIED, ::srcDevice and ::srcPitch
 *   specify the (unified virtual address space) base address of the source data
 *   and the bytes per row to apply.  ::srcArray is ignored.
 * This value may be used only if unified addressing is supported in the calling
 *   context.
 *
 * \par
 * If ::srcMemoryType is ::CU_MEMORYTYPE_HOST, ::srcHost, ::srcPitch and
 * ::srcHeight specify the (host) base address of the source data, the bytes
 * per row, and the height of each 2D slice of the 3D array. ::srcArray is
 * ignored.
 *
 * \par
 * If ::srcMemoryType is ::CU_MEMORYTYPE_DEVICE, ::srcDevice, ::srcPitch and
 * ::srcHeight specify the (device) base address of the source data, the bytes
 * per row, and the height of each 2D slice of the 3D array. ::srcArray is
 * ignored.
 *
 * \par
 * If ::srcMemoryType is ::CU_MEMORYTYPE_ARRAY, ::srcArray specifies the
 * handle of the source data. ::srcHost, ::srcDevice, ::srcPitch and
 * ::srcHeight are ignored.
 *
 * \par
 * If ::dstMemoryType is ::CU_MEMORYTYPE_UNIFIED, ::dstDevice and ::dstPitch
 *   specify the (unified virtual address space) base address of the source data
 *   and the bytes per row to apply.  ::dstArray is ignored.
 * This value may be used only if unified addressing is supported in the calling
 *   context.
 *
 * \par
 * If ::dstMemoryType is ::CU_MEMORYTYPE_HOST, ::dstHost and ::dstPitch
 * specify the (host) base address of the destination data, the bytes per row,
 * and the height of each 2D slice of the 3D array. ::dstArray is ignored.
 *
 * \par
 * If ::dstMemoryType is ::CU_MEMORYTYPE_DEVICE, ::dstDevice and ::dstPitch
 * specify the (device) base address of the destination data, the bytes per
 * row, and the height of each 2D slice of the 3D array. ::dstArray is ignored.
 *
 * \par
 * If ::dstMemoryType is ::CU_MEMORYTYPE_ARRAY, ::dstArray specifies the
 * handle of the destination data. ::dstHost, ::dstDevice, ::dstPitch and
 * ::dstHeight are ignored.
 *
 * - ::srcXInBytes, ::srcY and ::srcZ specify the base address of the source
 *   data for the copy.
 *
 * \par
 * For host pointers, the starting address is
 * \code
  void* Start = (void*)((char*)srcHost+(srcZ*srcHeight+srcY)*srcPitch + srcXInBytes);
 * \endcode
 *
 * \par
 * For device pointers, the starting address is
 * \code
  CUdeviceptr Start = srcDevice+(srcZ*srcHeight+srcY)*srcPitch+srcXInBytes;
 * \endcode
 *
 * \par
 * For CUDA arrays, ::srcXInBytes must be evenly divisible by the array
 * element size.
 *
 * - dstXInBytes, ::dstY and ::dstZ specify the base address of the
 *   destination data for the copy.
 *
 * \par
 * For host pointers, the base address is
 * \code
  void* dstStart = (void*)((char*)dstHost+(dstZ*dstHeight+dstY)*dstPitch + dstXInBytes);
 * \endcode
 *
 * \par
 * For device pointers, the starting address is
 * \code
  CUdeviceptr dstStart = dstDevice+(dstZ*dstHeight+dstY)*dstPitch+dstXInBytes;
 * \endcode
 *
 * \par
 * For CUDA arrays, ::dstXInBytes must be evenly divisible by the array
 * element size.
 *
 * - ::WidthInBytes, ::Height and ::Depth specify the width (in bytes), height
 *   and depth of the 3D copy being performed.
 * - If specified, ::srcPitch must be greater than or equal to ::WidthInBytes +
 *   ::srcXInBytes, and ::dstPitch must be greater than or equal to
 *   ::WidthInBytes + dstXInBytes.
 * - If specified, ::srcHeight must be greater than or equal to ::Height +
 *   ::srcY, and ::dstHeight must be greater than or equal to ::Height + ::dstY.
 *
 * \par
 * ::cuMemcpy3DAsync() returns an error if any pitch is greater than the maximum
 * allowed (::CU_DEVICE_ATTRIBUTE_MAX_PITCH).
 *
 * The ::srcLOD and ::dstLOD members of the ::CUDA_MEMCPY3D structure must be
 * set to 0.
 *
 * \param pCopy - Parameters for the memory copy
 * \param hStream - Stream identifier
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_HANDLE
 * \notefnerr
 * \note_async
 * \note_null_stream
 *
 * \sa ::cuArray3DCreate, ::cuArray3DGetDescriptor, ::cuArrayCreate,
 * ::cuArrayDestroy, ::cuArrayGetDescriptor, ::cuMemAlloc, ::cuMemAllocHost,
 * ::cuMemAllocPitch, ::cuMemcpy2D, ::cuMemcpy2DAsync, ::cuMemcpy2DUnaligned,
 * ::cuMemcpy3D, ::cuMemcpyAtoA, ::cuMemcpyAtoD,
 * ::cuMemcpyAtoH, ::cuMemcpyAtoHAsync, ::cuMemcpyDtoA, ::cuMemcpyDtoD, ::cuMemcpyDtoDAsync,
 * ::cuMemcpyDtoH, ::cuMemcpyDtoHAsync, ::cuMemcpyHtoA, ::cuMemcpyHtoAAsync,
 * ::cuMemcpyHtoD, ::cuMemcpyHtoDAsync, ::cuMemFree, ::cuMemFreeHost,
 * ::cuMemGetAddressRange, ::cuMemGetInfo, ::cuMemHostAlloc,
 * ::cuMemHostGetDevicePointer, ::cuMemsetD2D8, ::cuMemsetD2D8Async,
 * ::cuMemsetD2D16, ::cuMemsetD2D16Async, ::cuMemsetD2D32, ::cuMemsetD2D32Async,
 * ::cuMemsetD8, ::cuMemsetD8Async, ::cuMemsetD16, ::cuMemsetD16Async,
 * ::cuMemsetD32, ::cuMemsetD32Async,
 * ::cudaMemcpy3DAsync
 */
CUresult CUDAAPI cuMemcpy3DAsync(const CUDA_MEMCPY3D *pCopy, CUstream hStream);

/**
 * \brief Copies memory between contexts asynchronously.
 *
 * Perform a 3D memory copy according to the parameters specified in
 * \p pCopy.  See the definition of the ::CUDA_MEMCPY3D_PEER structure
 * for documentation of its parameters.
 *
 * \param pCopy - Parameters for the memory copy
 * \param hStream - Stream identifier
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 * \note_async
 * \note_null_stream
 *
 * \sa ::cuMemcpyDtoD, ::cuMemcpyPeer, ::cuMemcpyDtoDAsync, ::cuMemcpyPeerAsync,
 * ::cuMemcpy3DPeerAsync,
 * ::cudaMemcpy3DPeerAsync
 */
CUresult CUDAAPI cuMemcpy3DPeerAsync(const CUDA_MEMCPY3D_PEER *pCopy, CUstream hStream);

/**
 * \brief Performs a batch of memory copies asynchronously.
 *
 * Performs a batch of memory copies. The batch as a whole executes in stream order but copies within a
 * batch are not guaranteed to execute in any specific order. This API only supports pointer-to-pointer copies.
 * For copies involving CUDA arrays, please see ::cuMemcpy3DBatchAsync.
 *
 * Performs memory copies from source buffers specified in \p srcs to destination buffers specified in \p dsts.
 * The size of each copy is specified in \p sizes. All three arrays must be of the same length as specified
 * by \p count. Since there are no ordering guarantees for copies within a batch, specifying any dependent copies
 * within a batch will result in undefined behavior.
 *
 * Every copy in the batch has to be associated with a set of attributes specified in the \p attrs array.
 * Each entry in this array can apply to more than one copy. This can be done by specifying in the \p attrsIdxs array,
 * the index of the first copy that the corresponding entry in the \p attrs array applies to. Both \p attrs and
 * \p attrsIdxs must be of the same length as specified by \p numAttrs. For example, if a batch has 10 copies listed
 * in dst/src/sizes, the first 6 of which have one set of attributes and the remaining 4 another, then \p numAttrs
 * will be 2, \p attrsIdxs will be {0, 6} and \p attrs will contains the two sets of attributes. Note that the first entry
 * in \p attrsIdxs must always be 0. Also, each entry must be greater than the previous entry and the last entry should be
 * less than \p count. Furthermore, \p numAttrs must be lesser than or equal to \p count.
 *
 * The ::CUmemcpyAttributes::srcAccessOrder indicates the source access ordering to be observed for copies associated
 * with the attribute. If the source access order is set to ::CU_MEMCPY_SRC_ACCESS_ORDER_STREAM, then the source will
 * be accessed in stream order. If the source access order is set to ::CU_MEMCPY_SRC_ACCESS_ORDER_DURING_API_CALL then
 * it indicates that access to the source pointer can be out of stream order and all accesses must be complete before
 * the API call returns. This flag is suited for ephemeral sources (ex., stack variables) when it's known that no prior
 * operations in the stream can be accessing the memory and also that the lifetime of the memory is limited to the scope
 * that the source variable was declared in. Specifying this flag allows the driver to optimize the copy and removes the
 * need for the user to synchronize the stream after the API call. If the source access order is set to
 * ::CU_MEMCPY_SRC_ACCESS_ORDER_ANY then it indicates that access to the source pointer can be out of stream order and the
 * accesses can happen even after the API call returns. This flag is suited for host pointers allocated
 * outside CUDA (ex., via malloc) when it's known that no prior operations in the stream can be accessing the memory.
 * Specifying this flag allows the driver to optimize the copy on certain platforms. Each memcpy operation in the batch must
 * have a valid ::CUmemcpyAttributes corresponding to it including the appropriate srcAccessOrder setting, otherwise the API
 * will return ::CUDA_ERROR_INVALID_VALUE.
 *
 * The ::CUmemcpyAttributes::srcLocHint and ::CUmemcpyAttributes::dstLocHint allows applications to specify hint locations
 * for operands of a copy when the operand doesn't have a fixed location. That is, these hints are
 * only applicable for managed memory pointers on devices where ::CU_DEVICE_ATTRIBUTE_CONCURRENT_MANAGED_ACCESS is true or
 * system-allocated pageable memory on devices where ::CU_DEVICE_ATTRIBUTE_PAGEABLE_MEMORY_ACCESS is true.
 * For other cases, these hints are ignored.
 *
 * The ::CUmemcpyAttributes::flags field can be used to specify certain flags for copies. Setting the
 * ::CU_MEMCPY_FLAG_PREFER_OVERLAP_WITH_COMPUTE flag indicates that the associated copies should preferably overlap with
 * any compute work. Note that this flag is a hint and can be ignored depending on the platform and other parameters of the copy.
 *
 * If any error is encountered while parsing the batch, the index within the batch where the error was encountered
 * will be returned in \p failIdx. 
 *
 * \param dsts          - Array of destination pointers.
 * \param srcs          - Array of memcpy source pointers.
 * \param sizes         - Array of sizes for memcpy operations.
 * \param count         - Size of \p dsts, \p srcs and \p sizes arrays
 * \param attrs         - Array of memcpy attributes. 
 * \param attrsIdxs     - Array of indices to specify which copies each entry in the \p attrs array applies to.
                          The attributes specified in attrs[k] will be applied to copies starting from attrsIdxs[k]
                          through attrsIdxs[k+1] - 1. Also attrs[numAttrs-1] will apply to copies starting from
                          attrsIdxs[numAttrs-1] through count - 1.
 * \param numAttrs      - Size of \p attrs and \p attrsIdxs arrays.
 * \param failIdx       - Pointer to a location to return the index of the copy where a failure was encountered.
                          The value will be SIZE_MAX if the error doesn't pertain to any specific copy.
 * \param hStream       - The stream to enqueue the operations in. Must not be legacy NULL stream.
 *
 * \return
 * ::CUDA_SUCCESS
 * ::CUDA_ERROR_DEINITIALIZED
 * ::CUDA_ERROR_NOT_INITIALIZED
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 * \note_async
 * \note_memcpy
 */
CUresult CUDAAPI cuMemcpyBatchAsync(CUdeviceptr *dsts, CUdeviceptr *srcs, size_t *sizes, size_t count,
                                    CUmemcpyAttributes *attrs, size_t *attrsIdxs, size_t numAttrs,
                                    size_t *failIdx, CUstream hStream);

/**
 * \brief Performs a batch of 3D memory copies asynchronously.
 *
 * Performs a batch of memory copies. The batch as a whole executes in stream order but copies within a
 * batch are not guaranteed to execute in any specific order. Note that this means specifying any dependent
 * copies within a batch will result in undefined behavior.
 *
 * Performs memory copies as specified in the \p opList array. The length of this array is specified in \p numOps.
 * Each entry in this array describes a copy operation. This includes among other things, the source and destination
 * operands for the copy as specified in ::CUDA_MEMCPY3D_BATCH_OP::src and ::CUDA_MEMCPY3D_BATCH_OP::dst respectively.
 * The source and destination operands of a copy can either be a pointer or a CUDA array. The width, height and depth
 * of a copy is specified in ::CUDA_MEMCPY3D_BATCH_OP::extent. The width, height and depth of a copy are specified in
 * elements and must not be zero. For pointer-to-pointer copies, the element size is considered to be 1. For pointer
 * to CUDA array or vice versa copies, the element size is determined by the CUDA array. For CUDA array to CUDA array copies,
 * the element size of the two CUDA arrays must match.
 *
 * For a given operand, if ::CUmemcpy3DOperand::type is specified as ::CU_MEMCPY_OPERAND_TYPE_POINTER, then
 * ::CUmemcpy3DOperand::op::ptr will be used. The ::CUmemcpy3DOperand::op::ptr::ptr field must contain the pointer where
 * the copy should begin. The ::CUmemcpy3DOperand::op::ptr::rowLength field specifies the length of each row in elements and
 * must either be zero or be greater than or equal to the width of the copy specified in ::CUDA_MEMCPY3D_BATCH_OP::extent::width.
 * The ::CUmemcpy3DOperand::op::ptr::layerHeight field specifies the height of each layer and must either be zero or be greater than
 * or equal to the height of the copy specified in ::CUDA_MEMCPY3D_BATCH_OP::extent::height. When either of these values is zero,
 * that aspect of the operand is considered to be tightly packed according to the copy extent. For managed memory pointers on devices where
 * ::CU_DEVICE_ATTRIBUTE_CONCURRENT_MANAGED_ACCESS is true or system-allocated pageable memory on devices where
 * ::CU_DEVICE_ATTRIBUTE_PAGEABLE_MEMORY_ACCESS is true, the ::CUmemcpy3DOperand::op::ptr::locHint field can be used to hint
 * the location of the operand.
 *
 * If an operand's type is specified as ::CU_MEMCPY_OPERAND_TYPE_ARRAY, then ::CUmemcpy3DOperand::op::array will be used.
 * The ::CUmemcpy3DOperand::op::array::array field specifies the CUDA array and ::CUmemcpy3DOperand::op::array::offset specifies
 * the 3D offset into that array where the copy begins.
 *
 * The ::CUmemcpyAttributes::srcAccessOrder indicates the source access ordering to be observed for copies associated
 * with the attribute. If the source access order is set to ::CU_MEMCPY_SRC_ACCESS_ORDER_STREAM, then the source will
 * be accessed in stream order. If the source access order is set to ::CU_MEMCPY_SRC_ACCESS_ORDER_DURING_API_CALL then
 * it indicates that access to the source pointer can be out of stream order and all accesses must be complete before
 * the API call returns. This flag is suited for ephemeral sources (ex., stack variables) when it's known that no prior
 * operations in the stream can be accessing the memory and also that the lifetime of the memory is limited to the scope
 * that the source variable was declared in. Specifying this flag allows the driver to optimize the copy and removes the
 * need for the user to synchronize the stream after the API call. If the source access order is set to
 * ::CU_MEMCPY_SRC_ACCESS_ORDER_ANY then it indicates that access to the source pointer can be out of stream order and the
 * accesses can happen even after the API call returns. This flag is suited for host pointers allocated
 * outside CUDA (ex., via malloc) when it's known that no prior operations in the stream can be accessing the memory.
 * Specifying this flag allows the driver to optimize the copy on certain platforms. Each memcopy operation in \p opList must
 * have a valid srcAccessOrder setting, otherwise this API will return ::CUDA_ERROR_INVALID_VALUE.
 *
 * The ::CUmemcpyAttributes::flags field can be used to specify certain flags for copies. Setting the
 * ::CU_MEMCPY_FLAG_PREFER_OVERLAP_WITH_COMPUTE flag indicates that the associated copies should preferably overlap with
 * any compute work. Note that this flag is a hint and can be ignored depending on the platform and other parameters of the copy.
 *
 * If any error is encountered while parsing the batch, the index within the batch where the error was encountered
 * will be returned in \p failIdx. 
 *
 * \param numOps     - Total number of memcpy operations. 
 * \param opList     - Array of size \p numOps containing the actual memcpy operations. 
 * \param failIdx    - Pointer to a location to return the index of the copy where a failure was encountered.
 *                     The value will be SIZE_MAX if the error doesn't pertain to any specific copy.
 * \param flags      - Flags for future use, must be zero now.
 * \param hStream    - The stream to enqueue the operations in. Must not be default NULL stream.
 *
 * \return
 * ::CUDA_SUCCESS
 * ::CUDA_ERROR_DEINITIALIZED
 * ::CUDA_ERROR_NOT_INITIALIZED
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 * \note_async
 * \note_memcpy
 */
CUresult CUDAAPI cuMemcpy3DBatchAsync(size_t numOps, CUDA_MEMCPY3D_BATCH_OP *opList,
                                      size_t *failIdx, unsigned long long flags, CUstream hStream);

/**
 * \brief Initializes device memory
 *
 * Sets the memory range of \p N 8-bit values to the specified value
 * \p uc.
 *
 * \param dstDevice - Destination device pointer
 * \param uc        - Value to set
 * \param N         - Number of elements
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 * \note_memset
 *
 * \sa ::cuArray3DCreate, ::cuArray3DGetDescriptor, ::cuArrayCreate,
 * ::cuArrayDestroy, ::cuArrayGetDescriptor, ::cuMemAlloc, ::cuMemAllocHost,
 * ::cuMemAllocPitch, ::cuMemcpy2D, ::cuMemcpy2DAsync, ::cuMemcpy2DUnaligned,
 * ::cuMemcpy3D, ::cuMemcpy3DAsync, ::cuMemcpyAtoA, ::cuMemcpyAtoD,
 * ::cuMemcpyAtoH, ::cuMemcpyAtoHAsync, ::cuMemcpyDtoA, ::cuMemcpyDtoD, ::cuMemcpyDtoDAsync,
 * ::cuMemcpyDtoH, ::cuMemcpyDtoHAsync, ::cuMemcpyHtoA, ::cuMemcpyHtoAAsync,
 * ::cuMemcpyHtoD, ::cuMemcpyHtoDAsync, ::cuMemFree, ::cuMemFreeHost,
 * ::cuMemGetAddressRange, ::cuMemGetInfo, ::cuMemHostAlloc,
 * ::cuMemHostGetDevicePointer, ::cuMemsetD2D8, ::cuMemsetD2D8Async,
 * ::cuMemsetD2D16, ::cuMemsetD2D16Async, ::cuMemsetD2D32, ::cuMemsetD2D32Async,
 * ::cuMemsetD8Async, ::cuMemsetD16, ::cuMemsetD16Async,
 * ::cuMemsetD32, ::cuMemsetD32Async,
 * ::cudaMemset
 */
CUresult CUDAAPI cuMemsetD8(CUdeviceptr dstDevice, unsigned char uc, size_t N);

/**
 * \brief Initializes device memory
 *
 * Sets the memory range of \p N 16-bit values to the specified value
 * \p us. The \p dstDevice pointer must be two byte aligned.
 *
 * \param dstDevice - Destination device pointer
 * \param us        - Value to set
 * \param N         - Number of elements
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 * \note_memset
 *
 * \sa ::cuArray3DCreate, ::cuArray3DGetDescriptor, ::cuArrayCreate,
 * ::cuArrayDestroy, ::cuArrayGetDescriptor, ::cuMemAlloc, ::cuMemAllocHost,
 * ::cuMemAllocPitch, ::cuMemcpy2D, ::cuMemcpy2DAsync, ::cuMemcpy2DUnaligned,
 * ::cuMemcpy3D, ::cuMemcpy3DAsync, ::cuMemcpyAtoA, ::cuMemcpyAtoD,
 * ::cuMemcpyAtoH, ::cuMemcpyAtoHAsync, ::cuMemcpyDtoA, ::cuMemcpyDtoD, ::cuMemcpyDtoDAsync,
 * ::cuMemcpyDtoH, ::cuMemcpyDtoHAsync, ::cuMemcpyHtoA, ::cuMemcpyHtoAAsync,
 * ::cuMemcpyHtoD, ::cuMemcpyHtoDAsync, ::cuMemFree, ::cuMemFreeHost,
 * ::cuMemGetAddressRange, ::cuMemGetInfo, ::cuMemHostAlloc,
 * ::cuMemHostGetDevicePointer, ::cuMemsetD2D8, ::cuMemsetD2D8Async,
 * ::cuMemsetD2D16, ::cuMemsetD2D16Async, ::cuMemsetD2D32, ::cuMemsetD2D32Async,
 * ::cuMemsetD8, ::cuMemsetD8Async, ::cuMemsetD16Async,
 * ::cuMemsetD32, ::cuMemsetD32Async,
 * ::cudaMemset
 */
CUresult CUDAAPI cuMemsetD16(CUdeviceptr dstDevice, unsigned short us, size_t N);

/**
 * \brief Initializes device memory
 *
 * Sets the memory range of \p N 32-bit values to the specified value
 * \p ui. The \p dstDevice pointer must be four byte aligned.
 *
 * \param dstDevice - Destination device pointer
 * \param ui        - Value to set
 * \param N         - Number of elements
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 * \note_memset
 *
 * \sa ::cuArray3DCreate, ::cuArray3DGetDescriptor, ::cuArrayCreate,
 * ::cuArrayDestroy, ::cuArrayGetDescriptor, ::cuMemAlloc, ::cuMemAllocHost,
 * ::cuMemAllocPitch, ::cuMemcpy2D, ::cuMemcpy2DAsync, ::cuMemcpy2DUnaligned,
 * ::cuMemcpy3D, ::cuMemcpy3DAsync, ::cuMemcpyAtoA, ::cuMemcpyAtoD,
 * ::cuMemcpyAtoH, ::cuMemcpyAtoHAsync, ::cuMemcpyDtoA, ::cuMemcpyDtoD, ::cuMemcpyDtoDAsync,
 * ::cuMemcpyDtoH, ::cuMemcpyDtoHAsync, ::cuMemcpyHtoA, ::cuMemcpyHtoAAsync,
 * ::cuMemcpyHtoD, ::cuMemcpyHtoDAsync, ::cuMemFree, ::cuMemFreeHost,
 * ::cuMemGetAddressRange, ::cuMemGetInfo, ::cuMemHostAlloc,
 * ::cuMemHostGetDevicePointer, ::cuMemsetD2D8, ::cuMemsetD2D8Async,
 * ::cuMemsetD2D16, ::cuMemsetD2D16Async, ::cuMemsetD2D32, ::cuMemsetD2D32Async,
 * ::cuMemsetD8, ::cuMemsetD8Async, ::cuMemsetD16, ::cuMemsetD16Async,
 * ::cuMemsetD32Async,
 * ::cudaMemset
 */
CUresult CUDAAPI cuMemsetD32(CUdeviceptr dstDevice, unsigned int ui, size_t N);

/**
 * \brief Initializes device memory
 *
 * Sets the 2D memory range of \p Width 8-bit values to the specified value
 * \p uc. \p Height specifies the number of rows to set, and \p dstPitch
 * specifies the number of bytes between each row. This function performs
 * fastest when the pitch is one that has been passed back by
 * ::cuMemAllocPitch().
 *
 * \param dstDevice - Destination device pointer
 * \param dstPitch  - Pitch of destination device pointer(Unused if \p Height is 1)
 * \param uc        - Value to set
 * \param Width     - Width of row
 * \param Height    - Number of rows
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 * \note_memset
 *
 * \sa ::cuArray3DCreate, ::cuArray3DGetDescriptor, ::cuArrayCreate,
 * ::cuArrayDestroy, ::cuArrayGetDescriptor, ::cuMemAlloc, ::cuMemAllocHost,
 * ::cuMemAllocPitch, ::cuMemcpy2D, ::cuMemcpy2DAsync, ::cuMemcpy2DUnaligned,
 * ::cuMemcpy3D, ::cuMemcpy3DAsync, ::cuMemcpyAtoA, ::cuMemcpyAtoD,
 * ::cuMemcpyAtoH, ::cuMemcpyAtoHAsync, ::cuMemcpyDtoA, ::cuMemcpyDtoD, ::cuMemcpyDtoDAsync,
 * ::cuMemcpyDtoH, ::cuMemcpyDtoHAsync, ::cuMemcpyHtoA, ::cuMemcpyHtoAAsync,
 * ::cuMemcpyHtoD, ::cuMemcpyHtoDAsync, ::cuMemFree, ::cuMemFreeHost,
 * ::cuMemGetAddressRange, ::cuMemGetInfo, ::cuMemHostAlloc,
 * ::cuMemHostGetDevicePointer, ::cuMemsetD2D8Async,
 * ::cuMemsetD2D16, ::cuMemsetD2D16Async, ::cuMemsetD2D32, ::cuMemsetD2D32Async,
 * ::cuMemsetD8, ::cuMemsetD8Async, ::cuMemsetD16, ::cuMemsetD16Async,
 * ::cuMemsetD32, ::cuMemsetD32Async,
 * ::cudaMemset2D
 */
CUresult CUDAAPI cuMemsetD2D8(CUdeviceptr dstDevice, size_t dstPitch, unsigned char uc, size_t Width, size_t Height);

/**
 * \brief Initializes device memory
 *
 * Sets the 2D memory range of \p Width 16-bit values to the specified value
 * \p us. \p Height specifies the number of rows to set, and \p dstPitch
 * specifies the number of bytes between each row. The \p dstDevice pointer
 * and \p dstPitch offset must be two byte aligned. This function performs
 * fastest when the pitch is one that has been passed back by
 * ::cuMemAllocPitch().
 *
 * \param dstDevice - Destination device pointer
 * \param dstPitch  - Pitch of destination device pointer(Unused if \p Height is 1)
 * \param us        - Value to set
 * \param Width     - Width of row
 * \param Height    - Number of rows
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 * \note_memset
 *
 * \sa ::cuArray3DCreate, ::cuArray3DGetDescriptor, ::cuArrayCreate,
 * ::cuArrayDestroy, ::cuArrayGetDescriptor, ::cuMemAlloc, ::cuMemAllocHost,
 * ::cuMemAllocPitch, ::cuMemcpy2D, ::cuMemcpy2DAsync, ::cuMemcpy2DUnaligned,
 * ::cuMemcpy3D, ::cuMemcpy3DAsync, ::cuMemcpyAtoA, ::cuMemcpyAtoD,
 * ::cuMemcpyAtoH, ::cuMemcpyAtoHAsync, ::cuMemcpyDtoA, ::cuMemcpyDtoD, ::cuMemcpyDtoDAsync,
 * ::cuMemcpyDtoH, ::cuMemcpyDtoHAsync, ::cuMemcpyHtoA, ::cuMemcpyHtoAAsync,
 * ::cuMemcpyHtoD, ::cuMemcpyHtoDAsync, ::cuMemFree, ::cuMemFreeHost,
 * ::cuMemGetAddressRange, ::cuMemGetInfo, ::cuMemHostAlloc,
 * ::cuMemHostGetDevicePointer, ::cuMemsetD2D8, ::cuMemsetD2D8Async,
 * ::cuMemsetD2D16Async, ::cuMemsetD2D32, ::cuMemsetD2D32Async,
 * ::cuMemsetD8, ::cuMemsetD8Async, ::cuMemsetD16, ::cuMemsetD16Async,
 * ::cuMemsetD32, ::cuMemsetD32Async,
 * ::cudaMemset2D
 */
CUresult CUDAAPI cuMemsetD2D16(CUdeviceptr dstDevice, size_t dstPitch, unsigned short us, size_t Width, size_t Height);

/**
 * \brief Initializes device memory
 *
 * Sets the 2D memory range of \p Width 32-bit values to the specified value
 * \p ui. \p Height specifies the number of rows to set, and \p dstPitch
 * specifies the number of bytes between each row. The \p dstDevice pointer
 * and \p dstPitch offset must be four byte aligned. This function performs
 * fastest when the pitch is one that has been passed back by
 * ::cuMemAllocPitch().
 *
 * \param dstDevice - Destination device pointer
 * \param dstPitch  - Pitch of destination device pointer(Unused if \p Height is 1)
 * \param ui        - Value to set
 * \param Width     - Width of row
 * \param Height    - Number of rows
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 * \note_memset
 *
 * \sa ::cuArray3DCreate, ::cuArray3DGetDescriptor, ::cuArrayCreate,
 * ::cuArrayDestroy, ::cuArrayGetDescriptor, ::cuMemAlloc, ::cuMemAllocHost,
 * ::cuMemAllocPitch, ::cuMemcpy2D, ::cuMemcpy2DAsync, ::cuMemcpy2DUnaligned,
 * ::cuMemcpy3D, ::cuMemcpy3DAsync, ::cuMemcpyAtoA, ::cuMemcpyAtoD,
 * ::cuMemcpyAtoH, ::cuMemcpyAtoHAsync, ::cuMemcpyDtoA, ::cuMemcpyDtoD, ::cuMemcpyDtoDAsync,
 * ::cuMemcpyDtoH, ::cuMemcpyDtoHAsync, ::cuMemcpyHtoA, ::cuMemcpyHtoAAsync,
 * ::cuMemcpyHtoD, ::cuMemcpyHtoDAsync, ::cuMemFree, ::cuMemFreeHost,
 * ::cuMemGetAddressRange, ::cuMemGetInfo, ::cuMemHostAlloc,
 * ::cuMemHostGetDevicePointer, ::cuMemsetD2D8, ::cuMemsetD2D8Async,
 * ::cuMemsetD2D16, ::cuMemsetD2D16Async, ::cuMemsetD2D32Async,
 * ::cuMemsetD8, ::cuMemsetD8Async, ::cuMemsetD16, ::cuMemsetD16Async,
 * ::cuMemsetD32, ::cuMemsetD32Async,
 * ::cudaMemset2D
 */
CUresult CUDAAPI cuMemsetD2D32(CUdeviceptr dstDevice, size_t dstPitch, unsigned int ui, size_t Width, size_t Height);

/**
 * \brief Sets device memory
 *
 * Sets the memory range of \p N 8-bit values to the specified value
 * \p uc.
 *
 * \param dstDevice - Destination device pointer
 * \param uc        - Value to set
 * \param N         - Number of elements
 * \param hStream   - Stream identifier
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 * \note_memset
 * \note_null_stream
 *
 * \sa ::cuArray3DCreate, ::cuArray3DGetDescriptor, ::cuArrayCreate,
 * ::cuArrayDestroy, ::cuArrayGetDescriptor, ::cuMemAlloc, ::cuMemAllocHost,
 * ::cuMemAllocPitch, ::cuMemcpy2D, ::cuMemcpy2DAsync, ::cuMemcpy2DUnaligned,
 * ::cuMemcpy3D, ::cuMemcpy3DAsync, ::cuMemcpyAtoA, ::cuMemcpyAtoD,
 * ::cuMemcpyAtoH, ::cuMemcpyAtoHAsync, ::cuMemcpyDtoA, ::cuMemcpyDtoD, ::cuMemcpyDtoDAsync,
 * ::cuMemcpyDtoH, ::cuMemcpyDtoHAsync, ::cuMemcpyHtoA, ::cuMemcpyHtoAAsync,
 * ::cuMemcpyHtoD, ::cuMemcpyHtoDAsync, ::cuMemFree, ::cuMemFreeHost,
 * ::cuMemGetAddressRange, ::cuMemGetInfo, ::cuMemHostAlloc,
 * ::cuMemHostGetDevicePointer, ::cuMemsetD2D8, ::cuMemsetD2D8Async,
 * ::cuMemsetD2D16, ::cuMemsetD2D16Async, ::cuMemsetD2D32, ::cuMemsetD2D32Async,
 * ::cuMemsetD8, ::cuMemsetD16, ::cuMemsetD16Async,
 * ::cuMemsetD32, ::cuMemsetD32Async,
 * ::cudaMemsetAsync
 */
CUresult CUDAAPI cuMemsetD8Async(CUdeviceptr dstDevice, unsigned char uc, size_t N, CUstream hStream);

/**
 * \brief Sets device memory
 *
 * Sets the memory range of \p N 16-bit values to the specified value
 * \p us. The \p dstDevice pointer must be two byte aligned.
 *
 * \param dstDevice - Destination device pointer
 * \param us        - Value to set
 * \param N         - Number of elements
 * \param hStream   - Stream identifier
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 * \note_memset
 * \note_null_stream
 *
 * \sa ::cuArray3DCreate, ::cuArray3DGetDescriptor, ::cuArrayCreate,
 * ::cuArrayDestroy, ::cuArrayGetDescriptor, ::cuMemAlloc, ::cuMemAllocHost,
 * ::cuMemAllocPitch, ::cuMemcpy2D, ::cuMemcpy2DAsync, ::cuMemcpy2DUnaligned,
 * ::cuMemcpy3D, ::cuMemcpy3DAsync, ::cuMemcpyAtoA, ::cuMemcpyAtoD,
 * ::cuMemcpyAtoH, ::cuMemcpyAtoHAsync, ::cuMemcpyDtoA, ::cuMemcpyDtoD, ::cuMemcpyDtoDAsync,
 * ::cuMemcpyDtoH, ::cuMemcpyDtoHAsync, ::cuMemcpyHtoA, ::cuMemcpyHtoAAsync,
 * ::cuMemcpyHtoD, ::cuMemcpyHtoDAsync, ::cuMemFree, ::cuMemFreeHost,
 * ::cuMemGetAddressRange, ::cuMemGetInfo, ::cuMemHostAlloc,
 * ::cuMemHostGetDevicePointer, ::cuMemsetD2D8, ::cuMemsetD2D8Async,
 * ::cuMemsetD2D16, ::cuMemsetD2D16Async, ::cuMemsetD2D32, ::cuMemsetD2D32Async,
 * ::cuMemsetD8, ::cuMemsetD8Async, ::cuMemsetD16,
 * ::cuMemsetD32, ::cuMemsetD32Async,
 * ::cudaMemsetAsync
 */
CUresult CUDAAPI cuMemsetD16Async(CUdeviceptr dstDevice, unsigned short us, size_t N, CUstream hStream);

/**
 * \brief Sets device memory
 *
 * Sets the memory range of \p N 32-bit values to the specified value
 * \p ui. The \p dstDevice pointer must be four byte aligned.
 *
 * \param dstDevice - Destination device pointer
 * \param ui        - Value to set
 * \param N         - Number of elements
 * \param hStream   - Stream identifier
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 * \note_memset
 * \note_null_stream
 *
 * \sa ::cuArray3DCreate, ::cuArray3DGetDescriptor, ::cuArrayCreate,
 * ::cuArrayDestroy, ::cuArrayGetDescriptor, ::cuMemAlloc, ::cuMemAllocHost,
 * ::cuMemAllocPitch, ::cuMemcpy2D, ::cuMemcpy2DAsync, ::cuMemcpy2DUnaligned,
 * ::cuMemcpy3D, ::cuMemcpy3DAsync, ::cuMemcpyAtoA, ::cuMemcpyAtoD,
 * ::cuMemcpyAtoH, ::cuMemcpyAtoHAsync, ::cuMemcpyDtoA, ::cuMemcpyDtoD, ::cuMemcpyDtoDAsync,
 * ::cuMemcpyDtoH, ::cuMemcpyDtoHAsync, ::cuMemcpyHtoA, ::cuMemcpyHtoAAsync,
 * ::cuMemcpyHtoD, ::cuMemcpyHtoDAsync, ::cuMemFree, ::cuMemFreeHost,
 * ::cuMemGetAddressRange, ::cuMemGetInfo, ::cuMemHostAlloc,
 * ::cuMemHostGetDevicePointer, ::cuMemsetD2D8, ::cuMemsetD2D8Async,
 * ::cuMemsetD2D16, ::cuMemsetD2D16Async, ::cuMemsetD2D32, ::cuMemsetD2D32Async,
 * ::cuMemsetD8, ::cuMemsetD8Async, ::cuMemsetD16, ::cuMemsetD16Async, ::cuMemsetD32,
 * ::cudaMemsetAsync
 */
CUresult CUDAAPI cuMemsetD32Async(CUdeviceptr dstDevice, unsigned int ui, size_t N, CUstream hStream);

/**
 * \brief Sets device memory
 *
 * Sets the 2D memory range of \p Width 8-bit values to the specified value
 * \p uc. \p Height specifies the number of rows to set, and \p dstPitch
 * specifies the number of bytes between each row. This function performs
 * fastest when the pitch is one that has been passed back by
 * ::cuMemAllocPitch().
 *
 * \param dstDevice - Destination device pointer
 * \param dstPitch  - Pitch of destination device pointer(Unused if \p Height is 1)
 * \param uc        - Value to set
 * \param Width     - Width of row
 * \param Height    - Number of rows
 * \param hStream   - Stream identifier
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 * \note_memset
 * \note_null_stream
 *
 * \sa ::cuArray3DCreate, ::cuArray3DGetDescriptor, ::cuArrayCreate,
 * ::cuArrayDestroy, ::cuArrayGetDescriptor, ::cuMemAlloc, ::cuMemAllocHost,
 * ::cuMemAllocPitch, ::cuMemcpy2D, ::cuMemcpy2DAsync, ::cuMemcpy2DUnaligned,
 * ::cuMemcpy3D, ::cuMemcpy3DAsync, ::cuMemcpyAtoA, ::cuMemcpyAtoD,
 * ::cuMemcpyAtoH, ::cuMemcpyAtoHAsync, ::cuMemcpyDtoA, ::cuMemcpyDtoD, ::cuMemcpyDtoDAsync,
 * ::cuMemcpyDtoH, ::cuMemcpyDtoHAsync, ::cuMemcpyHtoA, ::cuMemcpyHtoAAsync,
 * ::cuMemcpyHtoD, ::cuMemcpyHtoDAsync, ::cuMemFree, ::cuMemFreeHost,
 * ::cuMemGetAddressRange, ::cuMemGetInfo, ::cuMemHostAlloc,
 * ::cuMemHostGetDevicePointer, ::cuMemsetD2D8,
 * ::cuMemsetD2D16, ::cuMemsetD2D16Async, ::cuMemsetD2D32, ::cuMemsetD2D32Async,
 * ::cuMemsetD8, ::cuMemsetD8Async, ::cuMemsetD16, ::cuMemsetD16Async,
 * ::cuMemsetD32, ::cuMemsetD32Async,
 * ::cudaMemset2DAsync
 */
CUresult CUDAAPI cuMemsetD2D8Async(CUdeviceptr dstDevice, size_t dstPitch, unsigned char uc, size_t Width, size_t Height, CUstream hStream);

/**
 * \brief Sets device memory
 *
 * Sets the 2D memory range of \p Width 16-bit values to the specified value
 * \p us. \p Height specifies the number of rows to set, and \p dstPitch
 * specifies the number of bytes between each row. The \p dstDevice pointer
 * and \p dstPitch offset must be two byte aligned. This function performs
 * fastest when the pitch is one that has been passed back by
 * ::cuMemAllocPitch().
 *
 * \param dstDevice - Destination device pointer
 * \param dstPitch  - Pitch of destination device pointer(Unused if \p Height is 1)
 * \param us        - Value to set
 * \param Width     - Width of row
 * \param Height    - Number of rows
 * \param hStream   - Stream identifier
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 * \note_memset
 * \note_null_stream
 *
 * \sa ::cuArray3DCreate, ::cuArray3DGetDescriptor, ::cuArrayCreate,
 * ::cuArrayDestroy, ::cuArrayGetDescriptor, ::cuMemAlloc, ::cuMemAllocHost,
 * ::cuMemAllocPitch, ::cuMemcpy2D, ::cuMemcpy2DAsync, ::cuMemcpy2DUnaligned,
 * ::cuMemcpy3D, ::cuMemcpy3DAsync, ::cuMemcpyAtoA, ::cuMemcpyAtoD,
 * ::cuMemcpyAtoH, ::cuMemcpyAtoHAsync, ::cuMemcpyDtoA, ::cuMemcpyDtoD, ::cuMemcpyDtoDAsync,
 * ::cuMemcpyDtoH, ::cuMemcpyDtoHAsync, ::cuMemcpyHtoA, ::cuMemcpyHtoAAsync,
 * ::cuMemcpyHtoD, ::cuMemcpyHtoDAsync, ::cuMemFree, ::cuMemFreeHost,
 * ::cuMemGetAddressRange, ::cuMemGetInfo, ::cuMemHostAlloc,
 * ::cuMemHostGetDevicePointer, ::cuMemsetD2D8, ::cuMemsetD2D8Async,
 * ::cuMemsetD2D16, ::cuMemsetD2D32, ::cuMemsetD2D32Async,
 * ::cuMemsetD8, ::cuMemsetD8Async, ::cuMemsetD16, ::cuMemsetD16Async,
 * ::cuMemsetD32, ::cuMemsetD32Async,
 * ::cudaMemset2DAsync
 */
CUresult CUDAAPI cuMemsetD2D16Async(CUdeviceptr dstDevice, size_t dstPitch, unsigned short us, size_t Width, size_t Height, CUstream hStream);

/**
 * \brief Sets device memory
 *
 * Sets the 2D memory range of \p Width 32-bit values to the specified value
 * \p ui. \p Height specifies the number of rows to set, and \p dstPitch
 * specifies the number of bytes between each row. The \p dstDevice pointer
 * and \p dstPitch offset must be four byte aligned. This function performs
 * fastest when the pitch is one that has been passed back by
 * ::cuMemAllocPitch().
 *
 * \param dstDevice - Destination device pointer
 * \param dstPitch  - Pitch of destination device pointer(Unused if \p Height is 1)
 * \param ui        - Value to set
 * \param Width     - Width of row
 * \param Height    - Number of rows
 * \param hStream   - Stream identifier
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 * \note_memset
 * \note_null_stream
 *
 * \sa ::cuArray3DCreate, ::cuArray3DGetDescriptor, ::cuArrayCreate,
 * ::cuArrayDestroy, ::cuArrayGetDescriptor, ::cuMemAlloc, ::cuMemAllocHost,
 * ::cuMemAllocPitch, ::cuMemcpy2D, ::cuMemcpy2DAsync, ::cuMemcpy2DUnaligned,
 * ::cuMemcpy3D, ::cuMemcpy3DAsync, ::cuMemcpyAtoA, ::cuMemcpyAtoD,
 * ::cuMemcpyAtoH, ::cuMemcpyAtoHAsync, ::cuMemcpyDtoA, ::cuMemcpyDtoD, ::cuMemcpyDtoDAsync,
 * ::cuMemcpyDtoH, ::cuMemcpyDtoHAsync, ::cuMemcpyHtoA, ::cuMemcpyHtoAAsync,
 * ::cuMemcpyHtoD, ::cuMemcpyHtoDAsync, ::cuMemFree, ::cuMemFreeHost,
 * ::cuMemGetAddressRange, ::cuMemGetInfo, ::cuMemHostAlloc,
 * ::cuMemHostGetDevicePointer, ::cuMemsetD2D8, ::cuMemsetD2D8Async,
 * ::cuMemsetD2D16, ::cuMemsetD2D16Async, ::cuMemsetD2D32,
 * ::cuMemsetD8, ::cuMemsetD8Async, ::cuMemsetD16, ::cuMemsetD16Async,
 * ::cuMemsetD32, ::cuMemsetD32Async,
 * ::cudaMemset2DAsync
 */
CUresult CUDAAPI cuMemsetD2D32Async(CUdeviceptr dstDevice, size_t dstPitch, unsigned int ui, size_t Width, size_t Height, CUstream hStream);

/**
 * \brief Creates a 1D or 2D CUDA array
 *
 * Creates a CUDA array according to the ::CUDA_ARRAY_DESCRIPTOR structure
 * \p pAllocateArray and returns a handle to the new CUDA array in \p *pHandle.
 * The ::CUDA_ARRAY_DESCRIPTOR is defined as:
 *
 * \code
    typedef struct {
        unsigned int Width;
        unsigned int Height;
        CUarray_format Format;
        unsigned int NumChannels;
    } CUDA_ARRAY_DESCRIPTOR;
 * \endcode
 * where:
 *
 * - \p Width, and \p Height are the width, and height of the CUDA array (in
 * elements); the CUDA array is one-dimensional if height is 0, two-dimensional
 * otherwise;
 * - ::Format specifies the format of the elements; ::CUarray_format is
 * defined as:
 * \code
    typedef enum CUarray_format_enum {
        CU_AD_FORMAT_UNSIGNED_INT8 = 0x01,
        CU_AD_FORMAT_UNSIGNED_INT16 = 0x02,
        CU_AD_FORMAT_UNSIGNED_INT32 = 0x03,
        CU_AD_FORMAT_SIGNED_INT8 = 0x08,
        CU_AD_FORMAT_SIGNED_INT16 = 0x09,
        CU_AD_FORMAT_SIGNED_INT32 = 0x0a,
        CU_AD_FORMAT_HALF = 0x10,
        CU_AD_FORMAT_FLOAT = 0x20,
        CU_AD_FORMAT_NV12 = 0xb0, 
        CU_AD_FORMAT_UNORM_INT8X1 = 0xc0, 
        CU_AD_FORMAT_UNORM_INT8X2 = 0xc1, 
        CU_AD_FORMAT_UNORM_INT8X4 = 0xc2, 
        CU_AD_FORMAT_UNORM_INT16X1 = 0xc3, 
        CU_AD_FORMAT_UNORM_INT16X2 = 0xc4, 
        CU_AD_FORMAT_UNORM_INT16X4 = 0xc5, 
        CU_AD_FORMAT_SNORM_INT8X1 = 0xc6, 
        CU_AD_FORMAT_SNORM_INT8X2 = 0xc7, 
        CU_AD_FORMAT_SNORM_INT8X4 = 0xc8, 
        CU_AD_FORMAT_SNORM_INT16X1 = 0xc9,
        CU_AD_FORMAT_SNORM_INT16X2 = 0xca,
        CU_AD_FORMAT_SNORM_INT16X4 = 0xcb,
        CU_AD_FORMAT_BC1_UNORM = 0x91,
        CU_AD_FORMAT_BC1_UNORM_SRGB = 0x92,
        CU_AD_FORMAT_BC2_UNORM = 0x93,
        CU_AD_FORMAT_BC2_UNORM_SRGB = 0x94,
        CU_AD_FORMAT_BC3_UNORM = 0x95,
        CU_AD_FORMAT_BC3_UNORM_SRGB = 0x96,
        CU_AD_FORMAT_BC4_UNORM = 0x97,
        CU_AD_FORMAT_BC4_SNORM = 0x98,
        CU_AD_FORMAT_BC5_UNORM = 0x99,
        CU_AD_FORMAT_BC5_SNORM = 0x9a,
        CU_AD_FORMAT_BC6H_UF16 = 0x9b,
        CU_AD_FORMAT_BC6H_SF16 = 0x9c,
        CU_AD_FORMAT_BC7_UNORM = 0x9d,
        CU_AD_FORMAT_BC7_UNORM_SRGB = 0x9e,
        CU_AD_FORMAT_P010 = 0x9f,
        CU_AD_FORMAT_P016 = 0xa1,
        CU_AD_FORMAT_NV16 = 0xa2,
        CU_AD_FORMAT_P210 = 0xa3,
        CU_AD_FORMAT_P216 = 0xa4,
        CU_AD_FORMAT_YUY2 = 0xa5,
        CU_AD_FORMAT_Y210 = 0xa6,
        CU_AD_FORMAT_Y216 = 0xa7,
        CU_AD_FORMAT_AYUV = 0xa8,
        CU_AD_FORMAT_Y410 = 0xa9,
        CU_AD_FORMAT_Y416 = 0xb1,
        CU_AD_FORMAT_Y444_PLANAR8 = 0xb2,
        CU_AD_FORMAT_Y444_PLANAR10 = 0xb3,
        CU_AD_FORMAT_YUV444_8bit_SemiPlanar = 0xb4,
        CU_AD_FORMAT_YUV444_16bit_SemiPlanar = 0xb5,
        CU_AD_FORMAT_UNORM_INT_101010_2 = 0x50,
   } CUarray_format;
 *  \endcode
 * - \p NumChannels specifies the number of packed components per CUDA array
 * element; it may be 1, 2, or 4;
 *
 * Here are examples of CUDA array descriptions:
 *
 * Description for a CUDA array of 2048 floats:
 * \code
    CUDA_ARRAY_DESCRIPTOR desc;
    desc.Format = CU_AD_FORMAT_FLOAT;
    desc.NumChannels = 1;
    desc.Width = 2048;
    desc.Height = 1;
 * \endcode
 *
 * Description for a 64 x 64 CUDA array of floats:
 * \code
    CUDA_ARRAY_DESCRIPTOR desc;
    desc.Format = CU_AD_FORMAT_FLOAT;
    desc.NumChannels = 1;
    desc.Width = 64;
    desc.Height = 64;
 * \endcode
 *
 * Description for a \p width x \p height CUDA array of 64-bit, 4x16-bit
 * float16's:
 * \code
    CUDA_ARRAY_DESCRIPTOR desc;
    desc.Format = CU_AD_FORMAT_HALF;
    desc.NumChannels = 4;
    desc.Width = width;
    desc.Height = height;
 * \endcode
 *
 * Description for a \p width x \p height CUDA array of 16-bit elements, each
 * of which is two 8-bit unsigned chars:
 * \code
    CUDA_ARRAY_DESCRIPTOR arrayDesc;
    desc.Format = CU_AD_FORMAT_UNSIGNED_INT8;
    desc.NumChannels = 2;
    desc.Width = width;
    desc.Height = height;
 * \endcode
 *
 * \param pHandle        - Returned array
 * \param pAllocateArray - Array descriptor
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_OUT_OF_MEMORY,
 * ::CUDA_ERROR_UNKNOWN
 * \notefnerr
 *
 * \sa ::cuArray3DCreate, ::cuArray3DGetDescriptor,
 * ::cuArrayDestroy, ::cuArrayGetDescriptor, ::cuMemAlloc, ::cuMemAllocHost,
 * ::cuMemAllocPitch, ::cuMemcpy2D, ::cuMemcpy2DAsync, ::cuMemcpy2DUnaligned,
 * ::cuMemcpy3D, ::cuMemcpy3DAsync, ::cuMemcpyAtoA, ::cuMemcpyAtoD,
 * ::cuMemcpyAtoH, ::cuMemcpyAtoHAsync, ::cuMemcpyDtoA, ::cuMemcpyDtoD, ::cuMemcpyDtoDAsync,
 * ::cuMemcpyDtoH, ::cuMemcpyDtoHAsync, ::cuMemcpyHtoA, ::cuMemcpyHtoAAsync,
 * ::cuMemcpyHtoD, ::cuMemcpyHtoDAsync, ::cuMemFree, ::cuMemFreeHost,
 * ::cuMemGetAddressRange, ::cuMemGetInfo, ::cuMemHostAlloc,
 * ::cuMemHostGetDevicePointer, ::cuMemsetD2D8, ::cuMemsetD2D16,
 * ::cuMemsetD2D32, ::cuMemsetD8, ::cuMemsetD16, ::cuMemsetD32,
 * ::cudaMallocArray
 */
CUresult CUDAAPI cuArrayCreate(CUarray *pHandle, const CUDA_ARRAY_DESCRIPTOR *pAllocateArray);

/**
 * \brief Get a 1D or 2D CUDA array descriptor
 *
 * Returns in \p *pArrayDescriptor a descriptor containing information on the
 * format and dimensions of the CUDA array \p hArray. It is useful for
 * subroutines that have been passed a CUDA array, but need to know the CUDA
 * array parameters for validation or other purposes.
 *
 * \param pArrayDescriptor - Returned array descriptor
 * \param hArray           - Array to get descriptor of
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_HANDLE
 * \notefnerr
 *
 * \sa ::cuArray3DCreate, ::cuArray3DGetDescriptor, ::cuArrayCreate,
 * ::cuArrayDestroy, ::cuMemAlloc, ::cuMemAllocHost,
 * ::cuMemAllocPitch, ::cuMemcpy2D, ::cuMemcpy2DAsync, ::cuMemcpy2DUnaligned,
 * ::cuMemcpy3D, ::cuMemcpy3DAsync, ::cuMemcpyAtoA, ::cuMemcpyAtoD,
 * ::cuMemcpyAtoH, ::cuMemcpyAtoHAsync, ::cuMemcpyDtoA, ::cuMemcpyDtoD, ::cuMemcpyDtoDAsync,
 * ::cuMemcpyDtoH, ::cuMemcpyDtoHAsync, ::cuMemcpyHtoA, ::cuMemcpyHtoAAsync,
 * ::cuMemcpyHtoD, ::cuMemcpyHtoDAsync, ::cuMemFree, ::cuMemFreeHost,
 * ::cuMemGetAddressRange, ::cuMemGetInfo, ::cuMemHostAlloc,
 * ::cuMemHostGetDevicePointer, ::cuMemsetD2D8, ::cuMemsetD2D16,
 * ::cuMemsetD2D32, ::cuMemsetD8, ::cuMemsetD16, ::cuMemsetD32,
 * ::cudaArrayGetInfo
 */
CUresult CUDAAPI cuArrayGetDescriptor(CUDA_ARRAY_DESCRIPTOR *pArrayDescriptor, CUarray hArray);

/**
 * \brief Returns the layout properties of a sparse CUDA array
 *
 * Returns the layout properties of a sparse CUDA array in \p sparseProperties
 * If the CUDA array is not allocated with flag ::CUDA_ARRAY3D_SPARSE 
 * ::CUDA_ERROR_INVALID_VALUE will be returned.
 *
 * If the returned value in ::CUDA_ARRAY_SPARSE_PROPERTIES::flags contains ::CU_ARRAY_SPARSE_PROPERTIES_SINGLE_MIPTAIL,
 * then ::CUDA_ARRAY_SPARSE_PROPERTIES::miptailSize represents the total size of the array. Otherwise, it will be zero.
 * Also, the returned value in ::CUDA_ARRAY_SPARSE_PROPERTIES::miptailFirstLevel is always zero.
 * Note that the \p array must have been allocated using ::cuArrayCreate or ::cuArray3DCreate. For CUDA arrays obtained
 * using ::cuMipmappedArrayGetLevel, ::CUDA_ERROR_INVALID_VALUE will be returned. Instead, ::cuMipmappedArrayGetSparseProperties 
 * must be used to obtain the sparse properties of the entire CUDA mipmapped array to which \p array belongs to.
 *
 * \return
 * ::CUDA_SUCCESS
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \param[out] sparseProperties - Pointer to ::CUDA_ARRAY_SPARSE_PROPERTIES
 * \param[in] array - CUDA array to get the sparse properties of
 * \sa ::cuMipmappedArrayGetSparseProperties, ::cuMemMapArrayAsync
 */
CUresult CUDAAPI cuArrayGetSparseProperties(CUDA_ARRAY_SPARSE_PROPERTIES *sparseProperties, CUarray array);

/**
 * \brief Returns the layout properties of a sparse CUDA mipmapped array
 *
 * Returns the sparse array layout properties in \p sparseProperties
 * If the CUDA mipmapped array is not allocated with flag ::CUDA_ARRAY3D_SPARSE 
 * ::CUDA_ERROR_INVALID_VALUE will be returned.
 *
 * For non-layered CUDA mipmapped arrays, ::CUDA_ARRAY_SPARSE_PROPERTIES::miptailSize returns the
 * size of the mip tail region. The mip tail region includes all mip levels whose width, height or depth
 * is less than that of the tile.
 * For layered CUDA mipmapped arrays, if ::CUDA_ARRAY_SPARSE_PROPERTIES::flags contains ::CU_ARRAY_SPARSE_PROPERTIES_SINGLE_MIPTAIL,
 * then ::CUDA_ARRAY_SPARSE_PROPERTIES::miptailSize specifies the size of the mip tail of all layers combined. 
 * Otherwise, ::CUDA_ARRAY_SPARSE_PROPERTIES::miptailSize specifies mip tail size per layer.
 * The returned value of ::CUDA_ARRAY_SPARSE_PROPERTIES::miptailFirstLevel is valid only if ::CUDA_ARRAY_SPARSE_PROPERTIES::miptailSize is non-zero.
 *
 * \return
 * ::CUDA_SUCCESS
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \param[out] sparseProperties - Pointer to ::CUDA_ARRAY_SPARSE_PROPERTIES
 * \param[in] mipmap - CUDA mipmapped array to get the sparse properties of
 * \sa ::cuArrayGetSparseProperties, ::cuMemMapArrayAsync
 */
CUresult CUDAAPI cuMipmappedArrayGetSparseProperties(CUDA_ARRAY_SPARSE_PROPERTIES *sparseProperties, CUmipmappedArray mipmap);

/**
 * \brief Returns the memory requirements of a CUDA array
 *
 * Returns the memory requirements of a CUDA array in \p memoryRequirements
 * If the CUDA array is not allocated with flag ::CUDA_ARRAY3D_DEFERRED_MAPPING
 * ::CUDA_ERROR_INVALID_VALUE will be returned.
 *
 * The returned value in ::CUDA_ARRAY_MEMORY_REQUIREMENTS::size 
 * represents the total size of the CUDA array.
 * The returned value in ::CUDA_ARRAY_MEMORY_REQUIREMENTS::alignment 
 * represents the alignment necessary for mapping the CUDA array.
 *
 * \return
 * ::CUDA_SUCCESS
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \param[out] memoryRequirements - Pointer to ::CUDA_ARRAY_MEMORY_REQUIREMENTS
 * \param[in] array - CUDA array to get the memory requirements of
 * \param[in] device - Device to get the memory requirements for
 * \sa ::cuMipmappedArrayGetMemoryRequirements, ::cuMemMapArrayAsync
 */
CUresult CUDAAPI cuArrayGetMemoryRequirements(CUDA_ARRAY_MEMORY_REQUIREMENTS *memoryRequirements, CUarray array, CUdevice device);
 
/**
 * \brief Returns the memory requirements of a CUDA mipmapped array
 *
 * Returns the memory requirements of a CUDA mipmapped array in \p memoryRequirements
 * If the CUDA mipmapped array is not allocated with flag ::CUDA_ARRAY3D_DEFERRED_MAPPING
 * ::CUDA_ERROR_INVALID_VALUE will be returned.
 *
 * The returned value in ::CUDA_ARRAY_MEMORY_REQUIREMENTS::size 
 * represents the total size of the CUDA mipmapped array.
 * The returned value in ::CUDA_ARRAY_MEMORY_REQUIREMENTS::alignment 
 * represents the alignment necessary for mapping the CUDA mipmapped  
 * array.
 *
 * \return
 * ::CUDA_SUCCESS
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \param[out] memoryRequirements - Pointer to ::CUDA_ARRAY_MEMORY_REQUIREMENTS
 * \param[in] mipmap - CUDA mipmapped array to get the memory requirements of
 * \param[in] device - Device to get the memory requirements for
 * \sa ::cuArrayGetMemoryRequirements, ::cuMemMapArrayAsync
 */
CUresult CUDAAPI cuMipmappedArrayGetMemoryRequirements(CUDA_ARRAY_MEMORY_REQUIREMENTS *memoryRequirements, CUmipmappedArray mipmap, CUdevice device);

/**
 * \brief Gets a CUDA array plane from a CUDA array
 *
 * Returns in \p pPlaneArray a CUDA array that represents a single format plane
 * of the CUDA array \p hArray.
 *
 * If \p planeIdx is greater than the maximum number of planes in this array or if the array does
 * not have a multi-planar format e.g: ::CU_AD_FORMAT_NV12, then ::CUDA_ERROR_INVALID_VALUE is returned.
 *
 * Note that if the \p hArray has format ::CU_AD_FORMAT_NV12, then passing in 0 for \p planeIdx returns
 * a CUDA array of the same size as \p hArray but with one channel and ::CU_AD_FORMAT_UNSIGNED_INT8 as its format.
 * If 1 is passed for \p planeIdx, then the returned CUDA array has half the height and width
 * of \p hArray with two channels and ::CU_AD_FORMAT_UNSIGNED_INT8 as its format.
 *
 * \param pPlaneArray   - Returned CUDA array referenced by the \p planeIdx
 * \param hArray        - Multiplanar CUDA array
 * \param planeIdx      - Plane index
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_HANDLE
 * \notefnerr
 *
 * \sa
 * ::cuArrayCreate,
 * ::cudaArrayGetPlane
 */
CUresult CUDAAPI cuArrayGetPlane(CUarray *pPlaneArray, CUarray hArray, unsigned int planeIdx);

/**
 * \brief Destroys a CUDA array
 *
 * Destroys the CUDA array \p hArray.
 *
 * \param hArray - Array to destroy
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_ARRAY_IS_MAPPED,
 * ::CUDA_ERROR_CONTEXT_IS_DESTROYED
 * \notefnerr
 *
 * \sa ::cuArray3DCreate, ::cuArray3DGetDescriptor, ::cuArrayCreate,
 * ::cuArrayGetDescriptor, ::cuMemAlloc, ::cuMemAllocHost,
 * ::cuMemAllocPitch, ::cuMemcpy2D, ::cuMemcpy2DAsync, ::cuMemcpy2DUnaligned,
 * ::cuMemcpy3D, ::cuMemcpy3DAsync, ::cuMemcpyAtoA, ::cuMemcpyAtoD,
 * ::cuMemcpyAtoH, ::cuMemcpyAtoHAsync, ::cuMemcpyDtoA, ::cuMemcpyDtoD, ::cuMemcpyDtoDAsync,
 * ::cuMemcpyDtoH, ::cuMemcpyDtoHAsync, ::cuMemcpyHtoA, ::cuMemcpyHtoAAsync,
 * ::cuMemcpyHtoD, ::cuMemcpyHtoDAsync, ::cuMemFree, ::cuMemFreeHost,
 * ::cuMemGetAddressRange, ::cuMemGetInfo, ::cuMemHostAlloc,
 * ::cuMemHostGetDevicePointer, ::cuMemsetD2D8, ::cuMemsetD2D16,
 * ::cuMemsetD2D32, ::cuMemsetD8, ::cuMemsetD16, ::cuMemsetD32,
 * ::cudaFreeArray
 */
CUresult CUDAAPI cuArrayDestroy(CUarray hArray);

/**
 * \brief Creates a 3D CUDA array
 *
 * Creates a CUDA array according to the ::CUDA_ARRAY3D_DESCRIPTOR structure
 * \p pAllocateArray and returns a handle to the new CUDA array in \p *pHandle.
 * The ::CUDA_ARRAY3D_DESCRIPTOR is defined as:
 *
 * \code
    typedef struct {
        unsigned int Width;
        unsigned int Height;
        unsigned int Depth;
        CUarray_format Format;
        unsigned int NumChannels;
        unsigned int Flags;
    } CUDA_ARRAY3D_DESCRIPTOR;
 * \endcode
 * where:
 *
 * - \p Width, \p Height, and \p Depth are the width, height, and depth of the
 * CUDA array (in elements); the following types of CUDA arrays can be allocated:
 *     - A 1D array is allocated if \p Height and \p Depth extents are both zero.
 *     - A 2D array is allocated if only \p Depth extent is zero.
 *     - A 3D array is allocated if all three extents are non-zero.
 *     - A 1D layered CUDA array is allocated if only \p Height is zero and the
 *       ::CUDA_ARRAY3D_LAYERED flag is set. Each layer is a 1D array. The number
 *       of layers is determined by the depth extent.
 *     - A 2D layered CUDA array is allocated if all three extents are non-zero and
 *       the ::CUDA_ARRAY3D_LAYERED flag is set. Each layer is a 2D array. The number
 *       of layers is determined by the depth extent.
 *     - A cubemap CUDA array is allocated if all three extents are non-zero and the
 *       ::CUDA_ARRAY3D_CUBEMAP flag is set. \p Width must be equal to \p Height, and
 *       \p Depth must be six. A cubemap is a special type of 2D layered CUDA array,
 *       where the six layers represent the six faces of a cube. The order of the six
 *       layers in memory is the same as that listed in ::CUarray_cubemap_face.
 *     - A cubemap layered CUDA array is allocated if all three extents are non-zero,
 *       and both, ::CUDA_ARRAY3D_CUBEMAP and ::CUDA_ARRAY3D_LAYERED flags are set.
 *       \p Width must be equal to \p Height, and \p Depth must be a multiple of six.
 *       A cubemap layered CUDA array is a special type of 2D layered CUDA array that
 *       consists of a collection of cubemaps. The first six layers represent the first
 *       cubemap, the next six layers form the second cubemap, and so on.
 *
 * - ::Format specifies the format of the elements; ::CUarray_format is
 * defined as:
 * \code
    typedef enum CUarray_format_enum {
        CU_AD_FORMAT_UNSIGNED_INT8 = 0x01,
        CU_AD_FORMAT_UNSIGNED_INT16 = 0x02,
        CU_AD_FORMAT_UNSIGNED_INT32 = 0x03,
        CU_AD_FORMAT_SIGNED_INT8 = 0x08,
        CU_AD_FORMAT_SIGNED_INT16 = 0x09,
        CU_AD_FORMAT_SIGNED_INT32 = 0x0a,
        CU_AD_FORMAT_HALF = 0x10,
        CU_AD_FORMAT_FLOAT = 0x20,
        CU_AD_FORMAT_NV12 = 0xb0, 
        CU_AD_FORMAT_UNORM_INT8X1 = 0xc0, 
        CU_AD_FORMAT_UNORM_INT8X2 = 0xc1, 
        CU_AD_FORMAT_UNORM_INT8X4 = 0xc2, 
        CU_AD_FORMAT_UNORM_INT16X1 = 0xc3, 
        CU_AD_FORMAT_UNORM_INT16X2 = 0xc4, 
        CU_AD_FORMAT_UNORM_INT16X4 = 0xc5, 
        CU_AD_FORMAT_SNORM_INT8X1 = 0xc6, 
        CU_AD_FORMAT_SNORM_INT8X2 = 0xc7, 
        CU_AD_FORMAT_SNORM_INT8X4 = 0xc8, 
        CU_AD_FORMAT_SNORM_INT16X1 = 0xc9,
        CU_AD_FORMAT_SNORM_INT16X2 = 0xca,
        CU_AD_FORMAT_SNORM_INT16X4 = 0xcb,
        CU_AD_FORMAT_BC1_UNORM = 0x91,
        CU_AD_FORMAT_BC1_UNORM_SRGB = 0x92,
        CU_AD_FORMAT_BC2_UNORM = 0x93,
        CU_AD_FORMAT_BC2_UNORM_SRGB = 0x94,
        CU_AD_FORMAT_BC3_UNORM = 0x95,
        CU_AD_FORMAT_BC3_UNORM_SRGB = 0x96,
        CU_AD_FORMAT_BC4_UNORM = 0x97,
        CU_AD_FORMAT_BC4_SNORM = 0x98,
        CU_AD_FORMAT_BC5_UNORM = 0x99,
        CU_AD_FORMAT_BC5_SNORM = 0x9a,
        CU_AD_FORMAT_BC6H_UF16 = 0x9b,
        CU_AD_FORMAT_BC6H_SF16 = 0x9c,
        CU_AD_FORMAT_BC7_UNORM = 0x9d,
        CU_AD_FORMAT_BC7_UNORM_SRGB = 0x9e,
        CU_AD_FORMAT_P010 = 0x9f,
        CU_AD_FORMAT_P016 = 0xa1,
        CU_AD_FORMAT_NV16 = 0xa2,
        CU_AD_FORMAT_P210 = 0xa3,
        CU_AD_FORMAT_P216 = 0xa4,
        CU_AD_FORMAT_YUY2 = 0xa5,
        CU_AD_FORMAT_Y210 = 0xa6,
        CU_AD_FORMAT_Y216 = 0xa7,
        CU_AD_FORMAT_AYUV = 0xa8,
        CU_AD_FORMAT_Y410 = 0xa9,
        CU_AD_FORMAT_Y416 = 0xb1,
        CU_AD_FORMAT_Y444_PLANAR8 = 0xb2,
        CU_AD_FORMAT_Y444_PLANAR10 = 0xb3,
        CU_AD_FORMAT_YUV444_8bit_SemiPlanar = 0xb4,
        CU_AD_FORMAT_YUV444_16bit_SemiPlanar = 0xb5,
        CU_AD_FORMAT_UNORM_INT_101010_2 = 0x50,
    } CUarray_format;
 *  \endcode
 *
 * - \p NumChannels specifies the number of packed components per CUDA array
 * element; it may be 1, 2, or 4;
 *
 * - ::Flags may be set to
 *   - ::CUDA_ARRAY3D_LAYERED to enable creation of layered CUDA arrays. If this flag is set,
 *     \p Depth specifies the number of layers, not the depth of a 3D array.
 *   - ::CUDA_ARRAY3D_SURFACE_LDST to enable surface references to be bound to the CUDA array.
 *     If this flag is not set, ::cuSurfRefSetArray will fail when attempting to bind the CUDA array
 *     to a surface reference.
 *   - ::CUDA_ARRAY3D_CUBEMAP to enable creation of cubemaps. If this flag is set, \p Width must be
 *     equal to \p Height, and \p Depth must be six. If the ::CUDA_ARRAY3D_LAYERED flag is also set,
 *     then \p Depth must be a multiple of six.
 *   - ::CUDA_ARRAY3D_TEXTURE_GATHER to indicate that the CUDA array will be used for texture gather.
 *     Texture gather can only be performed on 2D CUDA arrays.
 *
 * \p Width, \p Height and \p Depth must meet certain size requirements as listed in the following table.
 * All values are specified in elements. Note that for brevity's sake, the full name of the device attribute
 * is not specified. For ex., TEXTURE1D_WIDTH refers to the device attribute
 * ::CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE1D_WIDTH.
 *
 * Note that 2D CUDA arrays have different size requirements if the ::CUDA_ARRAY3D_TEXTURE_GATHER flag
 * is set. \p Width and \p Height must not be greater than ::CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_GATHER_WIDTH
 * and ::CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_GATHER_HEIGHT respectively, in that case.
 *
 * <table>
 * <tr><td><b>CUDA array type</b></td>
 * <td><b>Valid extents that must always be met<br>{(width range in elements), (height range),
 * (depth range)}</b></td>
 * <td><b>Valid extents with CUDA_ARRAY3D_SURFACE_LDST set<br>
 * {(width range in elements), (height range), (depth range)}</b></td></tr>
 * <tr><td>1D</td>
 * <td><small>{ (1,TEXTURE1D_WIDTH), 0, 0 }</small></td>
 * <td><small>{ (1,SURFACE1D_WIDTH), 0, 0 }</small></td></tr>
 * <tr><td>2D</td>
 * <td><small>{ (1,TEXTURE2D_WIDTH), (1,TEXTURE2D_HEIGHT), 0 }</small></td>
 * <td><small>{ (1,SURFACE2D_WIDTH), (1,SURFACE2D_HEIGHT), 0 }</small></td></tr>
 * <tr><td>3D</td>
 * <td><small>{ (1,TEXTURE3D_WIDTH), (1,TEXTURE3D_HEIGHT), (1,TEXTURE3D_DEPTH) }
 * <br>OR<br>{ (1,TEXTURE3D_WIDTH_ALTERNATE), (1,TEXTURE3D_HEIGHT_ALTERNATE),
 * (1,TEXTURE3D_DEPTH_ALTERNATE) }</small></td>
 * <td><small>{ (1,SURFACE3D_WIDTH), (1,SURFACE3D_HEIGHT),
 * (1,SURFACE3D_DEPTH) }</small></td></tr>
 * <tr><td>1D Layered</td>
 * <td><small>{ (1,TEXTURE1D_LAYERED_WIDTH), 0,
 * (1,TEXTURE1D_LAYERED_LAYERS) }</small></td>
 * <td><small>{ (1,SURFACE1D_LAYERED_WIDTH), 0,
 * (1,SURFACE1D_LAYERED_LAYERS) }</small></td></tr>
 * <tr><td>2D Layered</td>
 * <td><small>{ (1,TEXTURE2D_LAYERED_WIDTH), (1,TEXTURE2D_LAYERED_HEIGHT),
 * (1,TEXTURE2D_LAYERED_LAYERS) }</small></td>
 * <td><small>{ (1,SURFACE2D_LAYERED_WIDTH), (1,SURFACE2D_LAYERED_HEIGHT),
 * (1,SURFACE2D_LAYERED_LAYERS) }</small></td></tr>
 * <tr><td>Cubemap</td>
 * <td><small>{ (1,TEXTURECUBEMAP_WIDTH), (1,TEXTURECUBEMAP_WIDTH), 6 }</small></td>
 * <td><small>{ (1,SURFACECUBEMAP_WIDTH),
 * (1,SURFACECUBEMAP_WIDTH), 6 }</small></td></tr>
 * <tr><td>Cubemap Layered</td>
 * <td><small>{ (1,TEXTURECUBEMAP_LAYERED_WIDTH), (1,TEXTURECUBEMAP_LAYERED_WIDTH),
 * (1,TEXTURECUBEMAP_LAYERED_LAYERS) }</small></td>
 * <td><small>{ (1,SURFACECUBEMAP_LAYERED_WIDTH), (1,SURFACECUBEMAP_LAYERED_WIDTH),
 * (1,SURFACECUBEMAP_LAYERED_LAYERS) }</small></td></tr>
 * </table>
 *
 * Here are examples of CUDA array descriptions:
 *
 * Description for a CUDA array of 2048 floats:
 * \code
    CUDA_ARRAY3D_DESCRIPTOR desc;
    desc.Format = CU_AD_FORMAT_FLOAT;
    desc.NumChannels = 1;
    desc.Width = 2048;
    desc.Height = 0;
    desc.Depth = 0;
 * \endcode
 *
 * Description for a 64 x 64 CUDA array of floats:
 * \code
    CUDA_ARRAY3D_DESCRIPTOR desc;
    desc.Format = CU_AD_FORMAT_FLOAT;
    desc.NumChannels = 1;
    desc.Width = 64;
    desc.Height = 64;
    desc.Depth = 0;
 * \endcode
 *
 * Description for a \p width x \p height x \p depth CUDA array of 64-bit,
 * 4x16-bit float16's:
 * \code
    CUDA_ARRAY3D_DESCRIPTOR desc;
    desc.Format = CU_AD_FORMAT_HALF;
    desc.NumChannels = 4;
    desc.Width = width;
    desc.Height = height;
    desc.Depth = depth;
 * \endcode
 *
 * \param pHandle        - Returned array
 * \param pAllocateArray - 3D array descriptor
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_OUT_OF_MEMORY,
 * ::CUDA_ERROR_UNKNOWN
 * \notefnerr
 *
 * \sa ::cuArray3DGetDescriptor, ::cuArrayCreate,
 * ::cuArrayDestroy, ::cuArrayGetDescriptor, ::cuMemAlloc, ::cuMemAllocHost,
 * ::cuMemAllocPitch, ::cuMemcpy2D, ::cuMemcpy2DAsync, ::cuMemcpy2DUnaligned,
 * ::cuMemcpy3D, ::cuMemcpy3DAsync, ::cuMemcpyAtoA, ::cuMemcpyAtoD,
 * ::cuMemcpyAtoH, ::cuMemcpyAtoHAsync, ::cuMemcpyDtoA, ::cuMemcpyDtoD, ::cuMemcpyDtoDAsync,
 * ::cuMemcpyDtoH, ::cuMemcpyDtoHAsync, ::cuMemcpyHtoA, ::cuMemcpyHtoAAsync,
 * ::cuMemcpyHtoD, ::cuMemcpyHtoDAsync, ::cuMemFree, ::cuMemFreeHost,
 * ::cuMemGetAddressRange, ::cuMemGetInfo, ::cuMemHostAlloc,
 * ::cuMemHostGetDevicePointer, ::cuMemsetD2D8, ::cuMemsetD2D16,
 * ::cuMemsetD2D32, ::cuMemsetD8, ::cuMemsetD16, ::cuMemsetD32,
 * ::cudaMalloc3DArray
 */
CUresult CUDAAPI cuArray3DCreate(CUarray *pHandle, const CUDA_ARRAY3D_DESCRIPTOR *pAllocateArray);

/**
 * \brief Get a 3D CUDA array descriptor
 *
 * Returns in \p *pArrayDescriptor a descriptor containing information on the
 * format and dimensions of the CUDA array \p hArray. It is useful for
 * subroutines that have been passed a CUDA array, but need to know the CUDA
 * array parameters for validation or other purposes.
 *
 * This function may be called on 1D and 2D arrays, in which case the \p Height
 * and/or \p Depth members of the descriptor struct will be set to 0.
 *
 * \param pArrayDescriptor - Returned 3D array descriptor
 * \param hArray           - 3D array to get descriptor of
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_CONTEXT_IS_DESTROYED
 * \notefnerr
 *
 * \sa ::cuArray3DCreate, ::cuArrayCreate,
 * ::cuArrayDestroy, ::cuArrayGetDescriptor, ::cuMemAlloc, ::cuMemAllocHost,
 * ::cuMemAllocPitch, ::cuMemcpy2D, ::cuMemcpy2DAsync, ::cuMemcpy2DUnaligned,
 * ::cuMemcpy3D, ::cuMemcpy3DAsync, ::cuMemcpyAtoA, ::cuMemcpyAtoD,
 * ::cuMemcpyAtoH, ::cuMemcpyAtoHAsync, ::cuMemcpyDtoA, ::cuMemcpyDtoD, ::cuMemcpyDtoDAsync,
 * ::cuMemcpyDtoH, ::cuMemcpyDtoHAsync, ::cuMemcpyHtoA, ::cuMemcpyHtoAAsync,
 * ::cuMemcpyHtoD, ::cuMemcpyHtoDAsync, ::cuMemFree, ::cuMemFreeHost,
 * ::cuMemGetAddressRange, ::cuMemGetInfo, ::cuMemHostAlloc,
 * ::cuMemHostGetDevicePointer, ::cuMemsetD2D8, ::cuMemsetD2D16,
 * ::cuMemsetD2D32, ::cuMemsetD8, ::cuMemsetD16, ::cuMemsetD32,
 * ::cudaArrayGetInfo
 */
CUresult CUDAAPI cuArray3DGetDescriptor(CUDA_ARRAY3D_DESCRIPTOR *pArrayDescriptor, CUarray hArray);

/**
 * \brief Creates a CUDA mipmapped array
 *
 * Creates a CUDA mipmapped array according to the ::CUDA_ARRAY3D_DESCRIPTOR structure
 * \p pMipmappedArrayDesc and returns a handle to the new CUDA mipmapped array in \p *pHandle.
 * \p numMipmapLevels specifies the number of mipmap levels to be allocated. This value is
 * clamped to the range [1, 1 + floor(log2(max(width, height, depth)))].
 *
 * The ::CUDA_ARRAY3D_DESCRIPTOR is defined as:
 *
 * \code
    typedef struct {
        unsigned int Width;
        unsigned int Height;
        unsigned int Depth;
        CUarray_format Format;
        unsigned int NumChannels;
        unsigned int Flags;
    } CUDA_ARRAY3D_DESCRIPTOR;
 * \endcode
 * where:
 *
 * - \p Width, \p Height, and \p Depth are the width, height, and depth of the
 * CUDA array (in elements); the following types of CUDA arrays can be allocated:
 *     - A 1D mipmapped array is allocated if \p Height and \p Depth extents are both zero.
 *     - A 2D mipmapped array is allocated if only \p Depth extent is zero.
 *     - A 3D mipmapped array is allocated if all three extents are non-zero.
 *     - A 1D layered CUDA mipmapped array is allocated if only \p Height is zero and the
 *       ::CUDA_ARRAY3D_LAYERED flag is set. Each layer is a 1D array. The number
 *       of layers is determined by the depth extent.
 *     - A 2D layered CUDA mipmapped array is allocated if all three extents are non-zero and
 *       the ::CUDA_ARRAY3D_LAYERED flag is set. Each layer is a 2D array. The number
 *       of layers is determined by the depth extent.
 *     - A cubemap CUDA mipmapped array is allocated if all three extents are non-zero and the
 *       ::CUDA_ARRAY3D_CUBEMAP flag is set. \p Width must be equal to \p Height, and
 *       \p Depth must be six. A cubemap is a special type of 2D layered CUDA array,
 *       where the six layers represent the six faces of a cube. The order of the six
 *       layers in memory is the same as that listed in ::CUarray_cubemap_face.
 *     - A cubemap layered CUDA mipmapped array is allocated if all three extents are non-zero,
 *       and both, ::CUDA_ARRAY3D_CUBEMAP and ::CUDA_ARRAY3D_LAYERED flags are set.
 *       \p Width must be equal to \p Height, and \p Depth must be a multiple of six.
 *       A cubemap layered CUDA array is a special type of 2D layered CUDA array that
 *       consists of a collection of cubemaps. The first six layers represent the first
 *       cubemap, the next six layers form the second cubemap, and so on.
 *
 * - ::Format specifies the format of the elements; ::CUarray_format is
 * defined as:
 * \code
    typedef enum CUarray_format_enum {
        CU_AD_FORMAT_UNSIGNED_INT8 = 0x01,
        CU_AD_FORMAT_UNSIGNED_INT16 = 0x02,
        CU_AD_FORMAT_UNSIGNED_INT32 = 0x03,
        CU_AD_FORMAT_SIGNED_INT8 = 0x08,
        CU_AD_FORMAT_SIGNED_INT16 = 0x09,
        CU_AD_FORMAT_SIGNED_INT32 = 0x0a,
        CU_AD_FORMAT_HALF = 0x10,
        CU_AD_FORMAT_FLOAT = 0x20,
        CU_AD_FORMAT_NV12 = 0xb0, 
        CU_AD_FORMAT_UNORM_INT8X1 = 0xc0, 
        CU_AD_FORMAT_UNORM_INT8X2 = 0xc1, 
        CU_AD_FORMAT_UNORM_INT8X4 = 0xc2, 
        CU_AD_FORMAT_UNORM_INT16X1 = 0xc3, 
        CU_AD_FORMAT_UNORM_INT16X2 = 0xc4, 
        CU_AD_FORMAT_UNORM_INT16X4 = 0xc5, 
        CU_AD_FORMAT_SNORM_INT8X1 = 0xc6, 
        CU_AD_FORMAT_SNORM_INT8X2 = 0xc7, 
        CU_AD_FORMAT_SNORM_INT8X4 = 0xc8, 
        CU_AD_FORMAT_SNORM_INT16X1 = 0xc9,
        CU_AD_FORMAT_SNORM_INT16X2 = 0xca,
        CU_AD_FORMAT_SNORM_INT16X4 = 0xcb,
        CU_AD_FORMAT_BC1_UNORM = 0x91,
        CU_AD_FORMAT_BC1_UNORM_SRGB = 0x92,
        CU_AD_FORMAT_BC2_UNORM = 0x93,
        CU_AD_FORMAT_BC2_UNORM_SRGB = 0x94,
        CU_AD_FORMAT_BC3_UNORM = 0x95,
        CU_AD_FORMAT_BC3_UNORM_SRGB = 0x96,
        CU_AD_FORMAT_BC4_UNORM = 0x97,
        CU_AD_FORMAT_BC4_SNORM = 0x98,
        CU_AD_FORMAT_BC5_UNORM = 0x99,
        CU_AD_FORMAT_BC5_SNORM = 0x9a,
        CU_AD_FORMAT_BC6H_UF16 = 0x9b,
        CU_AD_FORMAT_BC6H_SF16 = 0x9c,
        CU_AD_FORMAT_BC7_UNORM = 0x9d,
        CU_AD_FORMAT_BC7_UNORM_SRGB = 0x9e,
        CU_AD_FORMAT_P010 = 0x9f,
        CU_AD_FORMAT_P016 = 0xa1,
        CU_AD_FORMAT_NV16 = 0xa2,
        CU_AD_FORMAT_P210 = 0xa3,
        CU_AD_FORMAT_P216 = 0xa4,
        CU_AD_FORMAT_YUY2 = 0xa5,
        CU_AD_FORMAT_Y210 = 0xa6,
        CU_AD_FORMAT_Y216 = 0xa7,
        CU_AD_FORMAT_AYUV = 0xa8,
        CU_AD_FORMAT_Y410 = 0xa9,
        CU_AD_FORMAT_Y416 = 0xb1,
        CU_AD_FORMAT_Y444_PLANAR8 = 0xb2,
        CU_AD_FORMAT_Y444_PLANAR10 = 0xb3,
        CU_AD_FORMAT_YUV444_8bit_SemiPlanar = 0xb4,
        CU_AD_FORMAT_YUV444_16bit_SemiPlanar = 0xb5,
        CU_AD_FORMAT_UNORM_INT_101010_2 = 0x50,
    } CUarray_format;
 *  \endcode
 *
 * - \p NumChannels specifies the number of packed components per CUDA array
 * element; it may be 1, 2, or 4;
 *
 * - ::Flags may be set to
 *   - ::CUDA_ARRAY3D_LAYERED to enable creation of layered CUDA mipmapped arrays. If this flag is set,
 *     \p Depth specifies the number of layers, not the depth of a 3D array.
 *   - ::CUDA_ARRAY3D_SURFACE_LDST to enable surface references to be bound to individual mipmap levels of
 *     the CUDA mipmapped array. If this flag is not set, ::cuSurfRefSetArray will fail when attempting to
 *     bind a mipmap level of the CUDA mipmapped array to a surface reference.
  *   - ::CUDA_ARRAY3D_CUBEMAP to enable creation of mipmapped cubemaps. If this flag is set, \p Width must be
 *     equal to \p Height, and \p Depth must be six. If the ::CUDA_ARRAY3D_LAYERED flag is also set,
 *     then \p Depth must be a multiple of six.
 *   - ::CUDA_ARRAY3D_TEXTURE_GATHER to indicate that the CUDA mipmapped array will be used for texture gather.
 *     Texture gather can only be performed on 2D CUDA mipmapped arrays.
 *
 * \p Width, \p Height and \p Depth must meet certain size requirements as listed in the following table.
 * All values are specified in elements. Note that for brevity's sake, the full name of the device attribute
 * is not specified. For ex., TEXTURE1D_MIPMAPPED_WIDTH refers to the device attribute
 * ::CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE1D_MIPMAPPED_WIDTH.
 *
 * <table>
 * <tr><td><b>CUDA array type</b></td>
 * <td><b>Valid extents that must always be met<br>{(width range in elements), (height range),
 * (depth range)}</b></td>
 * <td><b>Valid extents with CUDA_ARRAY3D_SURFACE_LDST set<br>
 * {(width range in elements), (height range), (depth range)}</b></td></tr>
 * <tr><td>1D</td>
 * <td><small>{ (1,TEXTURE1D_MIPMAPPED_WIDTH), 0, 0 }</small></td>
 * <td><small>{ (1,SURFACE1D_WIDTH), 0, 0 }</small></td></tr>
 * <tr><td>2D</td>
 * <td><small>{ (1,TEXTURE2D_MIPMAPPED_WIDTH), (1,TEXTURE2D_MIPMAPPED_HEIGHT), 0 }</small></td>
 * <td><small>{ (1,SURFACE2D_WIDTH), (1,SURFACE2D_HEIGHT), 0 }</small></td></tr>
 * <tr><td>3D</td>
 * <td><small>{ (1,TEXTURE3D_WIDTH), (1,TEXTURE3D_HEIGHT), (1,TEXTURE3D_DEPTH) }
 * <br>OR<br>{ (1,TEXTURE3D_WIDTH_ALTERNATE), (1,TEXTURE3D_HEIGHT_ALTERNATE),
 * (1,TEXTURE3D_DEPTH_ALTERNATE) }</small></td>
 * <td><small>{ (1,SURFACE3D_WIDTH), (1,SURFACE3D_HEIGHT),
 * (1,SURFACE3D_DEPTH) }</small></td></tr>
 * <tr><td>1D Layered</td>
 * <td><small>{ (1,TEXTURE1D_LAYERED_WIDTH), 0,
 * (1,TEXTURE1D_LAYERED_LAYERS) }</small></td>
 * <td><small>{ (1,SURFACE1D_LAYERED_WIDTH), 0,
 * (1,SURFACE1D_LAYERED_LAYERS) }</small></td></tr>
 * <tr><td>2D Layered</td>
 * <td><small>{ (1,TEXTURE2D_LAYERED_WIDTH), (1,TEXTURE2D_LAYERED_HEIGHT),
 * (1,TEXTURE2D_LAYERED_LAYERS) }</small></td>
 * <td><small>{ (1,SURFACE2D_LAYERED_WIDTH), (1,SURFACE2D_LAYERED_HEIGHT),
 * (1,SURFACE2D_LAYERED_LAYERS) }</small></td></tr>
 * <tr><td>Cubemap</td>
 * <td><small>{ (1,TEXTURECUBEMAP_WIDTH), (1,TEXTURECUBEMAP_WIDTH), 6 }</small></td>
 * <td><small>{ (1,SURFACECUBEMAP_WIDTH),
 * (1,SURFACECUBEMAP_WIDTH), 6 }</small></td></tr>
 * <tr><td>Cubemap Layered</td>
 * <td><small>{ (1,TEXTURECUBEMAP_LAYERED_WIDTH), (1,TEXTURECUBEMAP_LAYERED_WIDTH),
 * (1,TEXTURECUBEMAP_LAYERED_LAYERS) }</small></td>
 * <td><small>{ (1,SURFACECUBEMAP_LAYERED_WIDTH), (1,SURFACECUBEMAP_LAYERED_WIDTH),
 * (1,SURFACECUBEMAP_LAYERED_LAYERS) }</small></td></tr>
 * </table>
 *
 *
 * \param pHandle             - Returned mipmapped array
 * \param pMipmappedArrayDesc - mipmapped array descriptor
 * \param numMipmapLevels     - Number of mipmap levels
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_OUT_OF_MEMORY,
 * ::CUDA_ERROR_UNKNOWN
 * \notefnerr
 *
 * \sa
 * ::cuMipmappedArrayDestroy,
 * ::cuMipmappedArrayGetLevel,
 * ::cuArrayCreate,
 * ::cudaMallocMipmappedArray
 */
CUresult CUDAAPI cuMipmappedArrayCreate(CUmipmappedArray *pHandle, const CUDA_ARRAY3D_DESCRIPTOR *pMipmappedArrayDesc, unsigned int numMipmapLevels);

/**
 * \brief Gets a mipmap level of a CUDA mipmapped array
 *
 * Returns in \p *pLevelArray a CUDA array that represents a single mipmap level
 * of the CUDA mipmapped array \p hMipmappedArray.
 *
 * If \p level is greater than the maximum number of levels in this mipmapped array,
 * ::CUDA_ERROR_INVALID_VALUE is returned.
 *
 * \param pLevelArray     - Returned mipmap level CUDA array
 * \param hMipmappedArray - CUDA mipmapped array
 * \param level           - Mipmap level
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_HANDLE
 * \notefnerr
 *
 * \sa
 * ::cuMipmappedArrayCreate,
 * ::cuMipmappedArrayDestroy,
 * ::cuArrayCreate,
 * ::cudaGetMipmappedArrayLevel
 */
CUresult CUDAAPI cuMipmappedArrayGetLevel(CUarray *pLevelArray, CUmipmappedArray hMipmappedArray, unsigned int level);

/**
 * \brief Destroys a CUDA mipmapped array
 *
 * Destroys the CUDA mipmapped array \p hMipmappedArray.
 *
 * \param hMipmappedArray - Mipmapped array to destroy
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_ARRAY_IS_MAPPED,
 * ::CUDA_ERROR_CONTEXT_IS_DESTROYED
 * \notefnerr
 *
 * \sa
 * ::cuMipmappedArrayCreate,
 * ::cuMipmappedArrayGetLevel,
 * ::cuArrayCreate,
 * ::cudaFreeMipmappedArray
 */
CUresult CUDAAPI cuMipmappedArrayDestroy(CUmipmappedArray hMipmappedArray);

/** 
* \brief Retrieve handle for an address range 
* 
* Get a handle of the specified type to an address range. The address range
* must have been obtained by a prior call to either ::cuMemAlloc or ::cuMemAddressReserve.
* If the address range was obtained via ::cuMemAddressReserve, it must also be fully mapped via ::cuMemMap.
* The address range must have been obtained by a prior call to either ::cuMemAllocHost or
* ::cuMemHostAlloc on Tegra.
* 
* Users must ensure the \p dptr and \p size are aligned to the host page size.
* 
* When requesting CUmemRangeHandleType::CU_MEM_RANGE_HANDLE_TYPE_DMA_BUF_FD,
* users are expected to query for dma_buf support for the platform
* by using ::CU_DEVICE_ATTRIBUTE_DMA_BUF_SUPPORTED device attribute before calling
* this API. The \p handle will be interpreted as a pointer to an integer to store the dma_buf file descriptor.
* Users must ensure the entire address range is backed and mapped when
* the address range is allocated by ::cuMemAddressReserve. All the physical
* allocations backing the address range must be resident on the same device and
* have identical allocation properties. Users are also expected to retrieve a
* new handle every time the underlying physical allocation(s) corresponding
* to a previously queried VA range are changed.
*
* For CUmemRangeHandleType::CU_MEM_RANGE_HANDLE_TYPE_DMA_BUF_FD, users may set
* flags to ::CU_MEM_RANGE_FLAG_DMA_BUF_MAPPING_TYPE_PCIE. Which when set on a
* supported platform, will give a DMA_BUF handle mapped via PCIE BAR1 or will
* return an error otherwise.
* 
* \param[out] handle     - Pointer to the location where the returned handle will be stored. 
* \param[in] dptr        - Pointer to a valid CUDA device allocation. Must be aligned to host page size.
* \param[in] size        - Length of the address range. Must be aligned to host page size.
* \param[in] handleType  - Type of handle requested (defines type and size of the \p handle output parameter)
* \param[in] flags       - When requesting CUmemRangeHandleType::CU_MEM_RANGE_HANDLE_TYPE_DMA_BUF_FD the value could be
*                          ::CU_MEM_RANGE_FLAG_DMA_BUF_MAPPING_TYPE_PCIE, otherwise 0.
* 
* \return
* CUDA_SUCCESS 
* CUDA_ERROR_INVALID_VALUE 
* CUDA_ERROR_NOT_SUPPORTED 
*/
CUresult CUDAAPI cuMemGetHandleForAddressRange(void *handle, CUdeviceptr dptr, size_t size, CUmemRangeHandleType handleType, unsigned long long flags);

/**
 * \brief Bitmasks for CU_DEVICE_ATTRIBUTE_MEM_DECOMPRESS_ALGORITHM_MASK.
 */
typedef enum CUmemDecompressAlgorithm_enum {
    CU_MEM_DECOMPRESS_UNSUPPORTED       = 0,    /**< Decompression is unsupported. */
    CU_MEM_DECOMPRESS_ALGORITHM_DEFLATE = 1<<0, /**< Deflate is supported. */
    CU_MEM_DECOMPRESS_ALGORITHM_SNAPPY  = 1<<1  /**< Snappy is supported. */
} CUmemDecompressAlgorithm;

/**
 * \brief Structure describing the parameters that compose a single
 *        decompression operation.
 */
typedef struct CUmemDecompressParams_st {
    /** The number of bytes to be read and decompressed from
     *  ::CUmemDecompressParams_st.src. */
    size_t srcNumBytes;
    /** The number of bytes that the decompression operation will be expected to
     *  write to ::CUmemDecompressParams_st.dst. This value is optional; if
     *  present, it may be used by the CUDA driver as a heuristic for scheduling
     *  the individual decompression operations. */
    size_t dstNumBytes;
    /** After the decompression operation has completed, the actual number of
     * bytes written to ::CUmemDecompressParams.dst will be recorded as a 32-bit
     * unsigned integer in the memory at this address. */
    cuuint32_t *dstActBytes;
    /** Pointer to a buffer of at least ::CUmemDecompressParams_st.srcNumBytes
      * compressed bytes. */
    const void *src;
    /** Pointer to a buffer where the decompressed data will be written. The
      * number of bytes written to this location will be recorded in the memory
      * pointed to by ::CUmemDecompressParams_st.dstActBytes */
    void *dst;
    /** The decompression algorithm to use. */
    CUmemDecompressAlgorithm algo;
    /*  These bytes are unused and must be zeroed. This ensures compatibility if
     *  additional fields are added in the future. */
    unsigned char padding[20];
} CUmemDecompressParams;

/**
 * \brief   Submit a batch of \p count independent decompression operations.
 *
 * \details Each of the \p count decompression operations is described by a
 *          single entry in the \p paramsArray array. Once the batch has been
 *          submitted, the function will return, and decompression will happen
 *          asynchronously w.r.t. the CPU. To the work completion tracking
 *          mechanisms in the CUDA driver, the batch will be considered a single
 *          unit of work and processed according to stream semantics, i.e., it
 *          is not possible to query the completion of individual decompression
 *          operations within a batch.
 *
 *          The memory pointed to by each of ::CUmemDecompressParams.src,
 *          ::CUmemDecompressParams.dst, and ::CUmemDecompressParams.dstActBytes,
 *          must be capable of usage with the hardware decompress feature. That
 *          is, for each of said pointers, the pointer attribute
 *          ::CU_POINTER_ATTRIBUTE_IS_MEM_DECOMPRESS_CAPABLE should give a
 *          non-zero value. To ensure this, the memory backing the pointers
 *          should have been allocated using one of the following CUDA memory
 *          allocators:
 *          * ::cuMemAlloc()
 *          * ::cuMemCreate() with the usage flag ::CU_MEM_CREATE_USAGE_HW_DECOMPRESS
 *          * ::cuMemAllocFromPoolAsync() from a pool that was created with
 *            the usage flag ::CU_MEM_POOL_CREATE_USAGE_HW_DECOMPRESS
 *          Additionally, ::CUmemDecompressParams.src, ::CUmemDecompressParams.dst,
 *          and ::CUmemDecompressParams.dstActBytes, must all be accessible from
 *          the device associated with the context where \p stream was created.
 *          For information on how to ensure this, see the documentation for the
 *          allocator of interest.
 *
 * \param[in]  paramsArray  The array of structures describing the independent
 *                          decompression operations.
 * \param[in]  count        The number of entries in \p paramsArray array.
 * \param[in]  flags        Must be 0.
 * \param[out] errorIndex   The index into \p paramsArray of the decompression
 *                          operation for which the error returned by this
 *                          function pertains to. If \p index is SIZE_MAX and
 *                          the value returned is not ::CUDA_SUCCESS, then the
 *                          error returned by this function should be considered
 *                          a general error that does not pertain to a
 *                          particular decompression operation. May be \p NULL,
 *                          in which case, no index will be recorded in the
 *                          event of error.
 * \param[in]  stream       The stream where the work will be enqueued.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_HANDLE
 * \notefnerr
 * \note_async
 * \note_null_stream
 *
 * \sa ::cuMemAlloc, ::cuMemPoolCreate, ::cuMemAllocFromPoolAsync
 */
CUresult CUDAAPI cuMemBatchDecompressAsync(
    CUmemDecompressParams *paramsArray,
    size_t count,
    unsigned int flags,
    size_t *errorIndex,
    CUstream stream
);

/** @} */ /* END CUDA_MEM */

/**
 * \defgroup CUDA_VA Virtual Memory Management
 *
 * ___MANBRIEF___ virtual memory management functions of the low-level CUDA driver API
 * (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the virtual memory management functions of the low-level CUDA
 * driver application programming interface.
 *
 * @{
 */

/**
* \brief Allocate an address range reservation. 
* 
* Reserves a virtual address range based on the given parameters, giving
* the starting address of the range in \p ptr.  This API requires a system that
* supports UVA.  The size and address parameters must be a multiple of the
* host page size and the alignment must be a power of two or zero for default
* alignment.
*
* \param[out] ptr       - Resulting pointer to start of virtual address range allocated
* \param[in]  size      - Size of the reserved virtual address range requested
* \param[in]  alignment - Alignment of the reserved virtual address range requested
* \param[in]  addr      - Fixed starting address range requested
* \param[in]  flags     - Currently unused, must be zero
* \return
* ::CUDA_SUCCESS,
* ::CUDA_ERROR_INVALID_VALUE,
* ::CUDA_ERROR_OUT_OF_MEMORY,
* ::CUDA_ERROR_NOT_INITIALIZED,
* ::CUDA_ERROR_DEINITIALIZED,
* ::CUDA_ERROR_NOT_PERMITTED,
* ::CUDA_ERROR_NOT_SUPPORTED
*
* \sa ::cuMemAddressFree
*/
CUresult CUDAAPI cuMemAddressReserve(CUdeviceptr *ptr, size_t size, size_t alignment, CUdeviceptr addr, unsigned long long flags);

/**
* \brief Free an address range reservation.
* 
* Frees a virtual address range reserved by cuMemAddressReserve.  The size
* must match what was given to memAddressReserve and the ptr given must
* match what was returned from memAddressReserve.
*
* \param[in] ptr  - Starting address of the virtual address range to free
* \param[in] size - Size of the virtual address region to free
* \return
* ::CUDA_SUCCESS,
* ::CUDA_ERROR_INVALID_VALUE,
* ::CUDA_ERROR_NOT_INITIALIZED,
* ::CUDA_ERROR_DEINITIALIZED,
* ::CUDA_ERROR_NOT_PERMITTED,
* ::CUDA_ERROR_NOT_SUPPORTED
*
* \sa ::cuMemAddressReserve
*/
CUresult CUDAAPI cuMemAddressFree(CUdeviceptr ptr, size_t size);

/**
* \brief Create a CUDA memory handle representing a memory allocation of a given size described by the given properties
*
* This creates a memory allocation on the target device specified through the
* \p prop structure. The created allocation will not have any device or host
* mappings. The generic memory \p handle for the allocation can be
* mapped to the address space of calling process via ::cuMemMap. This handle
* cannot be transmitted directly to other processes (see
* ::cuMemExportToShareableHandle).  On Windows, the caller must also pass
* an LPSECURITYATTRIBUTE in \p prop to be associated with this handle which
* limits or allows access to this handle for a recipient process (see
* ::CUmemAllocationProp::win32HandleMetaData for more).  The \p size of this
* allocation must be a multiple of the the value given via
* ::cuMemGetAllocationGranularity with the ::CU_MEM_ALLOC_GRANULARITY_MINIMUM
* flag.
* To create a CPU allocation targeting a specific host NUMA node, applications must
* set ::CUmemAllocationProp::CUmemLocation::type to ::CU_MEM_LOCATION_TYPE_HOST_NUMA and
* ::CUmemAllocationProp::CUmemLocation::id must specify the NUMA ID of the CPU.
* On systems where NUMA is not available ::CUmemAllocationProp::CUmemLocation::id must be set to 0.
* Specifying ::CU_MEM_LOCATION_TYPE_HOST_NUMA_CURRENT or ::CU_MEM_LOCATION_TYPE_HOST as the
* ::CUmemLocation::type will result in ::CUDA_ERROR_INVALID_VALUE.
*
* Applications that intend to use ::CU_MEM_HANDLE_TYPE_FABRIC based memory sharing must ensure:
* (1) `nvidia-caps-imex-channels` character device is created by the driver and is listed under /proc/devices 
* (2) have at least one IMEX channel file accessible by the user launching the application.
*
* When exporter and importer CUDA processes have been granted access to the same IMEX channel, they can securely
* share memory.
*
* The IMEX channel security model works on a per user basis. Which means all processes under a user can share
* memory if the user has access to a valid IMEX channel. When multi-user isolation is desired, a separate IMEX
* channel is required for each user.
*
* These channel files exist in /dev/nvidia-caps-imex-channels/channel* and can be created using standard OS
* native calls like mknod on Linux. For example: To create channel0 with the major number from /proc/devices
* users can execute the following command: `mknod /dev/nvidia-caps-imex-channels/channel0 c <major number> 0`
*
* If ::CUmemAllocationProp::allocFlags::usage contains ::CU_MEM_CREATE_USAGE_TILE_POOL flag then
* the memory allocation is intended only to be used as backing tile pool for sparse CUDA arrays
* and sparse CUDA mipmapped arrays.
* (see ::cuMemMapArrayAsync).
*
* \param[out] handle - Value of handle returned. All operations on this allocation are to be performed using this handle.
* \param[in]  size   - Size of the allocation requested
* \param[in]  prop   - Properties of the allocation to create.
* \param[in]  flags  - flags for future use, must be zero now.
* \return
* ::CUDA_SUCCESS,
* ::CUDA_ERROR_INVALID_VALUE,
* ::CUDA_ERROR_OUT_OF_MEMORY,
* ::CUDA_ERROR_INVALID_DEVICE,
* ::CUDA_ERROR_NOT_INITIALIZED,
* ::CUDA_ERROR_DEINITIALIZED,
* ::CUDA_ERROR_NOT_PERMITTED,
* ::CUDA_ERROR_NOT_SUPPORTED
* \notefnerr
*
* \sa ::cuMemRelease, ::cuMemExportToShareableHandle, ::cuMemImportFromShareableHandle
*/
CUresult CUDAAPI cuMemCreate(CUmemGenericAllocationHandle *handle, size_t size, const CUmemAllocationProp *prop, unsigned long long flags);

/**
* \brief Release a memory handle representing a memory allocation which was previously allocated through cuMemCreate.
* 
* Frees the memory that was allocated on a device through cuMemCreate.
*
* The memory allocation will be freed when all outstanding mappings to the memory
* are unmapped and when all outstanding references to the handle (including it's
* shareable counterparts) are also released. The generic memory handle can be
* freed when there are still outstanding mappings made with this handle. Each
* time a recipient process imports a shareable handle, it needs to pair it with
* ::cuMemRelease for the handle to be freed.  If \p handle is not a valid handle
* the behavior is undefined. 
*
* \param[in] handle Value of handle which was returned previously by cuMemCreate.
* \return
* ::CUDA_SUCCESS,
* ::CUDA_ERROR_INVALID_VALUE,
* ::CUDA_ERROR_NOT_INITIALIZED,
* ::CUDA_ERROR_DEINITIALIZED,
* ::CUDA_ERROR_NOT_PERMITTED,
* ::CUDA_ERROR_NOT_SUPPORTED
* \notefnerr
*
* \sa ::cuMemCreate
*/
CUresult CUDAAPI cuMemRelease(CUmemGenericAllocationHandle handle);

/**
* \brief Maps an allocation handle to a reserved virtual address range.
*
* Maps bytes of memory represented by \p handle starting from byte \p offset to
* \p size to address range [\p addr, \p addr + \p size]. This range must be an
* address reservation previously reserved with ::cuMemAddressReserve, and
* \p offset + \p size must be less than the size of the memory allocation.
* Both \p ptr, \p size, and \p offset must be a multiple of the value given via
* ::cuMemGetAllocationGranularity with the ::CU_MEM_ALLOC_GRANULARITY_MINIMUM flag.
* If \p handle represents a multicast object, \p ptr, \p size and \p offset must
* be aligned to the value returned by ::cuMulticastGetGranularity with the flag
* ::CU_MULTICAST_MINIMUM_GRANULARITY. For best performance however, it is
* recommended that \p ptr, \p size and \p offset be aligned to the value
* returned by ::cuMulticastGetGranularity with the flag
* ::CU_MULTICAST_RECOMMENDED_GRANULARITY.
* 
* Please note calling ::cuMemMap does not make the address accessible,
* the caller needs to update accessibility of a contiguous mapped VA
* range by calling ::cuMemSetAccess.
* 
* Once a recipient process obtains a shareable memory handle
* from ::cuMemImportFromShareableHandle, the process must
* use ::cuMemMap to map the memory into its address ranges before
* setting accessibility with ::cuMemSetAccess.
*  
* ::cuMemMap can only create mappings on VA range reservations 
* that are not currently mapped.
* 
* \param[in] ptr    - Address where memory will be mapped. 
* \param[in] size   - Size of the memory mapping. 
* \param[in] offset - Offset into the memory represented by 
*                   - \p handle from which to start mapping
*                   - Note: currently must be zero.
* \param[in] handle - Handle to a shareable memory 
* \param[in] flags  - flags for future use, must be zero now. 
* \return
* ::CUDA_SUCCESS,
* ::CUDA_ERROR_INVALID_VALUE,
* ::CUDA_ERROR_INVALID_DEVICE,
* ::CUDA_ERROR_OUT_OF_MEMORY,
* ::CUDA_ERROR_NOT_INITIALIZED,
* ::CUDA_ERROR_DEINITIALIZED,
* ::CUDA_ERROR_NOT_PERMITTED,
* ::CUDA_ERROR_NOT_SUPPORTED
* \notefnerr
*
* \sa ::cuMemUnmap, ::cuMemSetAccess, ::cuMemCreate, ::cuMemAddressReserve, ::cuMemImportFromShareableHandle
*/
CUresult CUDAAPI cuMemMap(CUdeviceptr ptr, size_t size, size_t offset, CUmemGenericAllocationHandle handle, unsigned long long flags);

/**
 * \brief Maps or unmaps subregions of sparse CUDA arrays and sparse CUDA mipmapped arrays
 *
 * Performs map or unmap operations on subregions of sparse CUDA arrays and sparse CUDA mipmapped arrays.
 * Each operation is specified by a ::CUarrayMapInfo entry in the \p mapInfoList array of size \p count.
 * The structure ::CUarrayMapInfo is defined as follow:
 \code
     typedef struct CUarrayMapInfo_st {
        CUresourcetype resourceType;                   
        union {
            CUmipmappedArray mipmap;
            CUarray array;
        } resource;

        CUarraySparseSubresourceType subresourceType;   
        union {
            struct {
                unsigned int level;                     
                unsigned int layer;                     
                unsigned int offsetX;                   
                unsigned int offsetY;                   
                unsigned int offsetZ;                   
                unsigned int extentWidth;               
                unsigned int extentHeight;              
                unsigned int extentDepth;               
            } sparseLevel;
            struct {
                unsigned int layer;
                unsigned long long offset;              
                unsigned long long size;                
            } miptail;
        } subresource;

        CUmemOperationType memOperationType;
        
        CUmemHandleType memHandleType;                  
        union {
            CUmemGenericAllocationHandle memHandle;
        } memHandle;

        unsigned long long offset;                      
        unsigned int deviceBitMask;                     
        unsigned int flags;                             
        unsigned int reserved[2];                       
    } CUarrayMapInfo;
 \endcode
 *
 * where ::CUarrayMapInfo::resourceType specifies the type of resource to be operated on.
 * If ::CUarrayMapInfo::resourceType is set to ::CUresourcetype::CU_RESOURCE_TYPE_ARRAY then 
 * ::CUarrayMapInfo::resource::array must be set to a valid sparse CUDA array handle.
 * The CUDA array must be either a 2D, 2D layered or 3D CUDA array and must have been allocated using
 * ::cuArrayCreate or ::cuArray3DCreate with the flag ::CUDA_ARRAY3D_SPARSE
 * or ::CUDA_ARRAY3D_DEFERRED_MAPPING.
 * For CUDA arrays obtained using ::cuMipmappedArrayGetLevel, ::CUDA_ERROR_INVALID_VALUE will be returned.
 * If ::CUarrayMapInfo::resourceType is set to ::CUresourcetype::CU_RESOURCE_TYPE_MIPMAPPED_ARRAY 
 * then ::CUarrayMapInfo::resource::mipmap must be set to a valid sparse CUDA mipmapped array handle.
 * The CUDA mipmapped array must be either a 2D, 2D layered or 3D CUDA mipmapped array and must have been
 * allocated using ::cuMipmappedArrayCreate with the flag ::CUDA_ARRAY3D_SPARSE
 * or ::CUDA_ARRAY3D_DEFERRED_MAPPING.
 *
 * ::CUarrayMapInfo::subresourceType specifies the type of subresource within the resource. 
 * ::CUarraySparseSubresourceType_enum is defined as:
 \code
    typedef enum CUarraySparseSubresourceType_enum {
        CU_ARRAY_SPARSE_SUBRESOURCE_TYPE_SPARSE_LEVEL = 0,
        CU_ARRAY_SPARSE_SUBRESOURCE_TYPE_MIPTAIL = 1
    } CUarraySparseSubresourceType;
 \endcode
 *
 * where ::CUarraySparseSubresourceType::CU_ARRAY_SPARSE_SUBRESOURCE_TYPE_SPARSE_LEVEL indicates a
 * sparse-miplevel which spans at least one tile in every dimension. The remaining miplevels which
 * are too small to span at least one tile in any dimension constitute the mip tail region as indicated by 
 * ::CUarraySparseSubresourceType::CU_ARRAY_SPARSE_SUBRESOURCE_TYPE_MIPTAIL subresource type.
 *
 * If ::CUarrayMapInfo::subresourceType is set to ::CUarraySparseSubresourceType::CU_ARRAY_SPARSE_SUBRESOURCE_TYPE_SPARSE_LEVEL
 * then ::CUarrayMapInfo::subresource::sparseLevel struct must contain valid array subregion offsets and extents.
 * The ::CUarrayMapInfo::subresource::sparseLevel::offsetX, ::CUarrayMapInfo::subresource::sparseLevel::offsetY
 * and ::CUarrayMapInfo::subresource::sparseLevel::offsetZ must specify valid X, Y and Z offsets respectively.
 * The ::CUarrayMapInfo::subresource::sparseLevel::extentWidth, ::CUarrayMapInfo::subresource::sparseLevel::extentHeight
 * and ::CUarrayMapInfo::subresource::sparseLevel::extentDepth must specify valid width, height and depth extents respectively.
 * These offsets and extents must be aligned to the corresponding tile dimension.
 * For CUDA mipmapped arrays ::CUarrayMapInfo::subresource::sparseLevel::level must specify a valid mip level index. Otherwise,
 * must be zero.
 * For layered CUDA arrays and layered CUDA mipmapped arrays ::CUarrayMapInfo::subresource::sparseLevel::layer must specify a valid layer index. Otherwise,
 * must be zero.
 * ::CUarrayMapInfo::subresource::sparseLevel::offsetZ must be zero and ::CUarrayMapInfo::subresource::sparseLevel::extentDepth
 * must be set to 1 for 2D and 2D layered CUDA arrays and CUDA mipmapped arrays.
 * Tile extents can be obtained by calling ::cuArrayGetSparseProperties and ::cuMipmappedArrayGetSparseProperties
 *
 * If ::CUarrayMapInfo::subresourceType is set to ::CUarraySparseSubresourceType::CU_ARRAY_SPARSE_SUBRESOURCE_TYPE_MIPTAIL
 * then ::CUarrayMapInfo::subresource::miptail struct must contain valid mip tail offset in 
 * ::CUarrayMapInfo::subresource::miptail::offset and size in ::CUarrayMapInfo::subresource::miptail::size.
 * Both, mip tail offset and mip tail size must be aligned to the tile size. 
 * For layered CUDA mipmapped arrays which don't have the flag ::CU_ARRAY_SPARSE_PROPERTIES_SINGLE_MIPTAIL set in ::CUDA_ARRAY_SPARSE_PROPERTIES::flags
 * as returned by ::cuMipmappedArrayGetSparseProperties, ::CUarrayMapInfo::subresource::miptail::layer must specify a valid layer index.
 * Otherwise, must be zero.
 *
 * If ::CUarrayMapInfo::resource::array or ::CUarrayMapInfo::resource::mipmap was created with ::CUDA_ARRAY3D_DEFERRED_MAPPING
 * flag set the ::CUarrayMapInfo::subresourceType and the contents of ::CUarrayMapInfo::subresource will be ignored.
 *
 * ::CUarrayMapInfo::memOperationType specifies the type of operation. ::CUmemOperationType is defined as:
 \code
    typedef enum CUmemOperationType_enum {
        CU_MEM_OPERATION_TYPE_MAP = 1,
        CU_MEM_OPERATION_TYPE_UNMAP = 2
    } CUmemOperationType;
 \endcode
 * If ::CUarrayMapInfo::memOperationType is set to ::CUmemOperationType::CU_MEM_OPERATION_TYPE_MAP then the subresource 
 * will be mapped onto the tile pool memory specified by ::CUarrayMapInfo::memHandle at offset ::CUarrayMapInfo::offset. 
 * The tile pool allocation has to be created by specifying the ::CU_MEM_CREATE_USAGE_TILE_POOL flag when calling ::cuMemCreate. Also, 
 * ::CUarrayMapInfo::memHandleType must be set to ::CUmemHandleType::CU_MEM_HANDLE_TYPE_GENERIC.
 * 
 * If ::CUarrayMapInfo::memOperationType is set to ::CUmemOperationType::CU_MEM_OPERATION_TYPE_UNMAP then an unmapping operation
 * is performed. ::CUarrayMapInfo::memHandle must be NULL.
 *
 * ::CUarrayMapInfo::deviceBitMask specifies the list of devices that must map or unmap physical memory. 
 * Currently, this mask must have exactly one bit set, and the corresponding device must match the device associated with the stream. 
 * If ::CUarrayMapInfo::memOperationType is set to ::CUmemOperationType::CU_MEM_OPERATION_TYPE_MAP, the device must also match 
 * the device associated with the tile pool memory allocation as specified by ::CUarrayMapInfo::memHandle.
 *
 * ::CUarrayMapInfo::flags and ::CUarrayMapInfo::reserved[] are unused and must be set to zero.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_HANDLE
 *
 * \param[in] mapInfoList - List of ::CUarrayMapInfo
 * \param[in] count       - Count of ::CUarrayMapInfo  in \p mapInfoList
 * \param[in] hStream     - Stream identifier for the stream to use for map or unmap operations
 *
 * \sa ::cuMipmappedArrayCreate, ::cuArrayCreate, ::cuArray3DCreate, ::cuMemCreate, ::cuArrayGetSparseProperties, ::cuMipmappedArrayGetSparseProperties
 */
CUresult CUDAAPI cuMemMapArrayAsync(CUarrayMapInfo  *mapInfoList, unsigned int count, CUstream hStream);

/**
* \brief Unmap the backing memory of a given address range.
*
* The range must be the entire contiguous address range that was mapped to.  In
* other words, ::cuMemUnmap cannot unmap a sub-range of an address range mapped
* by ::cuMemCreate / ::cuMemMap.  Any backing memory allocations will be freed
* if there are no existing mappings and there are no unreleased memory handles.
*
* When ::cuMemUnmap returns successfully the address range is converted to an
* address reservation and can be used for a future calls to ::cuMemMap.  Any new
* mapping to this virtual address will need to have access granted through
* ::cuMemSetAccess, as all mappings start with no accessibility setup.
*
* \param[in] ptr  - Starting address for the virtual address range to unmap
* \param[in] size - Size of the virtual address range to unmap
* \returns
* ::CUDA_SUCCESS,
* ::CUDA_ERROR_INVALID_VALUE,
* ::CUDA_ERROR_NOT_INITIALIZED,
* ::CUDA_ERROR_DEINITIALIZED,
* ::CUDA_ERROR_NOT_PERMITTED,
* ::CUDA_ERROR_NOT_SUPPORTED
* \notefnerr
* \note_sync
*
* \sa ::cuMemCreate, ::cuMemAddressReserve
*/
CUresult CUDAAPI cuMemUnmap(CUdeviceptr ptr, size_t size);

/**
* \brief Set the access flags for each location specified in \p desc for the given virtual address range
* 
* Given the virtual address range via \p ptr and \p size, and the locations
* in the array given by \p desc and \p count, set the access flags for the
* target locations.  The range must be a fully mapped address range
* containing all allocations created by ::cuMemMap / ::cuMemCreate.
* Users cannot specify ::CU_MEM_LOCATION_TYPE_HOST_NUMA accessibility for allocations created on with other location types.
* Note: When ::CUmemAccessDesc::CUmemLocation::type is ::CU_MEM_LOCATION_TYPE_HOST_NUMA, ::CUmemAccessDesc::CUmemLocation::id
* is ignored.
* When setting the access flags for a virtual address range mapping a multicast
* object, \p ptr and \p size must be aligned to the value returned by
* ::cuMulticastGetGranularity with the flag ::CU_MULTICAST_MINIMUM_GRANULARITY.
* For best performance however, it is recommended that \p ptr and \p size be
* aligned to the value returned by ::cuMulticastGetGranularity with the flag
* ::CU_MULTICAST_RECOMMENDED_GRANULARITY.
*
* \param[in] ptr   - Starting address for the virtual address range
* \param[in] size  - Length of the virtual address range
* \param[in] desc  - Array of ::CUmemAccessDesc that describe how to change the
*                  - mapping for each location specified
* \param[in] count - Number of ::CUmemAccessDesc in \p desc
* \returns
* ::CUDA_SUCCESS,
* ::CUDA_ERROR_INVALID_VALUE,
* ::CUDA_ERROR_INVALID_DEVICE,
* ::CUDA_ERROR_NOT_SUPPORTED
* \notefnerr
* \note_sync
*
* \sa ::cuMemSetAccess, ::cuMemCreate, :cuMemMap
*/
CUresult CUDAAPI cuMemSetAccess(CUdeviceptr ptr, size_t size, const CUmemAccessDesc *desc, size_t count);

/**
* \brief Get the access \p flags set for the given \p location and \p ptr
*
* \param[out] flags   - Flags set for this location
* \param[in] location - Location in which to check the flags for
* \param[in] ptr      - Address in which to check the access flags for
* \returns
* ::CUDA_SUCCESS,
* ::CUDA_ERROR_INVALID_VALUE,
* ::CUDA_ERROR_INVALID_DEVICE,
* ::CUDA_ERROR_NOT_INITIALIZED,
* ::CUDA_ERROR_DEINITIALIZED,
* ::CUDA_ERROR_NOT_PERMITTED,
* ::CUDA_ERROR_NOT_SUPPORTED
*
* \sa ::cuMemSetAccess
*/
CUresult CUDAAPI cuMemGetAccess(unsigned long long *flags, const CUmemLocation *location, CUdeviceptr ptr);

/**
* \brief Exports an allocation to a requested shareable handle type
*
* Given a CUDA memory handle, create a shareable memory
* allocation handle that can be used to share the memory with other
* processes. The recipient process can convert the shareable handle back into a
* CUDA memory handle using ::cuMemImportFromShareableHandle and map
* it with ::cuMemMap. The implementation of what this handle is and how it
* can be transferred is defined by the requested handle type in \p handleType
*
* Once all shareable handles are closed and the allocation is released, the allocated
* memory referenced will be released back to the OS and uses of the CUDA handle afterward
* will lead to undefined behavior.
*
* This API can also be used in conjunction with other APIs (e.g. Vulkan, OpenGL)
* that support importing memory from the shareable type
*
* \param[out] shareableHandle - Pointer to the location in which to store the requested handle type
* \param[in] handle           - CUDA handle for the memory allocation
* \param[in] handleType       - Type of shareable handle requested (defines type and size of the \p shareableHandle output parameter)
* \param[in] flags            - Reserved, must be zero
* \returns
* ::CUDA_SUCCESS,
* ::CUDA_ERROR_INVALID_VALUE,
* ::CUDA_ERROR_NOT_INITIALIZED,
* ::CUDA_ERROR_DEINITIALIZED,
* ::CUDA_ERROR_NOT_PERMITTED,
* ::CUDA_ERROR_NOT_SUPPORTED
*
* \sa ::cuMemImportFromShareableHandle
*/
CUresult CUDAAPI cuMemExportToShareableHandle(void *shareableHandle, CUmemGenericAllocationHandle handle, CUmemAllocationHandleType handleType, unsigned long long flags);

/**
* \brief Imports an allocation from a requested shareable handle type.
*
* If the current process cannot support the memory described by this shareable
* handle, this API will error as ::CUDA_ERROR_NOT_SUPPORTED.
*
* If \p shHandleType is ::CU_MEM_HANDLE_TYPE_FABRIC and the importer process has not been
* granted access to the same IMEX channel as the exporter process, this API will error
* as ::CUDA_ERROR_NOT_PERMITTED.
*
* \note Importing shareable handles exported from some graphics APIs(VUlkan, OpenGL, etc)
* created on devices under an SLI group may not be supported, and thus this API will
* return CUDA_ERROR_NOT_SUPPORTED.
* There is no guarantee that the contents of \p handle will be the same CUDA memory handle
* for the same given OS shareable handle, or the same underlying allocation.
*
* \param[out] handle       - CUDA Memory handle for the memory allocation.
* \param[in]  osHandle     - Shareable Handle representing the memory allocation that is to be imported. 
* \param[in]  shHandleType - handle type of the exported handle ::CUmemAllocationHandleType.
* \returns
* ::CUDA_SUCCESS,
* ::CUDA_ERROR_INVALID_VALUE,
* ::CUDA_ERROR_NOT_INITIALIZED,
* ::CUDA_ERROR_DEINITIALIZED,
* ::CUDA_ERROR_NOT_PERMITTED,
* ::CUDA_ERROR_NOT_SUPPORTED
*
* \sa ::cuMemExportToShareableHandle, ::cuMemMap, ::cuMemRelease
*/
CUresult CUDAAPI cuMemImportFromShareableHandle(CUmemGenericAllocationHandle *handle, void *osHandle, CUmemAllocationHandleType shHandleType);

/**
* \brief Calculates either the minimal or recommended granularity 
*
* Calculates either the minimal or recommended granularity
* for a given allocation specification and returns it in granularity.  This
* granularity can be used as a multiple for alignment, size, or address mapping.
*
* \param[out] granularity Returned granularity.
* \param[in]  prop Property for which to determine the granularity for
* \param[in]  option Determines which granularity to return
* \returns
* ::CUDA_SUCCESS,
* ::CUDA_ERROR_INVALID_VALUE,
* ::CUDA_ERROR_NOT_INITIALIZED,
* ::CUDA_ERROR_DEINITIALIZED,
* ::CUDA_ERROR_NOT_PERMITTED,
* ::CUDA_ERROR_NOT_SUPPORTED
*
* \sa ::cuMemCreate, ::cuMemMap
*/
CUresult CUDAAPI cuMemGetAllocationGranularity(size_t *granularity, const CUmemAllocationProp *prop, CUmemAllocationGranularity_flags option);

/**
* \brief Retrieve the contents of the property structure defining properties for this handle
*
* \param[out] prop  - Pointer to a properties structure which will hold the information about this handle
* \param[in] handle - Handle which to perform the query on
* \returns
* ::CUDA_SUCCESS,
* ::CUDA_ERROR_INVALID_VALUE,
* ::CUDA_ERROR_NOT_INITIALIZED,
* ::CUDA_ERROR_DEINITIALIZED,
* ::CUDA_ERROR_NOT_PERMITTED,
* ::CUDA_ERROR_NOT_SUPPORTED
*
* \sa ::cuMemCreate, ::cuMemImportFromShareableHandle
*/
CUresult CUDAAPI cuMemGetAllocationPropertiesFromHandle(CUmemAllocationProp *prop, CUmemGenericAllocationHandle handle);

/**
* \brief Given an address \p addr, returns the allocation handle of the backing memory allocation.
*
* The handle is guaranteed to be the same handle value used to map the memory. If the address
* requested is not mapped, the function will fail. The returned handle must be released with
* corresponding number of calls to ::cuMemRelease.
*
* \note The address \p addr, can be any address in a range previously mapped
* by ::cuMemMap, and not necessarily the start address.
*
* \param[out] handle CUDA Memory handle for the backing memory allocation.
* \param[in] addr Memory address to query, that has been mapped previously.
* \returns
* ::CUDA_SUCCESS,
* ::CUDA_ERROR_INVALID_VALUE,
* ::CUDA_ERROR_NOT_INITIALIZED,
* ::CUDA_ERROR_DEINITIALIZED,
* ::CUDA_ERROR_NOT_PERMITTED,
* ::CUDA_ERROR_NOT_SUPPORTED
*
* \sa ::cuMemCreate, ::cuMemRelease, ::cuMemMap
*/
CUresult CUDAAPI cuMemRetainAllocationHandle(CUmemGenericAllocationHandle *handle, void *addr);

/** @} */ /* END CUDA_VA */

/**
 * \defgroup CUDA_MALLOC_ASYNC Stream Ordered Memory Allocator
 *
 * ___MANBRIEF___ Functions for performing allocation and free operations in stream order.
 *                Functions for controlling the behavior of the underlying allocator.
 * (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the stream ordered memory allocator exposed by the
 * low-level CUDA driver application programming interface.
 *
 * @{
 *
 * \section CUDA_MALLOC_ASYNC_overview overview
 *
 * The asynchronous allocator allows the user to allocate and free in stream order.
 * All asynchronous accesses of the allocation must happen between
 * the stream executions of the allocation and the free. If the memory is accessed
 * outside of the promised stream order, a use before allocation / use after free error
 * will cause undefined behavior.
 *
 * The allocator is free to reallocate the memory as long as it can guarantee
 * that compliant memory accesses will not overlap temporally.
 * The allocator may refer to internal stream ordering as well as inter-stream dependencies
 * (such as CUDA events and null stream dependencies) when establishing the temporal guarantee.
 * The allocator may also insert inter-stream dependencies to establish the temporal guarantee. 
 *
 * \section CUDA_MALLOC_ASYNC_support Supported Platforms
 *
 * Whether or not a device supports the integrated stream ordered memory allocator
 * may be queried by calling ::cuDeviceGetAttribute() with the device attribute
 * ::CU_DEVICE_ATTRIBUTE_MEMORY_POOLS_SUPPORTED
 */

/**
 * \brief Frees memory with stream ordered semantics
 *
 * Inserts a free operation into \p hStream.
 * The allocation must not be accessed after stream execution reaches the free.
 * After this API returns, accessing the memory from any subsequent work launched on the GPU
 * or querying its pointer attributes results in undefined behavior.
 *
 * \note During stream capture, this function results in the creation of a free node and
 *       must therefore be passed the address of a graph allocation.
 * 
 * \param dptr - memory to free
 * \param hStream - The stream establishing the stream ordering contract. 
 * \returns
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT (default stream specified with no current context),
 * ::CUDA_ERROR_NOT_SUPPORTED
 */
CUresult CUDAAPI cuMemFreeAsync(CUdeviceptr dptr, CUstream hStream);

/**
 * \brief Allocates memory with stream ordered semantics
 *
 * Inserts an allocation operation into \p hStream.
 * A pointer to the allocated memory is returned immediately in *dptr.
 * The allocation must not be accessed until the the allocation operation completes.
 * The allocation comes from the memory pool current to the stream's device.
 *
 * \note The default memory pool of a device contains device memory from that device.
 * \note Basic stream ordering allows future work submitted into the same stream to use the allocation.
 *       Stream query, stream synchronize, and CUDA events can be used to guarantee that the allocation
 *       operation completes before work submitted in a separate stream runs. 
 * \note During stream capture, this function results in the creation of an allocation node.  In this case,
 *       the allocation is owned by the graph instead of the memory pool. The memory pool's properties
 *       are used to set the node's creation parameters.
 *
 * \param[out] dptr    - Returned device pointer
 * \param[in] bytesize - Number of bytes to allocate
 * \param[in] hStream  - The stream establishing the stream ordering contract and the memory pool to allocate from
 * \returns
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT (default stream specified with no current context),
 * ::CUDA_ERROR_NOT_SUPPORTED,
 * ::CUDA_ERROR_OUT_OF_MEMORY
 *
 * \sa ::cuMemAllocFromPoolAsync, ::cuMemFreeAsync, ::cuDeviceSetMemPool,
 *     ::cuDeviceGetDefaultMemPool, ::cuDeviceGetMemPool, ::cuMemPoolCreate,
 *     ::cuMemPoolSetAccess, ::cuMemPoolSetAttribute
 */
CUresult CUDAAPI cuMemAllocAsync(CUdeviceptr *dptr, size_t bytesize, CUstream hStream);

/**
 * \brief Tries to release memory back to the OS
 *
 * Releases memory back to the OS until the pool contains fewer than minBytesToKeep
 * reserved bytes, or there is no more memory that the allocator can safely release.
 * The allocator cannot release OS allocations that back outstanding asynchronous allocations.
 * The OS allocations may happen at different granularity from the user allocations.
 *
 * \note: Allocations that have not been freed count as outstanding. 
 * \note: Allocations that have been asynchronously freed but whose completion has
 *        not been observed on the host (eg. by a synchronize) can count as outstanding.
 *
 * \param[in] pool           - The memory pool to trim
 * \param[in] minBytesToKeep - If the pool has less than minBytesToKeep reserved,
 * the TrimTo operation is a no-op.  Otherwise the pool will be guaranteed to have
 * at least minBytesToKeep bytes reserved after the operation.
 * \returns
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa ::cuMemAllocAsync, ::cuMemFreeAsync, ::cuDeviceGetDefaultMemPool,
 *     ::cuDeviceGetMemPool, ::cuMemPoolCreate
 */
CUresult CUDAAPI cuMemPoolTrimTo(CUmemoryPool pool, size_t minBytesToKeep);

/**
 * \brief Sets attributes of a memory pool
 *
 * Supported attributes are:
 * - ::CU_MEMPOOL_ATTR_RELEASE_THRESHOLD: (value type = cuuint64_t)
 *                    Amount of reserved memory in bytes to hold onto before trying
 *                    to release memory back to the OS. When more than the release
 *                    threshold bytes of memory are held by the memory pool, the
 *                    allocator will try to release memory back to the OS on the
 *                    next call to stream, event or context synchronize. (default 0)
 * - ::CU_MEMPOOL_ATTR_REUSE_FOLLOW_EVENT_DEPENDENCIES: (value type = int)
 *                    Allow ::cuMemAllocAsync to use memory asynchronously freed
 *                    in another stream as long as a stream ordering dependency
 *                    of the allocating stream on the free action exists.
 *                    Cuda events and null stream interactions can create the required
 *                    stream ordered dependencies. (default enabled)
 * - ::CU_MEMPOOL_ATTR_REUSE_ALLOW_OPPORTUNISTIC: (value type = int)
 *                    Allow reuse of already completed frees when there is no dependency
 *                    between the free and allocation. (default enabled)
 * - ::CU_MEMPOOL_ATTR_REUSE_ALLOW_INTERNAL_DEPENDENCIES: (value type = int)
 *                    Allow ::cuMemAllocAsync to insert new stream dependencies
 *                    in order to establish the stream ordering required to reuse
 *                    a piece of memory released by ::cuMemFreeAsync (default enabled).
 * - ::CU_MEMPOOL_ATTR_RESERVED_MEM_HIGH: (value type = cuuint64_t)
 *                    Reset the high watermark that tracks the amount of backing memory that was
 *                    allocated for the memory pool. It is illegal to set this attribute to a non-zero value.
 * - ::CU_MEMPOOL_ATTR_USED_MEM_HIGH: (value type = cuuint64_t)
 *                    Reset the high watermark that tracks the amount of used memory that was
 *                    allocated for the memory pool.
 *
 * \param[in] pool  - The memory pool to modify
 * \param[in] attr  - The attribute to modify
 * \param[in] value - Pointer to the value to assign
 *
 * \returns
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa ::cuMemAllocAsync, ::cuMemFreeAsync, ::cuDeviceGetDefaultMemPool,
 *     ::cuDeviceGetMemPool, ::cuMemPoolCreate
 */
CUresult CUDAAPI cuMemPoolSetAttribute(CUmemoryPool pool, CUmemPool_attribute attr, void *value);

/**
 * \brief Gets attributes of a memory pool
 *
 * Supported attributes are:
 * - ::CU_MEMPOOL_ATTR_RELEASE_THRESHOLD: (value type = cuuint64_t)
 *                    Amount of reserved memory in bytes to hold onto before trying
 *                    to release memory back to the OS. When more than the release
 *                    threshold bytes of memory are held by the memory pool, the
 *                    allocator will try to release memory back to the OS on the
 *                    next call to stream, event or context synchronize. (default 0)
 * - ::CU_MEMPOOL_ATTR_REUSE_FOLLOW_EVENT_DEPENDENCIES: (value type = int)
 *                    Allow ::cuMemAllocAsync to use memory asynchronously freed
 *                    in another stream as long as a stream ordering dependency
 *                    of the allocating stream on the free action exists.
 *                    Cuda events and null stream interactions can create the required
 *                    stream ordered dependencies. (default enabled)
 * - ::CU_MEMPOOL_ATTR_REUSE_ALLOW_OPPORTUNISTIC: (value type = int)
 *                    Allow reuse of already completed frees when there is no dependency
 *                    between the free and allocation. (default enabled)
 * - ::CU_MEMPOOL_ATTR_REUSE_ALLOW_INTERNAL_DEPENDENCIES: (value type = int)
 *                    Allow ::cuMemAllocAsync to insert new stream dependencies
 *                    in order to establish the stream ordering required to reuse
 *                    a piece of memory released by ::cuMemFreeAsync (default enabled).
 * - ::CU_MEMPOOL_ATTR_RESERVED_MEM_CURRENT: (value type = cuuint64_t)
 *                    Amount of backing memory currently allocated for the mempool
 * - ::CU_MEMPOOL_ATTR_RESERVED_MEM_HIGH: (value type = cuuint64_t)
 *                    High watermark of backing memory allocated for the mempool since the
 *                    last time it was reset.
 * - ::CU_MEMPOOL_ATTR_USED_MEM_CURRENT: (value type = cuuint64_t)
 *                    Amount of memory from the pool that is currently in use by the application.
 * - ::CU_MEMPOOL_ATTR_USED_MEM_HIGH: (value type = cuuint64_t)
 *                    High watermark of the amount of memory from the pool that was in use by the application.
 *
 * \param[in] pool   - The memory pool to get attributes of
 * \param[in] attr   - The attribute to get 
 * \param[out] value - Retrieved value
 *
 * \returns
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa ::cuMemAllocAsync, ::cuMemFreeAsync, ::cuDeviceGetDefaultMemPool,
 *     ::cuDeviceGetMemPool, ::cuMemPoolCreate
 */
CUresult CUDAAPI cuMemPoolGetAttribute(CUmemoryPool pool, CUmemPool_attribute attr, void *value);

/**
 * \brief Controls visibility of pools between devices
 *
 * \param[in] pool  - The pool being modified
 * \param[in] map   - Array of access descriptors. Each descriptor instructs the access to enable for a single gpu.
 * \param[in] count - Number of descriptors in the map array.
 *
 * \returns
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa ::cuMemAllocAsync, ::cuMemFreeAsync, ::cuDeviceGetDefaultMemPool,
 *     ::cuDeviceGetMemPool, ::cuMemPoolCreate
 */
CUresult CUDAAPI cuMemPoolSetAccess(CUmemoryPool pool, const CUmemAccessDesc *map, size_t count);

/**
 * \brief Returns the accessibility of a pool from a device
 *
 * Returns the accessibility of the pool's memory from the specified location. 
 *
 * \param[out] flags   - the accessibility of the pool from the specified location
 * \param[in] memPool  - the pool being queried
 * \param[in] location - the location accessing the pool
 *
 * \sa ::cuMemAllocAsync, ::cuMemFreeAsync, ::cuDeviceGetDefaultMemPool,
 *     ::cuDeviceGetMemPool, ::cuMemPoolCreate
 */
CUresult CUDAAPI cuMemPoolGetAccess(CUmemAccess_flags *flags, CUmemoryPool memPool, CUmemLocation *location);

/**
 * \brief Creates a memory pool
 *
 * Creates a CUDA memory pool and returns the handle in \p pool.  The \p poolProps determines
 * the properties of the pool such as the backing device and IPC capabilities. 
 *
 * To create a memory pool targeting a specific host NUMA node, applications must
 * set ::CUmemPoolProps::CUmemLocation::type to ::CU_MEM_LOCATION_TYPE_HOST_NUMA and
 * ::CUmemPoolProps::CUmemLocation::id must specify the NUMA ID of the host memory node.
 * Specifying ::CU_MEM_LOCATION_TYPE_HOST_NUMA_CURRENT or ::CU_MEM_LOCATION_TYPE_HOST as the
 * ::CUmemPoolProps::CUmemLocation::type will result in ::CUDA_ERROR_INVALID_VALUE.
* By default, the pool's memory will be accessible from the device it is allocated on.
 * In the case of pools created with ::CU_MEM_LOCATION_TYPE_HOST_NUMA, their default accessibility
 * will be from the host CPU.
 * Applications can control the maximum size of the pool by specifying a non-zero value for ::CUmemPoolProps::maxSize.
 * If set to 0, the maximum size of the pool will default to a system dependent value.
 *
 * Applications that intend to use ::CU_MEM_HANDLE_TYPE_FABRIC based memory sharing must ensure:
 * (1) `nvidia-caps-imex-channels` character device is created by the driver and is listed under /proc/devices 
 * (2) have at least one IMEX channel file accessible by the user launching the application.
 *
 * When exporter and importer CUDA processes have been granted access to the same IMEX channel, they can securely
 * share memory.
 *
 * The IMEX channel security model works on a per user basis. Which means all processes under a user can share
 * memory if the user has access to a valid IMEX channel. When multi-user isolation is desired, a separate IMEX
 * channel is required for each user.
 *
 * These channel files exist in /dev/nvidia-caps-imex-channels/channel* and can be created using standard OS
 * native calls like mknod on Linux. For example: To create channel0 with the major number from /proc/devices
 * users can execute the following command: `mknod /dev/nvidia-caps-imex-channels/channel0 c <major number> 0`
 *
 * \note Specifying CU_MEM_HANDLE_TYPE_NONE creates a memory pool that will not support IPC.
 *
 * \returns
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_OUT_OF_MEMORY,
 * ::CUDA_ERROR_NOT_PERMITTED
 * ::CUDA_ERROR_NOT_SUPPORTED
 *
 * \sa ::cuDeviceSetMemPool, ::cuDeviceGetMemPool, ::cuDeviceGetDefaultMemPool,
 *     ::cuMemAllocFromPoolAsync, ::cuMemPoolExportToShareableHandle
 */
CUresult CUDAAPI cuMemPoolCreate(CUmemoryPool *pool, const CUmemPoolProps *poolProps);

/**
 * \brief Destroys the specified memory pool
 *
 * If any pointers obtained from this pool haven't been freed or
 * the pool has free operations that haven't completed
 * when ::cuMemPoolDestroy is invoked, the function will return immediately and the
 * resources associated with the pool will be released automatically
 * once there are no more outstanding allocations. 
 *
 * Destroying the current mempool of a device sets the default mempool of
 * that device as the current mempool for that device.
 *
 * \note A device's default memory pool cannot be destroyed.
 *
 * \returns
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa ::cuMemFreeAsync, ::cuDeviceSetMemPool, ::cuDeviceGetMemPool,
 *     ::cuDeviceGetDefaultMemPool, ::cuMemPoolCreate
 */
CUresult CUDAAPI cuMemPoolDestroy(CUmemoryPool pool);

/**
 * \brief Allocates memory from a specified pool with stream ordered semantics.
 *
 * Inserts an allocation operation into \p hStream.
 * A pointer to the allocated memory is returned immediately in *dptr.
 * The allocation must not be accessed until the the allocation operation completes.
 * The allocation comes from the specified memory pool.
 *
 * \note
 *    -  The specified memory pool may be from a device different than that of the specified \p hStream. 
 * 
 *    -  Basic stream ordering allows future work submitted into the same stream to use the allocation.
 *       Stream query, stream synchronize, and CUDA events can be used to guarantee that the allocation
 *       operation completes before work submitted in a separate stream runs. 
 *
 * \note During stream capture, this function results in the creation of an allocation node.  In this case,
 *       the allocation is owned by the graph instead of the memory pool. The memory pool's properties
 *       are used to set the node's creation parameters.
 *
 * \param[out] dptr    - Returned device pointer
 * \param[in] bytesize - Number of bytes to allocate
 * \param[in] pool     - The pool to allocate from 
 * \param[in] hStream  - The stream establishing the stream ordering semantic
 *
 * \returns
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT (default stream specified with no current context),
 * ::CUDA_ERROR_NOT_SUPPORTED,
 * ::CUDA_ERROR_OUT_OF_MEMORY
 *
 * \sa ::cuMemAllocAsync, ::cuMemFreeAsync, ::cuDeviceGetDefaultMemPool,
 *     ::cuDeviceGetMemPool, ::cuMemPoolCreate, ::cuMemPoolSetAccess,
 *     ::cuMemPoolSetAttribute
 */
CUresult CUDAAPI cuMemAllocFromPoolAsync(CUdeviceptr *dptr, size_t bytesize, CUmemoryPool pool, CUstream hStream);

/**
 * \brief Exports a memory pool to the requested handle type.
 *
 * Given an IPC capable mempool, create an OS handle to share the pool with another process.
 * A recipient process can convert the shareable handle into a mempool with ::cuMemPoolImportFromShareableHandle.
 * Individual pointers can then be shared with the ::cuMemPoolExportPointer and ::cuMemPoolImportPointer APIs.
 * The implementation of what the shareable handle is and how it can be transferred is defined by the requested
 * handle type.
 *
 * \note: To create an IPC capable mempool, create a mempool with a CUmemAllocationHandleType other than CU_MEM_HANDLE_TYPE_NONE.
 *
 * \param[out] handle_out  - Returned OS handle 
 * \param[in] pool         - pool to export 
 * \param[in] handleType   - the type of handle to create 
 * \param[in] flags        - must be 0 
 *
 * \returns
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_OUT_OF_MEMORY
 *
 * \sa ::cuMemPoolImportFromShareableHandle, ::cuMemPoolExportPointer,
 *     ::cuMemPoolImportPointer, ::cuMemAllocAsync, ::cuMemFreeAsync,
 *     ::cuDeviceGetDefaultMemPool, ::cuDeviceGetMemPool, ::cuMemPoolCreate,
 *     ::cuMemPoolSetAccess, ::cuMemPoolSetAttribute
 */
CUresult CUDAAPI cuMemPoolExportToShareableHandle(void *handle_out, CUmemoryPool pool, CUmemAllocationHandleType handleType, unsigned long long flags);

/**
 * \brief imports a memory pool from a shared handle.
 *
 * Specific allocations can be imported from the imported pool with cuMemPoolImportPointer.
 *
 * If \p handleType is ::CU_MEM_HANDLE_TYPE_FABRIC and the importer process has not been
 * granted access to the same IMEX channel as the exporter process, this API will error
 * as ::CUDA_ERROR_NOT_PERMITTED.
 * 
 *
 * \note Imported memory pools do not support creating new allocations.
 *       As such imported memory pools may not be used in cuDeviceSetMemPool
 *       or ::cuMemAllocFromPoolAsync calls.
 *
 * \param[out] pool_out    - Returned memory pool
 * \param[in] handle       - OS handle of the pool to open 
 * \param[in] handleType   - The type of handle being imported 
 * \param[in] flags        - must be 0 
 *
 * \returns
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_OUT_OF_MEMORY
 *
 * \sa ::cuMemPoolExportToShareableHandle, ::cuMemPoolExportPointer, ::cuMemPoolImportPointer
 */
CUresult CUDAAPI cuMemPoolImportFromShareableHandle(
        CUmemoryPool *pool_out,
        void *handle,
        CUmemAllocationHandleType handleType,
        unsigned long long flags);

/**
 * \brief Export data to share a memory pool allocation between processes.
 *
 * Constructs \p shareData_out for sharing a specific allocation from an already shared memory pool.
 * The recipient process can import the allocation with the ::cuMemPoolImportPointer api.
 * The data is not a handle and may be shared through any IPC mechanism.
 *
 * \param[out] shareData_out - Returned export data  
 * \param[in] ptr            - pointer to memory being exported
 *
 * \returns
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_OUT_OF_MEMORY
 *
 * \sa ::cuMemPoolExportToShareableHandle, ::cuMemPoolImportFromShareableHandle, ::cuMemPoolImportPointer
 */
CUresult CUDAAPI cuMemPoolExportPointer(CUmemPoolPtrExportData *shareData_out, CUdeviceptr ptr);

/**
 * \brief Import a memory pool allocation from another process.
 *
 * Returns in \p ptr_out a pointer to the imported memory.
 * The imported memory must not be accessed before the allocation operation completes
 * in the exporting process. The imported memory must be freed from all importing processes before
 * being freed in the exporting process. The pointer may be freed with cuMemFree
 * or cuMemFreeAsync.  If cuMemFreeAsync is used, the free must be completed
 * on the importing process before the free operation on the exporting process.
 *
 * \note The cuMemFreeAsync api may be used in the exporting process before
 *       the cuMemFreeAsync operation completes in its stream as long as the
 *       cuMemFreeAsync in the exporting process specifies a stream with
 *       a stream dependency on the importing process's cuMemFreeAsync.
 *
 * \param[out] ptr_out  - pointer to imported memory
 * \param[in] pool      - pool from which to import
 * \param[in] shareData - data specifying the memory to import
 *
 * \returns
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_OUT_OF_MEMORY
 *
 * \sa ::cuMemPoolExportToShareableHandle, ::cuMemPoolImportFromShareableHandle, ::cuMemPoolExportPointer
 */
CUresult CUDAAPI cuMemPoolImportPointer(CUdeviceptr *ptr_out, CUmemoryPool pool, CUmemPoolPtrExportData *shareData);

/** @} */ /* END CUDA_MALLOC_ASYNC */

/**
 * \defgroup CUDA_MULTICAST Multicast Object Management
 *
 * ___MANBRIEF___ Functions for creating multicast objects, adding devices to them and binding/unbinding memory
 * (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the CUDA multicast object operations exposed by the
 * low-level CUDA driver application programming interface.
 *
 * @{
 *
 * \section CUDA_MULTICAST_overview overview
 *
 * A multicast object created via ::cuMulticastCreate enables certain memory
 * operations to be broadcast to a team of devices. Devices can be added to a
 * multicast object via ::cuMulticastAddDevice. Memory can be bound on each
 * participating device via either ::cuMulticastBindMem or ::cuMulticastBindAddr.
 * Multicast objects can be mapped into a device's virtual address space using
 * the virtual memmory management APIs (see ::cuMemMap and ::cuMemSetAccess).
 *
 * \section CUDA_MULTICAST_support Supported Platforms
 *
 * Support for multicast on a specific device can be queried using the device
 * attribute ::CU_DEVICE_ATTRIBUTE_MULTICAST_SUPPORTED
 */

/**
 * \brief Create a generic allocation handle representing a multicast object described by the given properties.
 *
 * This creates a multicast object as described by \p prop. The number of
 * participating devices is specified by ::CUmulticastObjectProp::numDevices.
 * Devices can be added to the multicast object via ::cuMulticastAddDevice.
 * All participating devices must be added to the multicast object before memory
 * can be bound to it. Memory is bound to the multicast object via either
 * ::cuMulticastBindMem or ::cuMulticastBindAddr, and can be unbound via
 * ::cuMulticastUnbind. The total amount of memory that can be bound per device
 * is specified by :CUmulticastObjectProp::size. This size must be a multiple of
 * the value returned by ::cuMulticastGetGranularity with the flag
 * ::CU_MULTICAST_GRANULARITY_MINIMUM. For best performance however, the size
 * should be aligned to the value returned by ::cuMulticastGetGranularity with
 * the flag ::CU_MULTICAST_GRANULARITY_RECOMMENDED.
 *
 * After all participating devices have been added, multicast objects can also
 * be mapped to a device's virtual address space using the virtual memory
 * management APIs (see ::cuMemMap and ::cuMemSetAccess). Multicast objects can
 * also be shared with other processes by requesting a shareable handle via
 * ::cuMemExportToShareableHandle. Note that the desired types of shareable
 * handles must be specified in the bitmask ::CUmulticastObjectProp::handleTypes.
 * Multicast objects can be released using the virtual memory management API
 * ::cuMemRelease.
 *
 * \param[out] mcHandle     Value of handle returned.
 * \param[in]  prop         Properties of the multicast object to create.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_OUT_OF_MEMORY,
 * ::CUDA_ERROR_INVALID_DEVICE,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_PERMITTED,
 * ::CUDA_ERROR_NOT_SUPPORTED
 *
 * \sa ::cuMulticastAddDevice, ::cuMulticastBindMem, ::cuMulticastBindAddr, ::cuMulticastUnbind
 * \sa ::cuMemCreate, ::cuMemRelease, ::cuMemExportToShareableHandle, ::cuMemImportFromShareableHandle
 */
CUresult CUDAAPI cuMulticastCreate(CUmemGenericAllocationHandle *mcHandle, const CUmulticastObjectProp *prop);

/**
 * \brief Associate a device to a multicast object.
 *
 * Associates a device to a multicast object. The added device will be a part of
 * the multicast team of size specified by CUmulticastObjectProp::numDevices
 * during ::cuMulticastCreate.
 * The association of the device to the multicast object is permanent during
 * the life time of the multicast object.
 * All devices must be added to the multicast team before any memory can be
 * bound to any device in the team. Any calls to ::cuMulticastBindMem or
 * ::cuMulticastBindAddr will block until all devices have been added.
 * Similarly all devices must be added to the multicast team before a virtual
 * address range can be mapped to the multicast object. A call to ::cuMemMap
 * will block until all devices have been added.
 *
 * \param[in] mcHandle     Handle representing a multicast object.
 * \param[in] dev          Device that will be associated to the multicast
 *                         object.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_OUT_OF_MEMORY,
 * ::CUDA_ERROR_INVALID_DEVICE,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_PERMITTED,
 * ::CUDA_ERROR_NOT_SUPPORTED
 *
 * \sa ::cuMulticastCreate, ::cuMulticastBindMem, ::cuMulticastBindAddr
 */
CUresult CUDAAPI cuMulticastAddDevice(CUmemGenericAllocationHandle mcHandle, CUdevice dev);

/**
 * \brief Bind a memory allocation represented by a handle to a multicast object.
 *
 * Binds a memory allocation specified by \p memHandle and created via
 * ::cuMemCreate to a multicast object represented by \p mcHandle and created
 * via ::cuMulticastCreate. The intended \p size of the bind, the offset in the
 * multicast range \p mcOffset as well as the offset in the memory \p memOffset
 * must be a multiple of the value returned by ::cuMulticastGetGranularity with
 * the flag ::CU_MULTICAST_GRANULARITY_MINIMUM. For best performance however,
 * \p size, \p mcOffset and \p memOffset should be aligned to the granularity of
 * the memory allocation(see ::cuMemGetAllocationGranularity) or to the value
 * returned by ::cuMulticastGetGranularity with the flag
 * ::CU_MULTICAST_GRANULARITY_RECOMMENDED.
 *
 * The \p size + \p memOffset cannot be larger than the size of the allocated
 * memory. Similarly the \p size + \p mcOffset cannot be larger than the size
 * of the multicast object.
 * The memory allocation must have beeen created on one of the devices
 * that was added to the multicast team via ::cuMulticastAddDevice.
 * Externally shareable as well as imported multicast objects can be bound only
 * to externally shareable memory.
 * Note that this call will return CUDA_ERROR_OUT_OF_MEMORY if there are
 * insufficient resources required to perform the bind. This call may also
 * return CUDA_ERROR_SYSTEM_NOT_READY if the necessary system software is not
 * initialized or running.
 *
 * \param[in]  mcHandle     Handle representing a multicast object.
 * \param[in]  mcOffset     Offset into the multicast object for attachment.
 * \param[in]  memHandle    Handle representing a memory allocation.
 * \param[in]  memOffset    Offset into the memory for attachment.
 * \param[in]  size         Size of the memory that will be bound to the
 *                          multicast object.
 * \param[in]  flags        Flags for future use, must be zero for now.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_DEVICE,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_PERMITTED,
 * ::CUDA_ERROR_NOT_SUPPORTED,
 * ::CUDA_ERROR_OUT_OF_MEMORY,
 * ::CUDA_ERROR_SYSTEM_NOT_READY
 *
 * \sa ::cuMulticastCreate, ::cuMulticastAddDevice, ::cuMemCreate
 */
CUresult CUDAAPI cuMulticastBindMem(CUmemGenericAllocationHandle mcHandle, size_t mcOffset, CUmemGenericAllocationHandle memHandle, size_t memOffset, size_t size, unsigned long long flags);

/**
 * \brief Bind a memory allocation represented by a virtual address to a multicast object.
 *
 * Binds a memory allocation specified by its mapped address \p memptr to a
 * multicast object represented by \p mcHandle.
 * The memory must have been allocated via ::cuMemCreate or ::cudaMallocAsync.
 * The intended \p size of the bind, the offset in the multicast range
 * \p mcOffset and \p memptr must be a multiple of the value returned by
 * ::cuMulticastGetGranularity with the flag ::CU_MULTICAST_GRANULARITY_MINIMUM.
 * For best performance however, \p size, \p mcOffset and \p memptr should be
 * aligned to the value returned by ::cuMulticastGetGranularity with the flag
 * ::CU_MULTICAST_GRANULARITY_RECOMMENDED.
 *
 * The \p size cannot be larger than the size of the allocated memory.
 * Similarly the \p size + \p mcOffset cannot be larger than the total size
 * of the multicast object.
 * The memory allocation must have beeen created on one of the devices
 * that was added to the multicast team via ::cuMulticastAddDevice.
 * Externally shareable as well as imported multicast objects can be bound only
 * to externally shareable memory.
 * Note that this call will return CUDA_ERROR_OUT_OF_MEMORY if there are
 * insufficient resources required to perform the bind. This call may also
 * return CUDA_ERROR_SYSTEM_NOT_READY if the necessary system software is not
 * initialized or running.
 *
 * \param[in]  mcHandle     Handle representing a multicast object.
 * \param[in]  mcOffset     Offset into multicast va range for attachment.
 * \param[in]  memptr       Virtual address of the memory allocation.
 * \param[in]  size         Size of memory that will be bound to the
 *                          multicast object.
 * \param[in]  flags        Flags for future use, must be zero now.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_DEVICE,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_PERMITTED,
 * ::CUDA_ERROR_NOT_SUPPORTED,
 * ::CUDA_ERROR_OUT_OF_MEMORY,
 * ::CUDA_ERROR_SYSTEM_NOT_READY
 *
 * \sa ::cuMulticastCreate, ::cuMulticastAddDevice, ::cuMemCreate
 */
CUresult CUDAAPI cuMulticastBindAddr(CUmemGenericAllocationHandle mcHandle, size_t mcOffset, CUdeviceptr memptr, size_t size, unsigned long long flags);

/**
 * \brief Unbind any memory allocations bound to a multicast object at a given offset and upto a given size.
 *
 * Unbinds any memory allocations hosted on \p dev and bound to a multicast
 * object at \p mcOffset and upto a given \p size.
 * The intended \p size of the unbind and the offset in the multicast range
 * ( \p mcOffset ) must be a multiple of the value returned by
 * ::cuMulticastGetGranularity flag ::CU_MULTICAST_GRANULARITY_MINIMUM.
 * The \p size + \p mcOffset cannot be larger than the total size of the
 * multicast object.
 *
 * \note 
 * Warning:
 * The \p mcOffset and the \p size must match the corresponding values specified
 * during the bind call. Any other values may result in undefined behavior.
 *
 * \param[in]  mcHandle     Handle representing a multicast object.
 * \param[in]  dev          Device that hosts the memory allocation.
 * \param[in]  mcOffset     Offset into the multicast object.
 * \param[in]  size         Desired size to unbind.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_DEVICE,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_PERMITTED,
 * ::CUDA_ERROR_NOT_SUPPORTED
 *
 * \sa ::cuMulticastBindMem, ::cuMulticastBindAddr
 */
CUresult CUDAAPI cuMulticastUnbind(CUmemGenericAllocationHandle mcHandle, CUdevice dev, size_t mcOffset, size_t size);

/**
* \brief Calculates either the minimal or recommended granularity for multicast object
*
* Calculates either the minimal or recommended granularity for a given set of
* multicast object properties and returns it in granularity.  This granularity
* can be used as a multiple for size, bind offsets and address mappings of the
* multicast object.
*
* \param[out] granularity Returned granularity.
* \param[in]  prop        Properties of the multicast object.
* \param[in]  option      Determines which granularity to return.
*
* \returns
* ::CUDA_SUCCESS,
* ::CUDA_ERROR_INVALID_VALUE,
* ::CUDA_ERROR_NOT_INITIALIZED,
* ::CUDA_ERROR_DEINITIALIZED,
* ::CUDA_ERROR_NOT_PERMITTED,
* ::CUDA_ERROR_NOT_SUPPORTED
*
* \sa ::cuMulticastCreate, ::cuMulticastBindMem, ::cuMulticastBindAddr, ::cuMulticastUnbind
*/
CUresult CUDAAPI cuMulticastGetGranularity(size_t *granularity, const CUmulticastObjectProp *prop, CUmulticastGranularity_flags option);

/** @} */ /* END CUDA_MULTICAST */

/**
 * \defgroup CUDA_UNIFIED Unified Addressing
 *
 * ___MANBRIEF___ unified addressing functions of the low-level CUDA driver
 * API (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the unified addressing functions of the
 * low-level CUDA driver application programming interface.
 *
 * @{
 *
 * \section CUDA_UNIFIED_overview Overview
 *
 * CUDA devices can share a unified address space with the host.
 * For these devices there is no distinction between a device
 * pointer and a host pointer -- the same pointer value may be
 * used to access memory from the host program and from a kernel
 * running on the device (with exceptions enumerated below).
 *
 * \section CUDA_UNIFIED_support Supported Platforms
 *
 * Whether or not a device supports unified addressing may be
 * queried by calling ::cuDeviceGetAttribute() with the device
 * attribute ::CU_DEVICE_ATTRIBUTE_UNIFIED_ADDRESSING.
 *
 * Unified addressing is automatically enabled in 64-bit processes
 *
 * \section CUDA_UNIFIED_lookup Looking Up Information from Pointer Values
 *
 * It is possible to look up information about the memory which backs a
 * pointer value.  For instance, one may want to know if a pointer points
 * to host or device memory.  As another example, in the case of device
 * memory, one may want to know on which CUDA device the memory
 * resides.  These properties may be queried using the function
 * ::cuPointerGetAttribute()
 *
 * Since pointers are unique, it is not necessary to specify information
 * about the pointers specified to the various copy functions in the
 * CUDA API.  The function ::cuMemcpy() may be used to perform a copy
 * between two pointers, ignoring whether they point to host or device
 * memory (making ::cuMemcpyHtoD(), ::cuMemcpyDtoD(), and ::cuMemcpyDtoH()
 * unnecessary for devices supporting unified addressing).  For
 * multidimensional copies, the memory type ::CU_MEMORYTYPE_UNIFIED may be
 * used to specify that the CUDA driver should infer the location of the
 * pointer from its value.
 *
 * \section CUDA_UNIFIED_automaphost Automatic Mapping of Host Allocated Host Memory
 *
 * All host memory allocated in all contexts using ::cuMemAllocHost() and
 * ::cuMemHostAlloc() is always directly accessible from all contexts on
 * all devices that support unified addressing.  This is the case regardless
 * of whether or not the flags ::CU_MEMHOSTALLOC_PORTABLE and
 * ::CU_MEMHOSTALLOC_DEVICEMAP are specified.
 *
 * The pointer value through which allocated host memory may be accessed
 * in kernels on all devices that support unified addressing is the same
 * as the pointer value through which that memory is accessed on the host,
 * so it is not necessary to call ::cuMemHostGetDevicePointer() to get the device
 * pointer for these allocations.
 *
 * Note that this is not the case for memory allocated using the flag
 * ::CU_MEMHOSTALLOC_WRITECOMBINED, as discussed below.
 *
 * \section CUDA_UNIFIED_autopeerregister Automatic Registration of Peer Memory
 *
 * Upon enabling direct access from a context that supports unified addressing
 * to another peer context that supports unified addressing using
 * ::cuCtxEnablePeerAccess() all memory allocated in the peer context using
 * ::cuMemAlloc() and ::cuMemAllocPitch() will immediately be accessible
 * by the current context.  The device pointer value through
 * which any peer memory may be accessed in the current context
 * is the same pointer value through which that memory may be
 * accessed in the peer context.
 *
 * \section CUDA_UNIFIED_exceptions Exceptions, Disjoint Addressing
 *
 * Not all memory may be accessed on devices through the same pointer
 * value through which they are accessed on the host.  These exceptions
 * are host memory registered using ::cuMemHostRegister() and host memory
 * allocated using the flag ::CU_MEMHOSTALLOC_WRITECOMBINED.  For these
 * exceptions, there exists a distinct host and device address for the
 * memory.  The device address is guaranteed to not overlap any valid host
 * pointer range and is guaranteed to have the same value across all
 * contexts that support unified addressing.
 *
 * This device address may be queried using ::cuMemHostGetDevicePointer()
 * when a context using unified addressing is current.  Either the host
 * or the unified device pointer value may be used to refer to this memory
 * through ::cuMemcpy() and similar functions using the
 * ::CU_MEMORYTYPE_UNIFIED memory type.
 *
 */

/**
 * \brief Returns information about a pointer
 *
 * The supported attributes are:
 *
 * - ::CU_POINTER_ATTRIBUTE_CONTEXT:
 *
 *      Returns in \p *data the ::CUcontext in which \p ptr was allocated or
 *      registered.
 *      The type of \p data must be ::CUcontext *.
 *
 *      If \p ptr was not allocated by, mapped by, or registered with
 *      a ::CUcontext which uses unified virtual addressing then
 *      ::CUDA_ERROR_INVALID_VALUE is returned.
 *
 * - ::CU_POINTER_ATTRIBUTE_MEMORY_TYPE:
 *
 *      Returns in \p *data the physical memory type of the memory that
 *      \p ptr addresses as a ::CUmemorytype enumerated value.
 *      The type of \p data must be unsigned int.
 *
 *      If \p ptr addresses device memory then \p *data is set to
 *      ::CU_MEMORYTYPE_DEVICE.  The particular ::CUdevice on which the
 *      memory resides is the ::CUdevice of the ::CUcontext returned by the
 *      ::CU_POINTER_ATTRIBUTE_CONTEXT attribute of \p ptr.
 *
 *      If \p ptr addresses host memory then \p *data is set to
 *      ::CU_MEMORYTYPE_HOST.
 *
 *      If \p ptr was not allocated by, mapped by, or registered with
 *      a ::CUcontext which uses unified virtual addressing then
 *      ::CUDA_ERROR_INVALID_VALUE is returned.
 *
 *      If the current ::CUcontext does not support unified virtual
 *      addressing then ::CUDA_ERROR_INVALID_CONTEXT is returned.
 *
 * - ::CU_POINTER_ATTRIBUTE_DEVICE_POINTER:
 *
 *      Returns in \p *data the device pointer value through which
 *      \p ptr may be accessed by kernels running in the current
 *      ::CUcontext.
 *      The type of \p data must be CUdeviceptr *.
 *
 *      If there exists no device pointer value through which
 *      kernels running in the current ::CUcontext may access
 *      \p ptr then ::CUDA_ERROR_INVALID_VALUE is returned.
 *
 *      If there is no current ::CUcontext then
 *      ::CUDA_ERROR_INVALID_CONTEXT is returned.
 *
 *      Except in the exceptional disjoint addressing cases discussed
 *      below, the value returned in \p *data will equal the input
 *      value \p ptr.
 *
 * - ::CU_POINTER_ATTRIBUTE_HOST_POINTER:
 *
 *      Returns in \p *data the host pointer value through which
 *      \p ptr may be accessed by by the host program.
 *      The type of \p data must be void **.
 *      If there exists no host pointer value through which
 *      the host program may directly access \p ptr then
 *      ::CUDA_ERROR_INVALID_VALUE is returned.
 *
 *      Except in the exceptional disjoint addressing cases discussed
 *      below, the value returned in \p *data will equal the input
 *      value \p ptr.
 *
 * - ::CU_POINTER_ATTRIBUTE_P2P_TOKENS:
 *
 *      Returns in \p *data two tokens for use with the nv-p2p.h Linux
 *      kernel interface. \p data must be a struct of type
 *      CUDA_POINTER_ATTRIBUTE_P2P_TOKENS.
 *
 *      \p ptr must be a pointer to memory obtained from :cuMemAlloc().
 *      Note that p2pToken and vaSpaceToken are only valid for the
 *      lifetime of the source allocation. A subsequent allocation at
 *      the same address may return completely different tokens.
 *      Querying this attribute has a side effect of setting the attribute
 *      ::CU_POINTER_ATTRIBUTE_SYNC_MEMOPS for the region of memory that
 *      \p ptr points to.
 *
 * - ::CU_POINTER_ATTRIBUTE_SYNC_MEMOPS:
 *
 *      A boolean attribute which when set, ensures that synchronous memory operations
 *      initiated on the region of memory that \p ptr points to will always synchronize.
 *      See further documentation in the section titled "API synchronization behavior"
 *      to learn more about cases when synchronous memory operations can
 *      exhibit asynchronous behavior.
 *
 * - ::CU_POINTER_ATTRIBUTE_BUFFER_ID:
 *
 *      Returns in \p *data a buffer ID which is guaranteed to be unique within the process.
 *      \p data must point to an unsigned long long.
 *
 *      \p ptr must be a pointer to memory obtained from a CUDA memory allocation API.
 *      Every memory allocation from any of the CUDA memory allocation APIs will
 *      have a unique ID over a process lifetime. Subsequent allocations do not reuse IDs
 *      from previous freed allocations. IDs are only unique within a single process.
 *
 *
 * - ::CU_POINTER_ATTRIBUTE_IS_MANAGED:
 *
 *      Returns in \p *data a boolean that indicates whether the pointer points to
 *      managed memory or not.
 *
 *      If \p ptr is not a valid CUDA pointer then ::CUDA_ERROR_INVALID_VALUE is returned.
 *
 * - ::CU_POINTER_ATTRIBUTE_DEVICE_ORDINAL:
 *
 *      Returns in \p *data an integer representing a device ordinal of a device against
 *      which the memory was allocated or registered.
 *
 * - ::CU_POINTER_ATTRIBUTE_IS_LEGACY_CUDA_IPC_CAPABLE:
 *
 *      Returns in \p *data a boolean that indicates if this pointer maps to
 *      an allocation that is suitable for ::cudaIpcGetMemHandle.
 *
 * - ::CU_POINTER_ATTRIBUTE_RANGE_START_ADDR:
 *
 *      Returns in \p *data the starting address for the allocation referenced
 *      by the device pointer \p ptr.  Note that this is not necessarily the
 *      address of the mapped region, but the address of the mappable address
 *      range \p ptr references (e.g. from ::cuMemAddressReserve).
 *
 * - ::CU_POINTER_ATTRIBUTE_RANGE_SIZE:
 *
 *      Returns in \p *data the size for the allocation referenced by the device
 *      pointer \p ptr.  Note that this is not necessarily the size of the mapped
 *      region, but the size of the mappable address range \p ptr references
 *      (e.g. from ::cuMemAddressReserve).  To retrieve the size of the mapped
 *      region, see ::cuMemGetAddressRange
 *
 * - ::CU_POINTER_ATTRIBUTE_MAPPED:
 *
 *      Returns in \p *data a boolean that indicates if this pointer is in a
 *      valid address range that is mapped to a backing allocation.
 *
 * - ::CU_POINTER_ATTRIBUTE_ALLOWED_HANDLE_TYPES:
 *
 *      Returns a bitmask of the allowed handle types for an allocation that may
 *      be passed to ::cuMemExportToShareableHandle.
 * 
 * - ::CU_POINTER_ATTRIBUTE_MEMPOOL_HANDLE:
 * 
 *      Returns in \p *data the handle to the mempool that the allocation was obtained from.
 *
 * - ::CU_POINTER_ATTRIBUTE_IS_HW_DECOMPRESS_CAPABLE:
 *
 *      Returns in \p *data a boolean that indicates whether the pointer points
 *      to memory that is capable to be used for hardware accelerated
 *      decompression.
 *
 * \par
 *
 * Note that for most allocations in the unified virtual address space
 * the host and device pointer for accessing the allocation will be the
 * same.  The exceptions to this are
 *  - user memory registered using ::cuMemHostRegister
 *  - host memory allocated using ::cuMemHostAlloc with the
 *    ::CU_MEMHOSTALLOC_WRITECOMBINED flag
 * For these types of allocation there will exist separate, disjoint host
 * and device addresses for accessing the allocation.  In particular
 *  - The host address will correspond to an invalid unmapped device address
 *    (which will result in an exception if accessed from the device)
 *  - The device address will correspond to an invalid unmapped host address
 *    (which will result in an exception if accessed from the host).
 * For these types of allocations, querying ::CU_POINTER_ATTRIBUTE_HOST_POINTER
 * and ::CU_POINTER_ATTRIBUTE_DEVICE_POINTER may be used to retrieve the host
 * and device addresses from either address.
 *
 * \param data      - Returned pointer attribute value
 * \param attribute - Pointer attribute to query
 * \param ptr       - Pointer
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_DEVICE
 * \notefnerr
 *
 * \sa
 * ::cuPointerSetAttribute,
 * ::cuMemAlloc,
 * ::cuMemFree,
 * ::cuMemAllocHost,
 * ::cuMemFreeHost,
 * ::cuMemHostAlloc,
 * ::cuMemHostRegister,
 * ::cuMemHostUnregister,
 * ::cudaPointerGetAttributes
 */
CUresult CUDAAPI cuPointerGetAttribute(void *data, CUpointer_attribute attribute, CUdeviceptr ptr);

/**
 * \brief Prefetches memory to the specified destination device
 * 
 * Note there is a later version of this API, ::cuMemPrefetchAsync_v2. It will
 * supplant this version in 13.0, which is retained for minor version compatibility.
 *
 * Prefetches memory to the specified destination device.  \p devPtr is the
 * base device pointer of the memory to be prefetched and \p dstDevice is the
 * destination device. \p count specifies the number of bytes to copy. \p hStream
 * is the stream in which the operation is enqueued. The memory range must refer
 * to managed memory allocated via ::cuMemAllocManaged or declared via __managed__ variables
 * or it may also refer to system-allocated memory on systems with non-zero 
 * CU_DEVICE_ATTRIBUTE_PAGEABLE_MEMORY_ACCESS.
 *
 * Passing in CU_DEVICE_CPU for \p dstDevice will prefetch the data to host memory. If
 * \p dstDevice is a GPU, then the device attribute ::CU_DEVICE_ATTRIBUTE_CONCURRENT_MANAGED_ACCESS
 * must be non-zero. Additionally, \p hStream must be associated with a device that has a
 * non-zero value for the device attribute ::CU_DEVICE_ATTRIBUTE_CONCURRENT_MANAGED_ACCESS.
 *
 * The start address and end address of the memory range will be rounded down and rounded up
 * respectively to be aligned to CPU page size before the prefetch operation is enqueued
 * in the stream.
 *
 * If no physical memory has been allocated for this region, then this memory region
 * will be populated and mapped on the destination device. If there's insufficient
 * memory to prefetch the desired region, the Unified Memory driver may evict pages from other
 * ::cuMemAllocManaged allocations to host memory in order to make room. Device memory
 * allocated using ::cuMemAlloc or ::cuArrayCreate will not be evicted.
 *
 * By default, any mappings to the previous location of the migrated pages are removed and
 * mappings for the new location are only setup on \p dstDevice. The exact behavior however
 * also depends on the settings applied to this memory range via ::cuMemAdvise as described
 * below:
 *
 * If ::CU_MEM_ADVISE_SET_READ_MOSTLY was set on any subset of this memory range,
 * then that subset will create a read-only copy of the pages on \p dstDevice.
 *
 * If ::CU_MEM_ADVISE_SET_PREFERRED_LOCATION was called on any subset of this memory
 * range, then the pages will be migrated to \p dstDevice even if \p dstDevice is not the
 * preferred location of any pages in the memory range.
 *
 * If ::CU_MEM_ADVISE_SET_ACCESSED_BY was called on any subset of this memory range,
 * then mappings to those pages from all the appropriate processors are updated to
 * refer to the new location if establishing such a mapping is possible. Otherwise,
 * those mappings are cleared.
 *
 * Note that this API is not required for functionality and only serves to improve performance
 * by allowing the application to migrate data to a suitable location before it is accessed.
 * Memory accesses to this range are always coherent and are allowed even when the data is
 * actively being migrated.
 *
 * Note that this function is asynchronous with respect to the host and all work
 * on other devices.
 *
 * \param devPtr    - Pointer to be prefetched
 * \param count     - Size in bytes
 * \param dstDevice - Destination device to prefetch to
 * \param hStream    - Stream to enqueue prefetch operation
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_DEVICE
 * \notefnerr
 * \note_async
 * \note_null_stream
 *
 * \sa ::cuMemcpy, ::cuMemcpyPeer, ::cuMemcpyAsync,
 * ::cuMemcpy3DPeerAsync, ::cuMemAdvise, ::cuMemPrefetchAsync
 * ::cudaMemPrefetchAsync_v2
 */
CUresult CUDAAPI cuMemPrefetchAsync(CUdeviceptr devPtr, size_t count, CUdevice dstDevice, CUstream hStream);

/**
 * \brief Prefetches memory to the specified destination location
 *
 * Prefetches memory to the specified destination location.  \p devPtr is the
 * base device pointer of the memory to be prefetched and \p location specifies the
 * destination location. \p count specifies the number of bytes to copy. \p hStream
 * is the stream in which the operation is enqueued. The memory range must refer
 * to managed memory allocated via ::cuMemAllocManaged or declared via __managed__ variables.
 *
 * Specifying ::CU_MEM_LOCATION_TYPE_DEVICE for ::CUmemLocation::type will prefetch memory to GPU
 * specified by device ordinal ::CUmemLocation::id which must have non-zero value for the device attribute
 * ::CU_DEVICE_ATTRIBUTE_CONCURRENT_MANAGED_ACCESS. Additionally, \p hStream must be associated with a device
 * that has a non-zero value for the device attribute ::CU_DEVICE_ATTRIBUTE_CONCURRENT_MANAGED_ACCESS.
 * Specifying ::CU_MEM_LOCATION_TYPE_HOST as ::CUmemLocation::type will prefetch data to host memory.
 * Applications can request prefetching memory to a specific host NUMA node by specifying
 * ::CU_MEM_LOCATION_TYPE_HOST_NUMA for ::CUmemLocation::type and a valid host NUMA node id in ::CUmemLocation::id
 * Users can also request prefetching memory to the host NUMA node closest to the current thread's CPU by specifying
 * ::CU_MEM_LOCATION_TYPE_HOST_NUMA_CURRENT for ::CUmemLocation::type. Note when ::CUmemLocation::type is etiher
 * ::CU_MEM_LOCATION_TYPE_HOST OR ::CU_MEM_LOCATION_TYPE_HOST_NUMA_CURRENT, ::CUmemLocation::id will be ignored.
 *
 * The start address and end address of the memory range will be rounded down and rounded up
 * respectively to be aligned to CPU page size before the prefetch operation is enqueued
 * in the stream.
 *
 * If no physical memory has been allocated for this region, then this memory region
 * will be populated and mapped on the destination device. If there's insufficient
 * memory to prefetch the desired region, the Unified Memory driver may evict pages from other
 * ::cuMemAllocManaged allocations to host memory in order to make room. Device memory
 * allocated using ::cuMemAlloc or ::cuArrayCreate will not be evicted.
 *
 * By default, any mappings to the previous location of the migrated pages are removed and
 * mappings for the new location are only setup on the destination location. The exact behavior however
 * also depends on the settings applied to this memory range via ::cuMemAdvise as described
 * below:
 *
 * If ::CU_MEM_ADVISE_SET_READ_MOSTLY was set on any subset of this memory range,
 * then that subset will create a read-only copy of the pages on destination location.
 * If however the destination location is a host NUMA node, then any pages of that subset
 * that are already in another host NUMA node will be transferred to the destination.
 *
 * If ::CU_MEM_ADVISE_SET_PREFERRED_LOCATION was called on any subset of this memory
 * range, then the pages will be migrated to \p location even if \p location is not the
 * preferred location of any pages in the memory range.
 *
 * If ::CU_MEM_ADVISE_SET_ACCESSED_BY was called on any subset of this memory range,
 * then mappings to those pages from all the appropriate processors are updated to
 * refer to the new location if establishing such a mapping is possible. Otherwise,
 * those mappings are cleared.
 *
 * Note that this API is not required for functionality and only serves to improve performance
 * by allowing the application to migrate data to a suitable location before it is accessed.
 * Memory accesses to this range are always coherent and are allowed even when the data is
 * actively being migrated.
 *
 * Note that this function is asynchronous with respect to the host and all work
 * on other devices.
 *
 * \param devPtr    - Pointer to be prefetched
 * \param count     - Size in bytes
 * \param dstDevice - Destination device to prefetch to
 * \param flags     - flags for future use, must be zero now. 
 * \param hStream   - Stream to enqueue prefetch operation
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_DEVICE
 * \notefnerr
 * \note_async
 * \note_null_stream
 *
 * \sa ::cuMemcpy, ::cuMemcpyPeer, ::cuMemcpyAsync,
 * ::cuMemcpy3DPeerAsync, ::cuMemAdvise, ::cuMemPrefetchAsync
 * ::cudaMemPrefetchAsync_v2
 */
CUresult CUDAAPI cuMemPrefetchAsync_v2(CUdeviceptr devPtr, size_t count, CUmemLocation location, unsigned int flags, CUstream hStream);

/**
 * \brief Advise about the usage of a given memory range
 *
 * Note there is a later version of this API, ::cuMemAdvise_v2. It will
 * supplant this version in 13.0, which is retained for minor version compatibility.
 * 
 * Advise the Unified Memory subsystem about the usage pattern for the memory range
 * starting at \p devPtr with a size of \p count bytes. The start address and end address of the memory
 * range will be rounded down and rounded up respectively to be aligned to CPU page size before the
 * advice is applied. The memory range must refer to managed memory allocated via ::cuMemAllocManaged
 * or declared via __managed__ variables. The memory range could also refer to system-allocated pageable
 * memory provided it represents a valid, host-accessible region of memory and all additional constraints
 * imposed by \p advice as outlined below are also satisfied. Specifying an invalid system-allocated pageable
 * memory range results in an error being returned.
 *
 * The \p advice parameter can take the following values:
 * - ::CU_MEM_ADVISE_SET_READ_MOSTLY: This implies that the data is mostly going to be read
 * from and only occasionally written to. Any read accesses from any processor to this region will create a
 * read-only copy of at least the accessed pages in that processor's memory. Additionally, if ::cuMemPrefetchAsync
 * is called on this region, it will create a read-only copy of the data on the destination processor.
 * If any processor writes to this region, all copies of the corresponding page will be invalidated
 * except for the one where the write occurred. The \p device argument is ignored for this advice.
 * Note that for a page to be read-duplicated, the accessing processor must either be the CPU or a GPU
 * that has a non-zero value for the device attribute ::CU_DEVICE_ATTRIBUTE_CONCURRENT_MANAGED_ACCESS.
 * Also, if a context is created on a device that does not have the device attribute
 * ::CU_DEVICE_ATTRIBUTE_CONCURRENT_MANAGED_ACCESS set, then read-duplication will not occur until
 * all such contexts are destroyed.
 * If the memory region refers to valid system-allocated pageable memory, then the accessing device must
 * have a non-zero value for the device attribute ::CU_DEVICE_ATTRIBUTE_PAGEABLE_MEMORY_ACCESS for a read-only
 * copy to be created on that device. Note however that if the accessing device also has a non-zero value for the
 * device attribute ::CU_DEVICE_ATTRIBUTE_PAGEABLE_MEMORY_ACCESS_USES_HOST_PAGE_TABLES, then setting this advice
 * will not create a read-only copy when that device accesses this memory region.
 *
 * - ::CU_MEM_ADVISE_UNSET_READ_MOSTLY:  Undoes the effect of ::CU_MEM_ADVISE_SET_READ_MOSTLY and also prevents the
 * Unified Memory driver from attempting heuristic read-duplication on the memory range. Any read-duplicated
 * copies of the data will be collapsed into a single copy. The location for the collapsed
 * copy will be the preferred location if the page has a preferred location and one of the read-duplicated
 * copies was resident at that location. Otherwise, the location chosen is arbitrary.
 *
 * - ::CU_MEM_ADVISE_SET_PREFERRED_LOCATION: This advice sets the preferred location for the
 * data to be the memory belonging to \p device. Passing in CU_DEVICE_CPU for \p device sets the
 * preferred location as host memory. If \p device is a GPU, then it must have a non-zero value for the
 * device attribute ::CU_DEVICE_ATTRIBUTE_CONCURRENT_MANAGED_ACCESS. Setting the preferred location
 * does not cause data to migrate to that location immediately. Instead, it guides the migration policy
 * when a fault occurs on that memory region. If the data is already in its preferred location and the
 * faulting processor can establish a mapping without requiring the data to be migrated, then
 * data migration will be avoided. On the other hand, if the data is not in its preferred location
 * or if a direct mapping cannot be established, then it will be migrated to the processor accessing
 * it. It is important to note that setting the preferred location does not prevent data prefetching
 * done using ::cuMemPrefetchAsync.
 * Having a preferred location can override the page thrash detection and resolution logic in the Unified
 * Memory driver. Normally, if a page is detected to be constantly thrashing between for example host and device
 * memory, the page may eventually be pinned to host memory by the Unified Memory driver. But
 * if the preferred location is set as device memory, then the page will continue to thrash indefinitely.
 * If ::CU_MEM_ADVISE_SET_READ_MOSTLY is also set on this memory region or any subset of it, then the
 * policies associated with that advice will override the policies of this advice, unless read accesses from
 * \p device will not result in a read-only copy being created on that device as outlined in description for
 * the advice ::CU_MEM_ADVISE_SET_READ_MOSTLY.
 * If the memory region refers to valid system-allocated pageable memory, then \p device must have a non-zero
 * value for the device attribute ::CU_DEVICE_ATTRIBUTE_PAGEABLE_MEMORY_ACCESS.
 *
 * - ::CU_MEM_ADVISE_UNSET_PREFERRED_LOCATION: Undoes the effect of ::CU_MEM_ADVISE_SET_PREFERRED_LOCATION
 * and changes the preferred location to none.
 *
 * - ::CU_MEM_ADVISE_SET_ACCESSED_BY: This advice implies that the data will be accessed by \p device.
 * Passing in ::CU_DEVICE_CPU for \p device will set the advice for the CPU. If \p device is a GPU, then
 * the device attribute ::CU_DEVICE_ATTRIBUTE_CONCURRENT_MANAGED_ACCESS must be non-zero.
 * This advice does not cause data migration and has no impact on the location of the data per se. Instead,
 * it causes the data to always be mapped in the specified processor's page tables, as long as the
 * location of the data permits a mapping to be established. If the data gets migrated for any reason,
 * the mappings are updated accordingly.
 * This advice is recommended in scenarios where data locality is not important, but avoiding faults is.
 * Consider for example a system containing multiple GPUs with peer-to-peer access enabled, where the
 * data located on one GPU is occasionally accessed by peer GPUs. In such scenarios, migrating data
 * over to the other GPUs is not as important because the accesses are infrequent and the overhead of
 * migration may be too high. But preventing faults can still help improve performance, and so having
 * a mapping set up in advance is useful. Note that on CPU access of this data, the data may be migrated
 * to host memory because the CPU typically cannot access device memory directly. Any GPU that had the
 * ::CU_MEM_ADVISE_SET_ACCESSED_BY flag set for this data will now have its mapping updated to point to the
 * page in host memory.
 * If ::CU_MEM_ADVISE_SET_READ_MOSTLY is also set on this memory region or any subset of it, then the
 * policies associated with that advice will override the policies of this advice. Additionally, if the
 * preferred location of this memory region or any subset of it is also \p device, then the policies
 * associated with ::CU_MEM_ADVISE_SET_PREFERRED_LOCATION will override the policies of this advice.
 * If the memory region refers to valid system-allocated pageable memory, then \p device must have a non-zero
 * value for the device attribute ::CU_DEVICE_ATTRIBUTE_PAGEABLE_MEMORY_ACCESS. Additionally, if \p device has
 * a non-zero value for the device attribute ::CU_DEVICE_ATTRIBUTE_PAGEABLE_MEMORY_ACCESS_USES_HOST_PAGE_TABLES,
 * then this call has no effect.
 *
 * - ::CU_MEM_ADVISE_UNSET_ACCESSED_BY: Undoes the effect of ::CU_MEM_ADVISE_SET_ACCESSED_BY. Any mappings to
 * the data from \p device may be removed at any time causing accesses to result in non-fatal page faults.
 * If the memory region refers to valid system-allocated pageable memory, then \p device must have a non-zero
 * value for the device attribute ::CU_DEVICE_ATTRIBUTE_PAGEABLE_MEMORY_ACCESS. Additionally, if \p device has
 * a non-zero value for the device attribute ::CU_DEVICE_ATTRIBUTE_PAGEABLE_MEMORY_ACCESS_USES_HOST_PAGE_TABLES,
 * then this call has no effect.
 *
 * \param devPtr - Pointer to memory to set the advice for
 * \param count  - Size in bytes of the memory range
 * \param advice - Advice to be applied for the specified memory range
 * \param device - Device to apply the advice for
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_DEVICE
 * \notefnerr
 * \note_async
 * \note_null_stream
 *
 * \sa ::cuMemcpy, ::cuMemcpyPeer, ::cuMemcpyAsync,
 * ::cuMemcpy3DPeerAsync, ::cuMemPrefetchAsync, ::cuMemAdvise_v2
 * ::cudaMemAdvise
 */
CUresult CUDAAPI cuMemAdvise(CUdeviceptr devPtr, size_t count, CUmem_advise advice, CUdevice device);

/**
 * \brief Advise about the usage of a given memory range
 *
 * Advise the Unified Memory subsystem about the usage pattern for the memory range
 * starting at \p devPtr with a size of \p count bytes. The start address and end address of the memory
 * range will be rounded down and rounded up respectively to be aligned to CPU page size before the
 * advice is applied. The memory range must refer to managed memory allocated via ::cuMemAllocManaged
 * or declared via __managed__ variables. The memory range could also refer to system-allocated pageable
 * memory provided it represents a valid, host-accessible region of memory and all additional constraints
 * imposed by \p advice as outlined below are also satisfied. Specifying an invalid system-allocated pageable
 * memory range results in an error being returned.
 *
 * The \p advice parameter can take the following values:
 * - ::CU_MEM_ADVISE_SET_READ_MOSTLY: This implies that the data is mostly going to be read
 * from and only occasionally written to. Any read accesses from any processor to this region will create a
 * read-only copy of at least the accessed pages in that processor's memory. Additionally, if ::cuMemPrefetchAsync
 * or ::cuMemPrefetchAsync_v2 is called on this region, it will create a read-only copy of the data on the destination processor.
 * If the target location for ::cuMemPrefetchAsync_v2 is a host NUMA node and a read-only copy already exists on
 * another host NUMA node, that copy will be migrated to the targeted host NUMA node.
 * If any processor writes to this region, all copies of the corresponding page will be invalidated
 * except for the one where the write occurred. If the writing processor is the CPU and the preferred location of
 * the page is a host NUMA node, then the page will also be migrated to that host NUMA node. The \p location argument is ignored for this advice.
 * Note that for a page to be read-duplicated, the accessing processor must either be the CPU or a GPU
 * that has a non-zero value for the device attribute ::CU_DEVICE_ATTRIBUTE_CONCURRENT_MANAGED_ACCESS.
 * Also, if a context is created on a device that does not have the device attribute
 * ::CU_DEVICE_ATTRIBUTE_CONCURRENT_MANAGED_ACCESS set, then read-duplication will not occur until
 * all such contexts are destroyed.
 * If the memory region refers to valid system-allocated pageable memory, then the accessing device must
 * have a non-zero value for the device attribute ::CU_DEVICE_ATTRIBUTE_PAGEABLE_MEMORY_ACCESS for a read-only
 * copy to be created on that device. Note however that if the accessing device also has a non-zero value for the
 * device attribute ::CU_DEVICE_ATTRIBUTE_PAGEABLE_MEMORY_ACCESS_USES_HOST_PAGE_TABLES, then setting this advice
 * will not create a read-only copy when that device accesses this memory region.
 *
 * - ::CU_MEM_ADVISE_UNSET_READ_MOSTLY:  Undoes the effect of ::CU_MEM_ADVISE_SET_READ_MOSTLY and also prevents the
 * Unified Memory driver from attempting heuristic read-duplication on the memory range. Any read-duplicated
 * copies of the data will be collapsed into a single copy. The location for the collapsed
 * copy will be the preferred location if the page has a preferred location and one of the read-duplicated
 * copies was resident at that location. Otherwise, the location chosen is arbitrary.
 * Note: The \p location argument is ignored for this advice.
 *
 * - ::CU_MEM_ADVISE_SET_PREFERRED_LOCATION: This advice sets the preferred location for the
 * data to be the memory belonging to \p location. When ::CUmemLocation::type is ::CU_MEM_LOCATION_TYPE_HOST,
 * ::CUmemLocation::id is ignored and the preferred location is set to be host memory. To set the preferred location
 * to a specific host NUMA node, applications must set ::CUmemLocation::type to ::CU_MEM_LOCATION_TYPE_HOST_NUMA and
 * ::CUmemLocation::id must specify the NUMA ID of the host NUMA node. If ::CUmemLocation::type is set to ::CU_MEM_LOCATION_TYPE_HOST_NUMA_CURRENT,
 * ::CUmemLocation::id will be ignored and the the host NUMA node closest to the calling thread's CPU will be used as the preferred location.
 * If ::CUmemLocation::type is a ::CU_MEM_LOCATION_TYPE_DEVICE, then ::CUmemLocation::id must be a valid device ordinal
 * and the device must have a non-zero value for the device attribute ::CU_DEVICE_ATTRIBUTE_CONCURRENT_MANAGED_ACCESS.
 * Setting the preferred location does not cause data to migrate to that location immediately. Instead, it guides the migration policy
 * when a fault occurs on that memory region. If the data is already in its preferred location and the
 * faulting processor can establish a mapping without requiring the data to be migrated, then
 * data migration will be avoided. On the other hand, if the data is not in its preferred location
 * or if a direct mapping cannot be established, then it will be migrated to the processor accessing
 * it. It is important to note that setting the preferred location does not prevent data prefetching
 * done using ::cuMemPrefetchAsync.
 * Having a preferred location can override the page thrash detection and resolution logic in the Unified
 * Memory driver. Normally, if a page is detected to be constantly thrashing between for example host and device
 * memory, the page may eventually be pinned to host memory by the Unified Memory driver. But
 * if the preferred location is set as device memory, then the page will continue to thrash indefinitely.
 * If ::CU_MEM_ADVISE_SET_READ_MOSTLY is also set on this memory region or any subset of it, then the
 * policies associated with that advice will override the policies of this advice, unless read accesses from
 * \p location will not result in a read-only copy being created on that procesor as outlined in description for
 * the advice ::CU_MEM_ADVISE_SET_READ_MOSTLY.
 * If the memory region refers to valid system-allocated pageable memory, and ::CUmemLocation::type is CU_MEM_LOCATION_TYPE_DEVICE
 * then ::CUmemLocation::id must be a valid device that has a non-zero alue for the device attribute ::CU_DEVICE_ATTRIBUTE_PAGEABLE_MEMORY_ACCESS.
 *
 * - ::CU_MEM_ADVISE_UNSET_PREFERRED_LOCATION: Undoes the effect of ::CU_MEM_ADVISE_SET_PREFERRED_LOCATION
 * and changes the preferred location to none. The \p location argument is ignored for this advice.
 *
 * - ::CU_MEM_ADVISE_SET_ACCESSED_BY: This advice implies that the data will be accessed by processor \p location.
 * The ::CUmemLocation::type must be either ::CU_MEM_LOCATION_TYPE_DEVICE with ::CUmemLocation::id representing a valid device
 * ordinal or ::CU_MEM_LOCATION_TYPE_HOST and ::CUmemLocation::id will be ignored. All other location types are invalid.
 * If ::CUmemLocation::id is a GPU, then the device attribute ::CU_DEVICE_ATTRIBUTE_CONCURRENT_MANAGED_ACCESS must be non-zero.
 * This advice does not cause data migration and has no impact on the location of the data per se. Instead,
 * it causes the data to always be mapped in the specified processor's page tables, as long as the
 * location of the data permits a mapping to be established. If the data gets migrated for any reason,
 * the mappings are updated accordingly.
 * This advice is recommended in scenarios where data locality is not important, but avoiding faults is.
 * Consider for example a system containing multiple GPUs with peer-to-peer access enabled, where the
 * data located on one GPU is occasionally accessed by peer GPUs. In such scenarios, migrating data
 * over to the other GPUs is not as important because the accesses are infrequent and the overhead of
 * migration may be too high. But preventing faults can still help improve performance, and so having
 * a mapping set up in advance is useful. Note that on CPU access of this data, the data may be migrated
 * to host memory because the CPU typically cannot access device memory directly. Any GPU that had the
 * ::CU_MEM_ADVISE_SET_ACCESSED_BY flag set for this data will now have its mapping updated to point to the
 * page in host memory.
 * If ::CU_MEM_ADVISE_SET_READ_MOSTLY is also set on this memory region or any subset of it, then the
 * policies associated with that advice will override the policies of this advice. Additionally, if the
 * preferred location of this memory region or any subset of it is also \p location, then the policies
 * associated with ::CU_MEM_ADVISE_SET_PREFERRED_LOCATION will override the policies of this advice.
 * If the memory region refers to valid system-allocated pageable memory, and ::CUmemLocation::type is ::CU_MEM_LOCATION_TYPE_DEVICE
 * then device in ::CUmemLocation::id must have a non-zero value for the device attribute ::CU_DEVICE_ATTRIBUTE_PAGEABLE_MEMORY_ACCESS.
 * Additionally, if ::CUmemLocation::id has a non-zero value for the device attribute ::CU_DEVICE_ATTRIBUTE_PAGEABLE_MEMORY_ACCESS_USES_HOST_PAGE_TABLES,
 * then this call has no effect.
 *
 * - ::CU_MEM_ADVISE_UNSET_ACCESSED_BY: Undoes the effect of ::CU_MEM_ADVISE_SET_ACCESSED_BY. Any mappings to
 * the data from \p location may be removed at any time causing accesses to result in non-fatal page faults.
 * If the memory region refers to valid system-allocated pageable memory, and ::CUmemLocation::type is ::CU_MEM_LOCATION_TYPE_DEVICE
 * then device in ::CUmemLocation::id must have a non-zero value for the device attribute ::CU_DEVICE_ATTRIBUTE_PAGEABLE_MEMORY_ACCESS.
 * Additionally, if ::CUmemLocation::id has a non-zero value for the device attribute ::CU_DEVICE_ATTRIBUTE_PAGEABLE_MEMORY_ACCESS_USES_HOST_PAGE_TABLES,
 * then this call has no effect.
 *
 * \param devPtr   - Pointer to memory to set the advice for
 * \param count    - Size in bytes of the memory range
 * \param advice   - Advice to be applied for the specified memory range
 * \param location - location to apply the advice for
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_DEVICE
 * \notefnerr
 * \note_async
 * \note_null_stream
 *
 * \sa ::cuMemcpy, ::cuMemcpyPeer, ::cuMemcpyAsync,
 * ::cuMemcpy3DPeerAsync, ::cuMemPrefetchAsync, ::cuMemAdvise
 * ::cudaMemAdvise
 */
CUresult CUDAAPI cuMemAdvise_v2(CUdeviceptr devPtr, size_t count, CUmem_advise advice, CUmemLocation location);

/**
 * \brief Query an attribute of a given memory range
 *
 * Query an attribute about the memory range starting at \p devPtr with a size of \p count bytes. The
 * memory range must refer to managed memory allocated via ::cuMemAllocManaged or declared via
 * __managed__ variables.
 *
 * The \p attribute parameter can take the following values:
 * - ::CU_MEM_RANGE_ATTRIBUTE_READ_MOSTLY: If this attribute is specified, \p data will be interpreted
 * as a 32-bit integer, and \p dataSize must be 4. The result returned will be 1 if all pages in the given
 * memory range have read-duplication enabled, or 0 otherwise.
 * - ::CU_MEM_RANGE_ATTRIBUTE_PREFERRED_LOCATION: If this attribute is specified, \p data will be
 * interpreted as a 32-bit integer, and \p dataSize must be 4. The result returned will be a GPU device
 * id if all pages in the memory range have that GPU as their preferred location, or it will be CU_DEVICE_CPU
 * if all pages in the memory range have the CPU as their preferred location, or it will be CU_DEVICE_INVALID
 * if either all the pages don't have the same preferred location or some of the pages don't have a
 * preferred location at all. Note that the actual location of the pages in the memory range at the time of
 * the query may be different from the preferred location.
 * - ::CU_MEM_RANGE_ATTRIBUTE_ACCESSED_BY: If this attribute is specified, \p data will be interpreted
 * as an array of 32-bit integers, and \p dataSize must be a non-zero multiple of 4. The result returned
 * will be a list of device ids that had ::CU_MEM_ADVISE_SET_ACCESSED_BY set for that entire memory range.
 * If any device does not have that advice set for the entire memory range, that device will not be included.
 * If \p data is larger than the number of devices that have that advice set for that memory range,
 * CU_DEVICE_INVALID will be returned in all the extra space provided. For ex., if \p dataSize is 12
 * (i.e. \p data has 3 elements) and only device 0 has the advice set, then the result returned will be
 * { 0, CU_DEVICE_INVALID, CU_DEVICE_INVALID }. If \p data is smaller than the number of devices that have
 * that advice set, then only as many devices will be returned as can fit in the array. There is no
 * guarantee on which specific devices will be returned, however.
 * - ::CU_MEM_RANGE_ATTRIBUTE_LAST_PREFETCH_LOCATION: If this attribute is specified, \p data will be
 * interpreted as a 32-bit integer, and \p dataSize must be 4. The result returned will be the last location
 * to which all pages in the memory range were prefetched explicitly via ::cuMemPrefetchAsync. This will either be
 * a GPU id or CU_DEVICE_CPU depending on whether the last location for prefetch was a GPU or the CPU
 * respectively. If any page in the memory range was never explicitly prefetched or if all pages were not
 * prefetched to the same location, CU_DEVICE_INVALID will be returned. Note that this simply returns the
 * last location that the application requested to prefetch the memory range to. It gives no indication as to
 * whether the prefetch operation to that location has completed or even begun.
 * - ::CU_MEM_RANGE_ATTRIBUTE_PREFERRED_LOCATION_TYPE: If this attribute is specified, \p data will be
 * interpreted as a ::CUmemLocationType, and \p dataSize must be sizeof(CUmemLocationType). The ::CUmemLocationType returned will be
 * ::CU_MEM_LOCATION_TYPE_DEVICE if all pages in the memory range have the same GPU as their preferred location, or ::CUmemLocationType
 * will be ::CU_MEM_LOCATION_TYPE_HOST if all pages in the memory range have the CPU as their preferred location, or it will be ::CU_MEM_LOCATION_TYPE_HOST_NUMA
 * if all the pages in the memory range have the same host NUMA node ID as their preferred location or it will be ::CU_MEM_LOCATION_TYPE_INVALID
 * if either all the pages don't have the same preferred location or some of the pages don't have a preferred location at all.
 * Note that the actual location type of the pages in the memory range at the time of the query may be different from the preferred location type.
 *  - ::CU_MEM_RANGE_ATTRIBUTE_PREFERRED_LOCATION_ID: If this attribute is specified, \p data will be
 * interpreted as a 32-bit integer, and \p dataSize must be 4. If the ::CU_MEM_RANGE_ATTRIBUTE_PREFERRED_LOCATION_TYPE query for the same address range
 * returns ::CU_MEM_LOCATION_TYPE_DEVICE, it will be a valid device ordinal or if it returns ::CU_MEM_LOCATION_TYPE_HOST_NUMA, it will be a valid host NUMA node ID
 * or if it returns any other location type, the id should be ignored.
 * - ::CU_MEM_RANGE_ATTRIBUTE_LAST_PREFETCH_LOCATION_TYPE: If this attribute is specified, \p data will be
 * interpreted as a ::CUmemLocationType, and \p dataSize must be sizeof(CUmemLocationType). The result returned will be the last location
 * to which all pages in the memory range were prefetched explicitly via ::cuMemPrefetchAsync. The ::CUmemLocationType returned
 * will be ::CU_MEM_LOCATION_TYPE_DEVICE if the last prefetch location was a GPU or ::CU_MEM_LOCATION_TYPE_HOST if it was the CPU or ::CU_MEM_LOCATION_TYPE_HOST_NUMA if
 * the last prefetch location was a specific host NUMA node. If any page in the memory range was never explicitly prefetched or if all pages were not
 * prefetched to the same location, ::CUmemLocationType will be ::CU_MEM_LOCATION_TYPE_INVALID.
 * Note that this simply returns the last location type that the application requested to prefetch the memory range to. It gives no indication as to
 * whether the prefetch operation to that location has completed or even begun.
 *  - ::CU_MEM_RANGE_ATTRIBUTE_LAST_PREFETCH_LOCATION_ID: If this attribute is specified, \p data will be
 * interpreted as a 32-bit integer, and \p dataSize must be 4. If the ::CU_MEM_RANGE_ATTRIBUTE_LAST_PREFETCH_LOCATION_TYPE query for the same address range
 * returns ::CU_MEM_LOCATION_TYPE_DEVICE, it will be a valid device ordinal or if it returns ::CU_MEM_LOCATION_TYPE_HOST_NUMA, it will be a valid host NUMA node ID
 * or if it returns any other location type, the id should be ignored.
 *
 * \param data      - A pointers to a memory location where the result
 *                    of each attribute query will be written to.
 * \param dataSize  - Array containing the size of data
 * \param attribute - The attribute to query
 * \param devPtr    - Start of the range to query
 * \param count     - Size of the range to query
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_DEVICE
 * \notefnerr
 * \note_async
 * \note_null_stream
 *
 * \sa ::cuMemRangeGetAttributes, ::cuMemPrefetchAsync,
 * ::cuMemAdvise,
 * ::cudaMemRangeGetAttribute
 */
CUresult CUDAAPI cuMemRangeGetAttribute(void *data, size_t dataSize, CUmem_range_attribute attribute, CUdeviceptr devPtr, size_t count);

/**
 * \brief Query attributes of a given memory range.
 *
 * Query attributes of the memory range starting at \p devPtr with a size of \p count bytes. The
 * memory range must refer to managed memory allocated via ::cuMemAllocManaged or declared via
 * __managed__ variables. The \p attributes array will be interpreted to have \p numAttributes
 * entries. The \p dataSizes array will also be interpreted to have \p numAttributes entries.
 * The results of the query will be stored in \p data.
 *
 * The list of supported attributes are given below. Please refer to ::cuMemRangeGetAttribute for
 * attribute descriptions and restrictions.
 *
 * - ::CU_MEM_RANGE_ATTRIBUTE_READ_MOSTLY
 * - ::CU_MEM_RANGE_ATTRIBUTE_PREFERRED_LOCATION
 * - ::CU_MEM_RANGE_ATTRIBUTE_ACCESSED_BY
 * - ::CU_MEM_RANGE_ATTRIBUTE_LAST_PREFETCH_LOCATION
 * - ::CU_MEM_RANGE_ATTRIBUTE_PREFERRED_LOCATION_TYPE
 * - ::CU_MEM_RANGE_ATTRIBUTE_PREFERRED_LOCATION_ID
 * - ::CU_MEM_RANGE_ATTRIBUTE_LAST_PREFETCH_LOCATION_TYPE
 * - ::CU_MEM_RANGE_ATTRIBUTE_LAST_PREFETCH_LOCATION_ID
 *
 * \param data          - A two-dimensional array containing pointers to memory
 *                        locations where the result of each attribute query will be written to.
 * \param dataSizes     - Array containing the sizes of each result
 * \param attributes    - An array of attributes to query
 *                        (numAttributes and the number of attributes in this array should match)
 * \param numAttributes - Number of attributes to query
 * \param devPtr        - Start of the range to query
 * \param count         - Size of the range to query
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_DEVICE
 * \notefnerr
 *
 * \sa ::cuMemRangeGetAttribute, ::cuMemAdvise,
 * ::cuMemPrefetchAsync,
 * ::cudaMemRangeGetAttributes
 */
CUresult CUDAAPI cuMemRangeGetAttributes(void **data, size_t *dataSizes, CUmem_range_attribute *attributes, size_t numAttributes, CUdeviceptr devPtr, size_t count);

/**
 * \brief Set attributes on a previously allocated memory region
 *
 * The supported attributes are:
 *
 * - ::CU_POINTER_ATTRIBUTE_SYNC_MEMOPS:
 *
 *      A boolean attribute that can either be set (1) or unset (0). When set,
 *      the region of memory that \p ptr points to is guaranteed to always synchronize
 *      memory operations that are synchronous. If there are some previously initiated
 *      synchronous memory operations that are pending when this attribute is set, the
 *      function does not return until those memory operations are complete.
 *      See further documentation in the section titled "API synchronization behavior"
 *      to learn more about cases when synchronous memory operations can
 *      exhibit asynchronous behavior.
 *      \p value will be considered as a pointer to an unsigned integer to which this attribute is to be set.
 *
 * \param value     - Pointer to memory containing the value to be set
 * \param attribute - Pointer attribute to set
 * \param ptr       - Pointer to a memory region allocated using CUDA memory allocation APIs
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_DEVICE
 * \notefnerr
 *
 * \sa ::cuPointerGetAttribute,
 * ::cuPointerGetAttributes,
 * ::cuMemAlloc,
 * ::cuMemFree,
 * ::cuMemAllocHost,
 * ::cuMemFreeHost,
 * ::cuMemHostAlloc,
 * ::cuMemHostRegister,
 * ::cuMemHostUnregister
 */
CUresult CUDAAPI cuPointerSetAttribute(const void *value, CUpointer_attribute attribute, CUdeviceptr ptr);

/**
 * \brief Returns information about a pointer.
 *
 * The supported attributes are (refer to ::cuPointerGetAttribute for attribute descriptions and restrictions):
 *
 * - ::CU_POINTER_ATTRIBUTE_CONTEXT
 * - ::CU_POINTER_ATTRIBUTE_MEMORY_TYPE
 * - ::CU_POINTER_ATTRIBUTE_DEVICE_POINTER
 * - ::CU_POINTER_ATTRIBUTE_HOST_POINTER
 * - ::CU_POINTER_ATTRIBUTE_SYNC_MEMOPS
 * - ::CU_POINTER_ATTRIBUTE_BUFFER_ID
 * - ::CU_POINTER_ATTRIBUTE_IS_MANAGED
 * - ::CU_POINTER_ATTRIBUTE_DEVICE_ORDINAL
 * - ::CU_POINTER_ATTRIBUTE_RANGE_START_ADDR
 * - ::CU_POINTER_ATTRIBUTE_RANGE_SIZE
 * - ::CU_POINTER_ATTRIBUTE_MAPPED
 * - ::CU_POINTER_ATTRIBUTE_IS_LEGACY_CUDA_IPC_CAPABLE
 * - ::CU_POINTER_ATTRIBUTE_ALLOWED_HANDLE_TYPES
 * - ::CU_POINTER_ATTRIBUTE_MEMPOOL_HANDLE
 * - ::CU_POINTER_ATTRIBUTE_IS_HW_DECOMPRESS_CAPABLE
 *
 * \param numAttributes - Number of attributes to query
 * \param attributes    - An array of attributes to query
 *                      (numAttributes and the number of attributes in this array should match)
 * \param data          - A two-dimensional array containing pointers to memory
 *                      locations where the result of each attribute query will be written to.
 * \param ptr           - Pointer to query
 *
 * Unlike ::cuPointerGetAttribute, this function will not return an error when the \p ptr
 * encountered is not a valid CUDA pointer. Instead, the attributes are assigned default NULL values
 * and CUDA_SUCCESS is returned.
 *
 * If \p ptr was not allocated by, mapped by, or registered with a ::CUcontext which uses UVA
 * (Unified Virtual Addressing), ::CUDA_ERROR_INVALID_CONTEXT is returned.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_DEVICE
 * \notefnerr
 *
 * \sa
 * ::cuPointerGetAttribute,
 * ::cuPointerSetAttribute,
 * ::cudaPointerGetAttributes
 */
CUresult CUDAAPI cuPointerGetAttributes(unsigned int numAttributes, CUpointer_attribute *attributes, void **data, CUdeviceptr ptr);

/** @} */ /* END CUDA_UNIFIED */

/**
 * \defgroup CUDA_STREAM Stream Management
 *
 * ___MANBRIEF___ stream management functions of the low-level CUDA driver API
 * (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the stream management functions of the low-level CUDA
 * driver application programming interface.
 *
 * @{
 */

/**
 * \brief Create a stream
 *
 * Creates a stream and returns a handle in \p phStream.  The \p Flags argument
 * determines behaviors of the stream.
 *
 * Valid values for \p Flags are:
 * - ::CU_STREAM_DEFAULT: Default stream creation flag.
 * - ::CU_STREAM_NON_BLOCKING: Specifies that work running in the created
 *   stream may run concurrently with work in stream 0 (the NULL stream), and that
 *   the created stream should perform no implicit synchronization with stream 0.
 *
 * \param phStream - Returned newly created stream
 * \param Flags    - Parameters for stream creation
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_OUT_OF_MEMORY
 * \notefnerr
 *
 * \sa ::cuStreamDestroy,
 * ::cuStreamCreateWithPriority,
 * ::cuGreenCtxStreamCreate,
 * ::cuStreamGetPriority,
 * ::cuStreamGetFlags,
 * ::cuStreamGetDevice
 * ::cuStreamWaitEvent,
 * ::cuStreamQuery,
 * ::cuStreamSynchronize,
 * ::cuStreamAddCallback,
 * ::cudaStreamCreate,
 * ::cudaStreamCreateWithFlags
 */
CUresult CUDAAPI cuStreamCreate(CUstream *phStream, unsigned int Flags);

/**
 * \brief Create a stream with the given priority
 *
 * Creates a stream with the specified priority and returns a handle in \p phStream.
 * This affects the scheduling priority of work in the stream. Priorities provide a
 * hint to preferentially run work with higher priority when possible, but do
 * not preempt already-running work or provide any other functional guarantee on
 * execution order.
 *
 * \p priority follows a convention where lower numbers represent higher priorities.
 * '0' represents default priority. The range of meaningful numerical priorities can
 * be queried using ::cuCtxGetStreamPriorityRange. If the specified priority is
 * outside the numerical range returned by ::cuCtxGetStreamPriorityRange,
 * it will automatically be clamped to the lowest or the highest number in the range.
 *
 * \param phStream    - Returned newly created stream
 * \param flags       - Flags for stream creation. See ::cuStreamCreate for a list of
 *                      valid flags
 * \param priority    - Stream priority. Lower numbers represent higher priorities.
 *                      See ::cuCtxGetStreamPriorityRange for more information about
 *                      meaningful stream priorities that can be passed.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_OUT_OF_MEMORY
 * \notefnerr
 *
 * \note Stream priorities are supported only on GPUs
 * with compute capability 3.5 or higher.
 *
 * \note In the current implementation, only compute kernels launched in
 * priority streams are affected by the stream's priority. Stream priorities have
 * no effect on host-to-device and device-to-host memory operations.
 *
 * \sa ::cuStreamDestroy,
 * ::cuStreamCreate,
 * ::cuGreenCtxStreamCreate,
 * ::cuStreamGetPriority,
 * ::cuCtxGetStreamPriorityRange,
 * ::cuStreamGetFlags,
 * ::cuStreamGetDevice
 * ::cuStreamWaitEvent,
 * ::cuStreamQuery,
 * ::cuStreamSynchronize,
 * ::cuStreamAddCallback,
 * ::cudaStreamCreateWithPriority
 */
CUresult CUDAAPI cuStreamCreateWithPriority(CUstream *phStream, unsigned int flags, int priority);


/**
 * \brief Query the priority of a given stream
 *
 * Query the priority of a stream created using ::cuStreamCreate, ::cuStreamCreateWithPriority or ::cuGreenCtxStreamCreate
 * and return the priority in \p priority. Note that if the stream was created with a
 * priority outside the numerical range returned by ::cuCtxGetStreamPriorityRange,
 * this function returns the clamped priority.
 * See ::cuStreamCreateWithPriority for details about priority clamping.
 *
 * \param hStream    - Handle to the stream to be queried
 * \param priority   - Pointer to a signed integer in which the stream's priority is returned
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_OUT_OF_MEMORY
 * \notefnerr
 *
 * \sa ::cuStreamDestroy,
 * ::cuStreamCreate,
 * ::cuStreamCreateWithPriority,
 * ::cuGreenCtxStreamCreate,
 * ::cuCtxGetStreamPriorityRange,
 * ::cuStreamGetFlags,
 * ::cuStreamGetDevice
 * ::cudaStreamGetPriority
 */
CUresult CUDAAPI cuStreamGetPriority(CUstream hStream, int *priority);

/**
 * \brief Returns the device handle of the stream
 *
 * Returns in \p *device the device handle of the stream
 *
 * \param hStream - Handle to the stream to be queried
 * \param device - Returns the device to which a stream belongs 
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_OUT_OF_MEMORY
 * \notefnerr
 *
 * \sa
 * ::cuStreamDestroy,
 * ::cuStreamCreate,
 * ::cuGreenCtxStreamCreate,
 * ::cuStreamGetFlags
 */
CUresult CUDAAPI cuStreamGetDevice(CUstream hStream, CUdevice *device);

/**
 * \brief Query the flags of a given stream
 *
 * Query the flags of a stream created using ::cuStreamCreate, ::cuStreamCreateWithPriority or ::cuGreenCtxStreamCreate
 * and return the flags in \p flags.
 *
 * \param hStream    - Handle to the stream to be queried
 * \param flags      - Pointer to an unsigned integer in which the stream's flags are returned
 *                     The value returned in \p flags is a logical 'OR' of all flags that
 *                     were used while creating this stream. See ::cuStreamCreate for the list
 *                     of valid flags
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_OUT_OF_MEMORY
 * \notefnerr
 *
 * \sa ::cuStreamDestroy,
 * ::cuStreamCreate,
 * ::cuGreenCtxStreamCreate,
 * ::cuStreamGetPriority,
 * ::cudaStreamGetFlags
 * ::cuStreamGetDevice
 */
CUresult CUDAAPI cuStreamGetFlags(CUstream hStream, unsigned int *flags);

/**
 * \brief Returns the unique Id associated with the stream handle supplied
 *
 * Returns in \p streamId the unique Id which is associated with the given stream handle.
 * The Id is unique for the life of the program.
 * 
 * The stream handle \p hStream can refer to any of the following:
 * <ul>
 *   <li>a stream created via any of the CUDA driver APIs such as ::cuStreamCreate
 *   and ::cuStreamCreateWithPriority, or their runtime API equivalents such as
 *   ::cudaStreamCreate, ::cudaStreamCreateWithFlags and ::cudaStreamCreateWithPriority.
 *   Passing an invalid handle will result in undefined behavior.</li>
 *   <li>any of the special streams such as the NULL stream, ::CU_STREAM_LEGACY and
 *   ::CU_STREAM_PER_THREAD. The runtime API equivalents of these are also accepted,
 *   which are NULL, ::cudaStreamLegacy and ::cudaStreamPerThread respectively.</li>
 * </ul>
 *
 * \param hStream    - Handle to the stream to be queried
 * \param streamId   - Pointer to store the Id of the stream
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_HANDLE
 * \notefnerr
 *
 * \sa ::cuStreamDestroy,
 * ::cuStreamCreate,
 * ::cuStreamGetPriority,
 * ::cudaStreamGetId
 */
CUresult CUDAAPI cuStreamGetId(CUstream hStream, unsigned long long *streamId);

/**
 * \brief Query the context associated with a stream
 *
 * Returns the CUDA context that the stream is associated with.
 *
 * Note there is a later version of this API, ::cuStreamGetCtx_v2. It will
 * supplant this version in CUDA 13.0. It is recommended to use ::cuStreamGetCtx_v2
 * till then as this version will return ::CUDA_ERROR_NOT_SUPPORTED for streams created via the API ::cuGreenCtxStreamCreate.
 *
 * The stream handle \p hStream can refer to any of the following:
 * <ul>
 *   <li>a stream created via any of the CUDA driver APIs such as ::cuStreamCreate
 *   and ::cuStreamCreateWithPriority, or their runtime API equivalents such as
 *   ::cudaStreamCreate, ::cudaStreamCreateWithFlags and ::cudaStreamCreateWithPriority.
 *   The returned context is the context that was active in the calling thread when the
 *   stream was created. Passing an invalid handle will result in undefined behavior.</li>
 *   <li>any of the special streams such as the NULL stream, ::CU_STREAM_LEGACY and
 *   ::CU_STREAM_PER_THREAD. The runtime API equivalents of these are also accepted,
 *   which are NULL, ::cudaStreamLegacy and ::cudaStreamPerThread respectively.
 *   Specifying any of the special handles will return the context current to the
 *   calling thread. If no context is current to the calling thread,
 *   ::CUDA_ERROR_INVALID_CONTEXT is returned.</li>
 * </ul>
 *
 * \param hStream - Handle to the stream to be queried
 * \param pctx    - Returned context associated with the stream
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_NOT_SUPPORTED
 * \notefnerr
 *
 * \sa ::cuStreamDestroy,
 * ::cuStreamCreateWithPriority,
 * ::cuStreamGetPriority,
 * ::cuStreamGetFlags,
 * ::cuStreamGetDevice
 * ::cuStreamWaitEvent,
 * ::cuStreamQuery,
 * ::cuStreamSynchronize,
 * ::cuStreamAddCallback,
 * ::cudaStreamCreate,
 * ::cuStreamGetCtx_v2,
 * ::cudaStreamCreateWithFlags
 */
CUresult CUDAAPI cuStreamGetCtx(CUstream hStream, CUcontext *pctx);

/**
 * \brief Query the contexts associated with a stream
 *
 * Returns the contexts that the stream is associated with.
 *
 * If the stream is associated with a green context, the API returns the green context in \p pGreenCtx
 * and the primary context of the associated device in \p pCtx.
 *
 * If the stream is associated with a regular context, the API returns the regular context in \p pCtx
 * and NULL in \p pGreenCtx.
 *
 * The stream handle \p hStream can refer to any of the following:
 * <ul>
 *   <li>a stream created via any of the CUDA driver APIs such as ::cuStreamCreate,
 *   ::cuStreamCreateWithPriority and ::cuGreenCtxStreamCreate, or their runtime API equivalents such as
 *   ::cudaStreamCreate, ::cudaStreamCreateWithFlags and ::cudaStreamCreateWithPriority.
 *   Passing an invalid handle will result in undefined behavior.</li>
 *   <li>any of the special streams such as the NULL stream, ::CU_STREAM_LEGACY and
 *   ::CU_STREAM_PER_THREAD. The runtime API equivalents of these are also accepted,
 *   which are NULL, ::cudaStreamLegacy and ::cudaStreamPerThread respectively.
 *   If any of the special handles are specified, the API will operate on the context current to the
 *   calling thread. If a green context (that was converted via ::cuCtxFromGreenCtx() before setting it current)
 *   is current to the calling thread, the API will return the green context in \p pGreenCtx
 *   and the primary context of the associated device in \p pCtx. If a regular context is current,
 *   the API returns the regular context in \p pCtx and NULL in \p pGreenCtx.
 *   Note that specifying ::CU_STREAM_PER_THREAD or ::cudaStreamPerThread will return ::CUDA_ERROR_INVALID_HANDLE
 *   if a green context is current to the calling thread.
 *   If no context is current to the calling thread, ::CUDA_ERROR_INVALID_CONTEXT is returned.</li>
 * </ul>
 *
 * \param hStream   - Handle to the stream to be queried
 * \param pCtx      - Returned regular context associated with the stream
 * \param pGreenCtx - Returned green context if the stream is associated with a green context or NULL if not
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_HANDLE
 * \notefnerr
 *
 * \sa ::cuStreamDestroy,
 * ::cuStreamCreate
 * ::cuStreamCreateWithPriority,
 * ::cuGreenCtxStreamCreate,
 * ::cuStreamGetPriority,
 * ::cuStreamGetFlags,
 * ::cuStreamGetDevice
 * ::cuStreamWaitEvent,
 * ::cuStreamQuery,
 * ::cuStreamSynchronize,
 * ::cuStreamAddCallback,
 * ::cudaStreamCreate,
 * ::cudaStreamCreateWithFlags,
 */
CUresult CUDAAPI cuStreamGetCtx_v2(CUstream hStream, CUcontext *pCtx, CUgreenCtx *pGreenCtx);

/**
 * \brief Make a compute stream wait on an event
 *
 * Makes all future work submitted to \p hStream wait for all work captured in
 * \p hEvent.  See ::cuEventRecord() for details on what is captured by an event.
 * The synchronization will be performed efficiently on the device when applicable.
 * \p hEvent may be from a different context or device than \p hStream.
 *
 * flags include:
 * - ::CU_EVENT_WAIT_DEFAULT: Default event creation flag.
 * - ::CU_EVENT_WAIT_EXTERNAL: Event is captured in the graph as an external
 *   event node when performing stream capture. This flag is invalid outside
 *   of stream capture.
 *
 * \param hStream - Stream to wait
 * \param hEvent  - Event to wait on (may not be NULL)
 * \param Flags   - See ::CUevent_capture_flags
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * \note_null_stream
 * \notefnerr
 *
 * \sa ::cuStreamCreate,
 * ::cuEventRecord,
 * ::cuStreamQuery,
 * ::cuStreamSynchronize,
 * ::cuStreamAddCallback,
 * ::cuStreamDestroy,
 * ::cudaStreamWaitEvent
 */
CUresult CUDAAPI cuStreamWaitEvent(CUstream hStream, CUevent hEvent, unsigned int Flags);

/**
 * \brief Add a callback to a compute stream
 *
 * \note This function is slated for eventual deprecation and removal. If
 * you do not require the callback to execute in case of a device error,
 * consider using ::cuLaunchHostFunc. Additionally, this function is not
 * supported with ::cuStreamBeginCapture and ::cuStreamEndCapture, unlike
 * ::cuLaunchHostFunc.
 *
 * Adds a callback to be called on the host after all currently enqueued
 * items in the stream have completed.  For each
 * cuStreamAddCallback call, the callback will be executed exactly once.
 * The callback will block later work in the stream until it is finished.
 *
 * The callback may be passed ::CUDA_SUCCESS or an error code.  In the event
 * of a device error, all subsequently executed callbacks will receive an
 * appropriate ::CUresult.
 *
 * Callbacks must not make any CUDA API calls.  Attempting to use a CUDA API
 * will result in ::CUDA_ERROR_NOT_PERMITTED.  Callbacks must not perform any
 * synchronization that may depend on outstanding device work or other callbacks
 * that are not mandated to run earlier.  Callbacks without a mandated order
 * (in independent streams) execute in undefined order and may be serialized.
 *
 * For the purposes of Unified Memory, callback execution makes a number of
 * guarantees:
 * <ul>
 *   <li>The callback stream is considered idle for the duration of the
 *   callback.  Thus, for example, a callback may always use memory attached
 *   to the callback stream.</li>
 *   <li>The start of execution of a callback has the same effect as
 *   synchronizing an event recorded in the same stream immediately prior to
 *   the callback.  It thus synchronizes streams which have been "joined"
 *   prior to the callback.</li>
 *   <li>Adding device work to any stream does not have the effect of making
 *   the stream active until all preceding host functions and stream callbacks
 *   have executed.  Thus, for
 *   example, a callback might use global attached memory even if work has
 *   been added to another stream, if the work has been ordered behind the
 *   callback with an event.</li>
 *   <li>Completion of a callback does not cause a stream to become
 *   active except as described above.  The callback stream will remain idle
 *   if no device work follows the callback, and will remain idle across
 *   consecutive callbacks without device work in between.  Thus, for example,
 *   stream synchronization can be done by signaling from a callback at the
 *   end of the stream.</li>
 * </ul>
 *
 * \param hStream  - Stream to add callback to
 * \param callback - The function to call once preceding stream operations are complete
 * \param userData - User specified data to be passed to the callback function
 * \param flags    - Reserved for future use, must be 0
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_NOT_SUPPORTED
 * \note_null_stream
 * \notefnerr
 *
 * \sa ::cuStreamCreate,
 * ::cuStreamQuery,
 * ::cuStreamSynchronize,
 * ::cuStreamWaitEvent,
 * ::cuStreamDestroy,
 * ::cuMemAllocManaged,
 * ::cuStreamAttachMemAsync,
 * ::cuLaunchHostFunc,
 * ::cudaStreamAddCallback
 */
CUresult CUDAAPI cuStreamAddCallback(CUstream hStream, CUstreamCallback callback, void *userData, unsigned int flags);

/**
 * \brief Begins graph capture on a stream
 *
 * Begin graph capture on \p hStream. When a stream is in capture mode, all operations
 * pushed into the stream will not be executed, but will instead be captured into
 * a graph, which will be returned via ::cuStreamEndCapture. Capture may not be initiated
 * if \p stream is CU_STREAM_LEGACY. Capture must be ended on the same stream in which
 * it was initiated, and it may only be initiated if the stream is not already in capture
 * mode. The capture mode may be queried via ::cuStreamIsCapturing. A unique id
 * representing the capture sequence may be queried via ::cuStreamGetCaptureInfo.
 *
 * If \p mode is not ::CU_STREAM_CAPTURE_MODE_RELAXED, ::cuStreamEndCapture must be
 * called on this stream from the same thread.
 *
 * \param hStream - Stream in which to initiate capture
 * \param mode    - Controls the interaction of this capture sequence with other API
 *                  calls that are potentially unsafe. For more details see
 *                  ::cuThreadExchangeStreamCaptureMode.
 *
 * \note Kernels captured using this API must not use texture and surface references.
 *       Reading or writing through any texture or surface reference is undefined
 *       behavior. This restriction does not apply to texture and surface objects.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 *
 * \sa
 * ::cuStreamCreate,
 * ::cuStreamIsCapturing,
 * ::cuStreamEndCapture,
 * ::cuThreadExchangeStreamCaptureMode
 */
CUresult CUDAAPI cuStreamBeginCapture(CUstream hStream, CUstreamCaptureMode mode);

/**
 * \brief Begins graph capture on a stream to an existing graph
 *
 * Begin graph capture on \p hStream, placing new nodes into an existing graph. When a stream is 
 * in capture mode, all operations pushed into the stream will not be executed, but will instead 
 * be captured into \p hGraph. The graph will not be instantiable until the user calls 
 * ::cuStreamEndCapture. 
 *  
 * Capture may not be initiated if \p stream is CU_STREAM_LEGACY. Capture must be ended on the 
 * same stream in which it was initiated, and it may only be initiated if the stream is not 
 * already in capture mode. The capture mode may be queried via ::cuStreamIsCapturing. A unique id
 * representing the capture sequence may be queried via ::cuStreamGetCaptureInfo.
 *
 * If \p mode is not ::CU_STREAM_CAPTURE_MODE_RELAXED, ::cuStreamEndCapture must be
 * called on this stream from the same thread.
 *
 * \param hStream         - Stream in which to initiate capture.
 * \param hGraph          - Graph to capture into.
 * \param dependencies    - Dependencies of the first node captured in the stream.  Can be NULL if numDependencies is 0.
 * \param dependencyData  - Optional array of data associated with each dependency.
 * \param numDependencies - Number of dependencies.
 * \param mode            - Controls the interaction of this capture sequence with other API
 *                          calls that are potentially unsafe. For more details see
 *                          ::cuThreadExchangeStreamCaptureMode.
 *
 * \note Kernels captured using this API must not use texture and surface references.
 *       Reading or writing through any texture or surface reference is undefined
 *       behavior. This restriction does not apply to texture and surface objects.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 *
 * \sa
 * ::cuStreamBeginCapture,
 * ::cuStreamCreate,
 * ::cuStreamIsCapturing,
 * ::cuStreamEndCapture,
 * ::cuThreadExchangeStreamCaptureMode,
 * ::cuGraphAddNode,
 */
CUresult CUDAAPI cuStreamBeginCaptureToGraph(CUstream hStream, CUgraph hGraph, const CUgraphNode *dependencies, const CUgraphEdgeData *dependencyData, size_t numDependencies, CUstreamCaptureMode mode);

/**
 * \brief Swaps the stream capture interaction mode for a thread
 *
 * Sets the calling thread's stream capture interaction mode to the value contained
 * in \p *mode, and overwrites \p *mode with the previous mode for the thread. To
 * facilitate deterministic behavior across function or module boundaries, callers
 * are encouraged to use this API in a push-pop fashion: \code
     CUstreamCaptureMode mode = desiredMode;
     cuThreadExchangeStreamCaptureMode(&mode);
     ...
     cuThreadExchangeStreamCaptureMode(&mode); // restore previous mode
 * \endcode
 *
 * During stream capture (see ::cuStreamBeginCapture), some actions, such as a call
 * to ::cudaMalloc, may be unsafe. In the case of ::cudaMalloc, the operation is
 * not enqueued asynchronously to a stream, and is not observed by stream capture.
 * Therefore, if the sequence of operations captured via ::cuStreamBeginCapture
 * depended on the allocation being replayed whenever the graph is launched, the
 * captured graph would be invalid.
 *
 * Therefore, stream capture places restrictions on API calls that can be made within
 * or concurrently to a ::cuStreamBeginCapture-::cuStreamEndCapture sequence. This
 * behavior can be controlled via this API and flags to ::cuStreamBeginCapture.
 *
 * A thread's mode is one of the following:
 * - \p CU_STREAM_CAPTURE_MODE_GLOBAL: This is the default mode. If the local thread has
 *   an ongoing capture sequence that was not initiated with
 *   \p CU_STREAM_CAPTURE_MODE_RELAXED at \p cuStreamBeginCapture, or if any other thread
 *   has a concurrent capture sequence initiated with \p CU_STREAM_CAPTURE_MODE_GLOBAL,
 *   this thread is prohibited from potentially unsafe API calls.
 * - \p CU_STREAM_CAPTURE_MODE_THREAD_LOCAL: If the local thread has an ongoing capture
 *   sequence not initiated with \p CU_STREAM_CAPTURE_MODE_RELAXED, it is prohibited
 *   from potentially unsafe API calls. Concurrent capture sequences in other threads
 *   are ignored.
 * - \p CU_STREAM_CAPTURE_MODE_RELAXED: The local thread is not prohibited from potentially
 *   unsafe API calls. Note that the thread is still prohibited from API calls which
 *   necessarily conflict with stream capture, for example, attempting ::cuEventQuery
 *   on an event that was last recorded inside a capture sequence.
 *
 * \param mode - Pointer to mode value to swap with the current mode
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 *
 * \sa
 * ::cuStreamBeginCapture
 */
CUresult CUDAAPI cuThreadExchangeStreamCaptureMode(CUstreamCaptureMode *mode);

/**
 * \brief Ends capture on a stream, returning the captured graph
 *
 * End capture on \p hStream, returning the captured graph via \p phGraph.
 * Capture must have been initiated on \p hStream via a call to ::cuStreamBeginCapture.
 * If capture was invalidated, due to a violation of the rules of stream capture, then
 * a NULL graph will be returned.
 *
 * If the \p mode argument to ::cuStreamBeginCapture was not
 * ::CU_STREAM_CAPTURE_MODE_RELAXED, this call must be from the same thread as
 * ::cuStreamBeginCapture.
 *
 * \param hStream - Stream to query
 * \param phGraph - The captured graph
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_STREAM_CAPTURE_WRONG_THREAD
 * \notefnerr
 *
 * \sa
 * ::cuStreamCreate,
 * ::cuStreamBeginCapture,
 * ::cuStreamIsCapturing,
 * ::cuGraphDestroy
 */
CUresult CUDAAPI cuStreamEndCapture(CUstream hStream, CUgraph *phGraph);

/**
 * \brief Returns a stream's capture status
 *
 * Return the capture status of \p hStream via \p captureStatus. After a successful
 * call, \p *captureStatus will contain one of the following:
 * - ::CU_STREAM_CAPTURE_STATUS_NONE: The stream is not capturing.
 * - ::CU_STREAM_CAPTURE_STATUS_ACTIVE: The stream is capturing.
 * - ::CU_STREAM_CAPTURE_STATUS_INVALIDATED: The stream was capturing but an error
 *   has invalidated the capture sequence. The capture sequence must be terminated
 *   with ::cuStreamEndCapture on the stream where it was initiated in order to
 *   continue using \p hStream.
 *
 * Note that, if this is called on ::CU_STREAM_LEGACY (the "null stream") while
 * a blocking stream in the same context is capturing, it will return
 * ::CUDA_ERROR_STREAM_CAPTURE_IMPLICIT and \p *captureStatus is unspecified
 * after the call. The blocking stream capture is not invalidated.
 *
 * When a blocking stream is capturing, the legacy stream is in an
 * unusable state until the blocking stream capture is terminated. The legacy
 * stream is not supported for stream capture, but attempted use would have an
 * implicit dependency on the capturing stream(s).
 *
 * \param hStream       - Stream to query
 * \param captureStatus - Returns the stream's capture status
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_STREAM_CAPTURE_IMPLICIT
 * \notefnerr
 *
 * \sa
 * ::cuStreamCreate,
 * ::cuStreamBeginCapture,
 * ::cuStreamEndCapture
 */
CUresult CUDAAPI cuStreamIsCapturing(CUstream hStream, CUstreamCaptureStatus *captureStatus);


/**
 * \brief Query a stream's capture state
 *
 * Query stream state related to stream capture.
 *
 * If called on ::CU_STREAM_LEGACY (the "null stream") while a stream not created 
 * with ::CU_STREAM_NON_BLOCKING is capturing, returns ::CUDA_ERROR_STREAM_CAPTURE_IMPLICIT.
 *
 * Valid data (other than capture status) is returned only if both of the following are true:
 * - the call returns CUDA_SUCCESS
 * - the returned capture status is ::CU_STREAM_CAPTURE_STATUS_ACTIVE
 *
 * \param hStream - The stream to query
 * \param captureStatus_out - Location to return the capture status of the stream; required
 * \param id_out - Optional location to return an id for the capture sequence, which is
 *           unique over the lifetime of the process
 * \param graph_out - Optional location to return the graph being captured into. All
 *           operations other than destroy and node removal are permitted on the graph
 *           while the capture sequence is in progress. This API does not transfer
 *           ownership of the graph, which is transferred or destroyed at
 *           ::cuStreamEndCapture. Note that the graph handle may be invalidated before
 *           end of capture for certain errors. Nodes that are or become
 *           unreachable from the original stream at ::cuStreamEndCapture due to direct
 *           actions on the graph do not trigger ::CUDA_ERROR_STREAM_CAPTURE_UNJOINED.
 * \param dependencies_out - Optional location to store a pointer to an array of nodes.
 *           The next node to be captured in the stream will depend on this set of nodes,
 *           absent operations such as event wait which modify this set. The array pointer
 *           is valid until the next API call which operates on the stream or until the
 *           capture is terminated. The node handles may be copied out and are valid until
 *           they or the graph is destroyed. The driver-owned array may also be passed
 *           directly to APIs that operate on the graph (not the stream) without copying.
 * \param numDependencies_out - Optional location to store the size of the array
 *           returned in dependencies_out.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_STREAM_CAPTURE_IMPLICIT
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuStreamGetCaptureInfo_v3
 * ::cuStreamBeginCapture,
 * ::cuStreamIsCapturing,
 * ::cuStreamUpdateCaptureDependencies
 */
CUresult CUDAAPI cuStreamGetCaptureInfo(CUstream hStream, CUstreamCaptureStatus *captureStatus_out,
        cuuint64_t *id_out, CUgraph *graph_out, const CUgraphNode **dependencies_out, size_t *numDependencies_out);

/**
 * \brief Query a stream's capture state (12.3+)
 *
 * Query stream state related to stream capture.
 *
 * If called on ::CU_STREAM_LEGACY (the "null stream") while a stream not created 
 * with ::CU_STREAM_NON_BLOCKING is capturing, returns ::CUDA_ERROR_STREAM_CAPTURE_IMPLICIT.
 *
 * Valid data (other than capture status) is returned only if both of the following are true:
 * - the call returns CUDA_SUCCESS
 * - the returned capture status is ::CU_STREAM_CAPTURE_STATUS_ACTIVE
 *
 * If \p edgeData_out is non-NULL then \p dependencies_out must be as well. If
 * \p dependencies_out is non-NULL and \p edgeData_out is NULL, but there is non-zero edge
 * data for one or more of the current stream dependencies, the call will return
 * ::CUDA_ERROR_LOSSY_QUERY.
 *
 * \param hStream - The stream to query
 * \param captureStatus_out - Location to return the capture status of the stream; required
 * \param id_out - Optional location to return an id for the capture sequence, which is
 *           unique over the lifetime of the process
 * \param graph_out - Optional location to return the graph being captured into. All
 *           operations other than destroy and node removal are permitted on the graph
 *           while the capture sequence is in progress. This API does not transfer
 *           ownership of the graph, which is transferred or destroyed at
 *           ::cuStreamEndCapture. Note that the graph handle may be invalidated before
 *           end of capture for certain errors. Nodes that are or become
 *           unreachable from the original stream at ::cuStreamEndCapture due to direct
 *           actions on the graph do not trigger ::CUDA_ERROR_STREAM_CAPTURE_UNJOINED.
 * \param dependencies_out - Optional location to store a pointer to an array of nodes.
 *           The next node to be captured in the stream will depend on this set of nodes,
 *           absent operations such as event wait which modify this set. The array pointer
 *           is valid until the next API call which operates on the stream or until the
 *           capture is terminated. The node handles may be copied out and are valid until
 *           they or the graph is destroyed. The driver-owned array may also be passed
 *           directly to APIs that operate on the graph (not the stream) without copying.
 * \param edgeData_out - Optional location to store a pointer to an array of graph edge
 *           data. This array parallels \c dependencies_out; the next node to be added
 *           has an edge to \c dependencies_out[i] with annotation \c edgeData_out[i] for
 *           each \c i. The array pointer is valid until the next API call which operates
 *           on the stream or until the capture is terminated.
 * \param numDependencies_out - Optional location to store the size of the array
 *           returned in dependencies_out.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_STREAM_CAPTURE_IMPLICIT,
 * ::CUDA_ERROR_LOSSY_QUERY
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuStreamGetCaptureInfo
 * ::cuStreamBeginCapture,
 * ::cuStreamIsCapturing,
 * ::cuStreamUpdateCaptureDependencies
 */
CUresult CUDAAPI cuStreamGetCaptureInfo_v3(CUstream hStream, CUstreamCaptureStatus *captureStatus_out,
        cuuint64_t *id_out, CUgraph *graph_out, const CUgraphNode **dependencies_out,
        const CUgraphEdgeData **edgeData_out, size_t *numDependencies_out);

/**
 * \brief Update the set of dependencies in a capturing stream (11.3+)
 *
 * Modifies the dependency set of a capturing stream. The dependency set is the set
 * of nodes that the next captured node in the stream will depend on.
 *
 * Valid flags are ::CU_STREAM_ADD_CAPTURE_DEPENDENCIES and
 * ::CU_STREAM_SET_CAPTURE_DEPENDENCIES. These control whether the set passed to
 * the API is added to the existing set or replaces it. A flags value of 0 defaults
 * to ::CU_STREAM_ADD_CAPTURE_DEPENDENCIES.
 *
 * Nodes that are removed from the dependency set via this API do not result in
 * ::CUDA_ERROR_STREAM_CAPTURE_UNJOINED if they are unreachable from the stream at
 * ::cuStreamEndCapture.
 *
 * Returns ::CUDA_ERROR_ILLEGAL_STATE if the stream is not capturing.
 *
 * This API is new in CUDA 11.3. Developers requiring compatibility across minor
 * versions to CUDA 11.0 should not use this API or provide a fallback.
 *
 * \param hStream - The stream to update
 * \param dependencies - The set of dependencies to add
 * \param numDependencies - The size of the dependencies array
 * \param flags - See above
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_ILLEGAL_STATE
 *
 * \sa
 * ::cuStreamBeginCapture,
 * ::cuStreamGetCaptureInfo,
 */
CUresult CUDAAPI cuStreamUpdateCaptureDependencies(CUstream hStream, CUgraphNode *dependencies, size_t numDependencies, unsigned int flags);

/**
 * \brief Update the set of dependencies in a capturing stream (12.3+)
 *
 * Modifies the dependency set of a capturing stream. The dependency set is the set
 * of nodes that the next captured node in the stream will depend on along with the
 * edge data for those dependencies.
 *
 * Valid flags are ::CU_STREAM_ADD_CAPTURE_DEPENDENCIES and
 * ::CU_STREAM_SET_CAPTURE_DEPENDENCIES. These control whether the set passed to
 * the API is added to the existing set or replaces it. A flags value of 0 defaults
 * to ::CU_STREAM_ADD_CAPTURE_DEPENDENCIES.
 *
 * Nodes that are removed from the dependency set via this API do not result in
 * ::CUDA_ERROR_STREAM_CAPTURE_UNJOINED if they are unreachable from the stream at
 * ::cuStreamEndCapture.
 *
 * Returns ::CUDA_ERROR_ILLEGAL_STATE if the stream is not capturing.
 *
 * \param hStream - The stream to update
 * \param dependencies - The set of dependencies to add
 * \param dependencyData - Optional array of data associated with each dependency.
 * \param numDependencies - The size of the dependencies array
 * \param flags - See above
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_ILLEGAL_STATE
 *
 * \sa
 * ::cuStreamBeginCapture,
 * ::cuStreamGetCaptureInfo,
 */
CUresult CUDAAPI cuStreamUpdateCaptureDependencies_v2(CUstream hStream, CUgraphNode *dependencies,
    const CUgraphEdgeData *dependencyData, size_t numDependencies, unsigned int flags);

/**
 * \brief Attach memory to a stream asynchronously
 *
 * Enqueues an operation in \p hStream to specify stream association of
 * \p length bytes of memory starting from \p dptr. This function is a
 * stream-ordered operation, meaning that it is dependent on, and will
 * only take effect when, previous work in stream has completed. Any
 * previous association is automatically replaced.
 *
 * \p dptr must point to one of the following types of memories:
 * - managed memory declared using the __managed__ keyword or allocated with
 *   ::cuMemAllocManaged.
 * - a valid host-accessible region of system-allocated pageable memory. This
 *   type of memory may only be specified if the device associated with the
 *   stream reports a non-zero value for the device attribute
 *   ::CU_DEVICE_ATTRIBUTE_PAGEABLE_MEMORY_ACCESS.
 *
 * For managed allocations, \p length must be either zero or the entire
 * allocation's size. Both indicate that the entire allocation's stream
 * association is being changed. Currently, it is not possible to change stream
 * association for a portion of a managed allocation.
 *
 * For pageable host allocations, \p length must be non-zero.
 *
 * The stream association is specified using \p flags which must be
 * one of ::CUmemAttach_flags.
 * If the ::CU_MEM_ATTACH_GLOBAL flag is specified, the memory can be accessed
 * by any stream on any device.
 * If the ::CU_MEM_ATTACH_HOST flag is specified, the program makes a guarantee
 * that it won't access the memory on the device from any stream on a device that
 * has a zero value for the device attribute ::CU_DEVICE_ATTRIBUTE_CONCURRENT_MANAGED_ACCESS.
 * If the ::CU_MEM_ATTACH_SINGLE flag is specified and \p hStream is associated with
 * a device that has a zero value for the device attribute ::CU_DEVICE_ATTRIBUTE_CONCURRENT_MANAGED_ACCESS,
 * the program makes a guarantee that it will only access the memory on the device
 * from \p hStream. It is illegal to attach singly to the NULL stream, because the
 * NULL stream is a virtual global stream and not a specific stream. An error will
 * be returned in this case.
 *
 * When memory is associated with a single stream, the Unified Memory system will
 * allow CPU access to this memory region so long as all operations in \p hStream
 * have completed, regardless of whether other streams are active. In effect,
 * this constrains exclusive ownership of the managed memory region by
 * an active GPU to per-stream activity instead of whole-GPU activity.
 *
 * Accessing memory on the device from streams that are not associated with
 * it will produce undefined results. No error checking is performed by the
 * Unified Memory system to ensure that kernels launched into other streams
 * do not access this region.
 *
 * It is a program's responsibility to order calls to ::cuStreamAttachMemAsync
 * via events, synchronization or other means to ensure legal access to memory
 * at all times. Data visibility and coherency will be changed appropriately
 * for all kernels which follow a stream-association change.
 *
 * If \p hStream is destroyed while data is associated with it, the association is
 * removed and the association reverts to the default visibility of the allocation
 * as specified at ::cuMemAllocManaged. For __managed__ variables, the default
 * association is always ::CU_MEM_ATTACH_GLOBAL. Note that destroying a stream is an
 * asynchronous operation, and as a result, the change to default association won't
 * happen until all work in the stream has completed.
 *
 * \param hStream - Stream in which to enqueue the attach operation
 * \param dptr    - Pointer to memory (must be a pointer to managed memory or
 *                  to a valid host-accessible region of system-allocated
 *                  pageable memory)
 * \param length  - Length of memory
 * \param flags   - Must be one of ::CUmemAttach_flags
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_NOT_SUPPORTED
 * \note_null_stream
 * \notefnerr
 *
 * \sa ::cuStreamCreate,
 * ::cuStreamQuery,
 * ::cuStreamSynchronize,
 * ::cuStreamWaitEvent,
 * ::cuStreamDestroy,
 * ::cuMemAllocManaged,
 * ::cudaStreamAttachMemAsync
 */
CUresult CUDAAPI cuStreamAttachMemAsync(CUstream hStream, CUdeviceptr dptr, size_t length, unsigned int flags);

/**
 * \brief Determine status of a compute stream
 *
 * Returns ::CUDA_SUCCESS if all operations in the stream specified by
 * \p hStream have completed, or ::CUDA_ERROR_NOT_READY if not.
 *
 * For the purposes of Unified Memory, a return value of ::CUDA_SUCCESS
 * is equivalent to having called ::cuStreamSynchronize().
 *
 * \param hStream - Stream to query status of
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_NOT_READY
 * \note_null_stream
 * \notefnerr
 *
 * \sa ::cuStreamCreate,
 * ::cuStreamWaitEvent,
 * ::cuStreamDestroy,
 * ::cuStreamSynchronize,
 * ::cuStreamAddCallback,
 * ::cudaStreamQuery
 */
CUresult CUDAAPI cuStreamQuery(CUstream hStream);

/**
 * \brief Wait until a stream's tasks are completed
 *
 * Waits until the device has completed all operations in the stream specified
 * by \p hStream. If the context was created with the
 * ::CU_CTX_SCHED_BLOCKING_SYNC flag, the CPU thread will block until the
 * stream is finished with all of its tasks.
 *
 * \param hStream - Stream to wait for
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_HANDLE

 * \note_null_stream
 * \notefnerr
 *
 * \sa ::cuStreamCreate,
 * ::cuStreamDestroy,
 * ::cuStreamWaitEvent,
 * ::cuStreamQuery,
 * ::cuStreamAddCallback,
 * ::cudaStreamSynchronize
 */
CUresult CUDAAPI cuStreamSynchronize(CUstream hStream);

/**
 * \brief Destroys a stream
 *
 * Destroys the stream specified by \p hStream.
 *
 * In case the device is still doing work in the stream \p hStream
 * when ::cuStreamDestroy() is called, the function will return immediately
 * and the resources associated with \p hStream will be released automatically
 * once the device has completed all work in \p hStream.
 *
 * \param hStream - Stream to destroy
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_HANDLE
 * \notefnerr
 *
 * \sa ::cuStreamCreate,
 * ::cuStreamWaitEvent,
 * ::cuStreamQuery,
 * ::cuStreamSynchronize,
 * ::cuStreamAddCallback,
 * ::cudaStreamDestroy
 */
CUresult CUDAAPI cuStreamDestroy(CUstream hStream);

/**
 * \brief Copies attributes from source stream to destination stream.
 *
 * Copies attributes from source stream \p src to destination stream \p dst.
 * Both streams must have the same context.
 *
 * \param[out] dst Destination stream
 * \param[in] src Source stream
 * For list of attributes see ::CUstreamAttrID
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 *
 * \sa
 * ::CUaccessPolicyWindow
 */
CUresult CUDAAPI cuStreamCopyAttributes(CUstream dst, CUstream src);

/**
 * \brief Queries stream attribute.
 *
 * Queries attribute \p attr from \p hStream and stores it in corresponding
 * member of \p value_out.
 *
 * \param[in] hStream
 * \param[in] attr
 * \param[out] value_out
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_HANDLE
 * \notefnerr
 *
 * \sa
 * ::CUaccessPolicyWindow
 */
CUresult CUDAAPI cuStreamGetAttribute(CUstream hStream, CUstreamAttrID attr,
                                      CUstreamAttrValue *value_out);

/**
 * \brief Sets stream attribute.
 *
 * Sets attribute \p attr on \p hStream from corresponding attribute of
 * \p value. The updated attribute will be applied to subsequent work
 * submitted to the stream. It will not affect previously submitted work.
 *
 * \param[out] hStream
 * \param[in] attr
 * \param[in] value
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_HANDLE
 * \notefnerr
 *
 * \sa
 * ::CUaccessPolicyWindow
 */
CUresult CUDAAPI cuStreamSetAttribute(CUstream hStream, CUstreamAttrID attr,
                                      const CUstreamAttrValue *value);

/** @} */ /* END CUDA_STREAM */


/**
 * \defgroup CUDA_EVENT Event Management
 *
 * ___MANBRIEF___ event management functions of the low-level CUDA driver API
 * (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the event management functions of the low-level CUDA
 * driver application programming interface.
 *
 * @{
 */

/**
 * \brief Creates an event
 *
 * Creates an event *phEvent for the current context with the flags specified via
 * \p Flags. Valid flags include:
 * - ::CU_EVENT_DEFAULT: Default event creation flag.
 * - ::CU_EVENT_BLOCKING_SYNC: Specifies that the created event should use blocking
 *   synchronization.  A CPU thread that uses ::cuEventSynchronize() to wait on
 *   an event created with this flag will block until the event has actually
 *   been recorded.
 * - ::CU_EVENT_DISABLE_TIMING: Specifies that the created event does not need
 *   to record timing data.  Events created with this flag specified and
 *   the ::CU_EVENT_BLOCKING_SYNC flag not specified will provide the best
 *   performance when used with ::cuStreamWaitEvent() and ::cuEventQuery().
 * - ::CU_EVENT_INTERPROCESS: Specifies that the created event may be used as an
 *   interprocess event by ::cuIpcGetEventHandle(). ::CU_EVENT_INTERPROCESS must
 *   be specified along with ::CU_EVENT_DISABLE_TIMING.
 *
 * \param phEvent - Returns newly created event
 * \param Flags   - Event creation flags
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_OUT_OF_MEMORY
 * \notefnerr
 *
 * \sa
 * ::cuEventRecord,
 * ::cuEventQuery,
 * ::cuEventSynchronize,
 * ::cuEventDestroy,
 * ::cuEventElapsedTime,
 * ::cudaEventCreate,
 * ::cudaEventCreateWithFlags
 */
CUresult CUDAAPI cuEventCreate(CUevent *phEvent, unsigned int Flags);

/**
 * \brief Records an event
 *
 * Captures in \p hEvent the contents of \p hStream at the time of this call.
 * \p hEvent and \p hStream must be from the same context otherwise
 * ::CUDA_ERROR_INVALID_HANDLE is returned.
 * Calls such as ::cuEventQuery() or ::cuStreamWaitEvent() will then
 * examine or wait for completion of the work that was captured. Uses of
 * \p hStream after this call do not modify \p hEvent. See note on default
 * stream behavior for what is captured in the default case.
 *
 * ::cuEventRecord() can be called multiple times on the same event and
 * will overwrite the previously captured state. Other APIs such as
 * ::cuStreamWaitEvent() use the most recently captured state at the time
 * of the API call, and are not affected by later calls to
 * ::cuEventRecord(). Before the first call to ::cuEventRecord(), an
 * event represents an empty set of work, so for example ::cuEventQuery()
 * would return ::CUDA_SUCCESS.
 *
 * \param hEvent  - Event to record
 * \param hStream - Stream to record event for
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_INVALID_VALUE
 * \note_null_stream
 * \notefnerr
 *
 * \sa ::cuEventCreate,
 * ::cuEventQuery,
 * ::cuEventSynchronize,
 * ::cuStreamWaitEvent,
 * ::cuEventDestroy,
 * ::cuEventElapsedTime,
 * ::cudaEventRecord,
 * ::cuEventRecordWithFlags
 */
CUresult CUDAAPI cuEventRecord(CUevent hEvent, CUstream hStream);

/**
 * \brief Records an event
 *
 * Captures in \p hEvent the contents of \p hStream at the time of this call.
 * \p hEvent and \p hStream must be from the same context otherwise
 * ::CUDA_ERROR_INVALID_HANDLE is returned.
 * Calls such as ::cuEventQuery() or ::cuStreamWaitEvent() will then
 * examine or wait for completion of the work that was captured. Uses of
 * \p hStream after this call do not modify \p hEvent. See note on default
 * stream behavior for what is captured in the default case.
 *
 * ::cuEventRecordWithFlags() can be called multiple times on the same event and
 * will overwrite the previously captured state. Other APIs such as
 * ::cuStreamWaitEvent() use the most recently captured state at the time
 * of the API call, and are not affected by later calls to
 * ::cuEventRecordWithFlags(). Before the first call to ::cuEventRecordWithFlags(), an
 * event represents an empty set of work, so for example ::cuEventQuery()
 * would return ::CUDA_SUCCESS.
 *
 * flags include:
 * - ::CU_EVENT_RECORD_DEFAULT: Default event creation flag.
 * - ::CU_EVENT_RECORD_EXTERNAL: Event is captured in the graph as an external
 *   event node when performing stream capture. This flag is invalid outside
 *   of stream capture.
 *
 * \param hEvent  - Event to record
 * \param hStream - Stream to record event for
 * \param flags   - See ::CUevent_capture_flags
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_INVALID_VALUE
 * \note_null_stream
 * \notefnerr
 *
 * \sa ::cuEventCreate,
 * ::cuEventQuery,
 * ::cuEventSynchronize,
 * ::cuStreamWaitEvent,
 * ::cuEventDestroy,
 * ::cuEventElapsedTime,
 * ::cuEventRecord,
 * ::cudaEventRecord
 */
CUresult CUDAAPI cuEventRecordWithFlags(CUevent hEvent, CUstream hStream, unsigned int flags);

/**
 * \brief Queries an event's status
 *
 * Queries the status of all work currently captured by \p hEvent. See
 * ::cuEventRecord() for details on what is captured by an event.
 *
 * Returns ::CUDA_SUCCESS if all captured work has been completed, or
 * ::CUDA_ERROR_NOT_READY if any captured work is incomplete.
 *
 * For the purposes of Unified Memory, a return value of ::CUDA_SUCCESS
 * is equivalent to having called ::cuEventSynchronize().
 *
 * \param hEvent - Event to query
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_NOT_READY
 * \notefnerr
 *
 * \sa ::cuEventCreate,
 * ::cuEventRecord,
 * ::cuEventSynchronize,
 * ::cuEventDestroy,
 * ::cuEventElapsedTime,
 * ::cudaEventQuery
 */
CUresult CUDAAPI cuEventQuery(CUevent hEvent);

/**
 * \brief Waits for an event to complete
 *
 * Waits until the completion of all work currently captured in \p hEvent.
 * See ::cuEventRecord() for details on what is captured by an event.
 *
 * Waiting for an event that was created with the ::CU_EVENT_BLOCKING_SYNC
 * flag will cause the calling CPU thread to block until the event has
 * been completed by the device.  If the ::CU_EVENT_BLOCKING_SYNC flag has
 * not been set, then the CPU thread will busy-wait until the event has
 * been completed by the device.
 *
 * \param hEvent - Event to wait for
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_HANDLE
 * \notefnerr
 *
 * \sa ::cuEventCreate,
 * ::cuEventRecord,
 * ::cuEventQuery,
 * ::cuEventDestroy,
 * ::cuEventElapsedTime,
 * ::cudaEventSynchronize
 */
CUresult CUDAAPI cuEventSynchronize(CUevent hEvent);

/**
 * \brief Destroys an event
 *
 * Destroys the event specified by \p hEvent.
 *
 * An event may be destroyed before it is complete (i.e., while
 * ::cuEventQuery() would return ::CUDA_ERROR_NOT_READY). In this case, the
 * call does not block on completion of the event, and any associated
 * resources will automatically be released asynchronously at completion.
 *
 * \param hEvent - Event to destroy
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_HANDLE
 * \notefnerr
 *
 * \sa ::cuEventCreate,
 * ::cuEventRecord,
 * ::cuEventQuery,
 * ::cuEventSynchronize,
 * ::cuEventElapsedTime,
 * ::cudaEventDestroy
 */
CUresult CUDAAPI cuEventDestroy(CUevent hEvent);

/**
 * \brief Computes the elapsed time between two events
 *
 * Computes the elapsed time between two events (in milliseconds with a
 * resolution of around 0.5 microseconds).
 *
 * If either event was last recorded in a non-NULL stream, the resulting time
 * may be greater than expected (even if both used the same stream handle). This
 * happens because the ::cuEventRecord() operation takes place asynchronously
 * and there is no guarantee that the measured latency is actually just between
 * the two events. Any number of other different stream operations could execute
 * in between the two measured events, thus altering the timing in a significant
 * way.
 *
 * If ::cuEventRecord() has not been called on either event then
 * ::CUDA_ERROR_INVALID_HANDLE is returned. If ::cuEventRecord() has been called
 * on both events but one or both of them has not yet been completed (that is,
 * ::cuEventQuery() would return ::CUDA_ERROR_NOT_READY on at least one of the
 * events), ::CUDA_ERROR_NOT_READY is returned. If either event was created with
 * the ::CU_EVENT_DISABLE_TIMING flag, then this function will return
 * ::CUDA_ERROR_INVALID_HANDLE.
 * 
 * Note there is a later version of this API, ::cuEventElapsedTime_v2. It will
 * supplant this version in CUDA 13.0, which is retained for minor version compatibility.
 *
 * \param pMilliseconds - Time between \p hStart and \p hEnd in ms
 * \param hStart        - Starting event
 * \param hEnd          - Ending event
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_NOT_READY,
 * ::CUDA_ERROR_UNKNOWN
 * \notefnerr
 *
 * \sa ::cuEventCreate,
 * ::cuEventRecord,
 * ::cuEventQuery,
 * ::cuEventSynchronize,
 * ::cuEventDestroy,
 * ::cudaEventElapsedTime
 */
CUresult CUDAAPI cuEventElapsedTime(float *pMilliseconds, CUevent hStart, CUevent hEnd);

/**
 * \brief Computes the elapsed time between two events
 *
 * Computes the elapsed time between two events (in milliseconds with a
 * resolution of around 0.5 microseconds). Note this API is not guaranteed
 * to return the latest errors for pending work. As such this API is intended to
 * serve as an elapsed time calculation only and any polling for completion on the
 * events to be compared should be done with ::cuEventQuery instead.
 *
 * If either event was last recorded in a non-NULL stream, the resulting time
 * may be greater than expected (even if both used the same stream handle). This
 * happens because the ::cuEventRecord() operation takes place asynchronously
 * and there is no guarantee that the measured latency is actually just between
 * the two events. Any number of other different stream operations could execute
 * in between the two measured events, thus altering the timing in a significant
 * way.
 *
 * If ::cuEventRecord() has not been called on either event then
 * ::CUDA_ERROR_INVALID_HANDLE is returned. If ::cuEventRecord() has been called
 * on both events but one or both of them has not yet been completed (that is,
 * ::cuEventQuery() would return ::CUDA_ERROR_NOT_READY on at least one of the
 * events), ::CUDA_ERROR_NOT_READY is returned. If either event was created with
 * the ::CU_EVENT_DISABLE_TIMING flag, then this function will return
 * ::CUDA_ERROR_INVALID_HANDLE.
 *
 * \param pMilliseconds - Time between \p hStart and \p hEnd in ms
 * \param hStart        - Starting event
 * \param hEnd          - Ending event
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_NOT_READY,
 * ::CUDA_ERROR_UNKNOWN
 * \notefnerr
 *
 * \sa ::cuEventCreate,
 * ::cuEventRecord,
 * ::cuEventQuery,
 * ::cuEventSynchronize,
 * ::cuEventDestroy,
 * ::cudaEventElapsedTime
 */
CUresult CUDAAPI cuEventElapsedTime_v2(float *pMilliseconds, CUevent hStart, CUevent hEnd);

/** @} */ /* END CUDA_EVENT */

/**
 * \defgroup CUDA_EXTRES_INTEROP External Resource Interoperability
 *
 * ___MANBRIEF___ External resource interoperability functions of the low-level CUDA driver API
 * (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the external resource interoperability functions of the low-level CUDA
 * driver application programming interface.
 *
 * @{
 */

 /**
 * \brief Imports an external memory object
 *
 * Imports an externally allocated memory object and returns
 * a handle to that in \p extMem_out.
 *
 * The properties of the handle being imported must be described in
 * \p memHandleDesc. The ::CUDA_EXTERNAL_MEMORY_HANDLE_DESC structure
 * is defined as follows:
 *
 * \code
        typedef struct CUDA_EXTERNAL_MEMORY_HANDLE_DESC_st {
            CUexternalMemoryHandleType type;
            union {
                int fd;
                struct {
                    void *handle;
                    const void *name;
                } win32;
                const void *nvSciBufObject;
            } handle;
            unsigned long long size;
            unsigned int flags;
        } CUDA_EXTERNAL_MEMORY_HANDLE_DESC;
 * \endcode
 *
 * where ::CUDA_EXTERNAL_MEMORY_HANDLE_DESC::type specifies the type
 * of handle being imported. ::CUexternalMemoryHandleType is
 * defined as:
 *
 * \code
        typedef enum CUexternalMemoryHandleType_enum {
            CU_EXTERNAL_MEMORY_HANDLE_TYPE_OPAQUE_FD          = 1,
            CU_EXTERNAL_MEMORY_HANDLE_TYPE_OPAQUE_WIN32       = 2,
            CU_EXTERNAL_MEMORY_HANDLE_TYPE_OPAQUE_WIN32_KMT   = 3,
            CU_EXTERNAL_MEMORY_HANDLE_TYPE_D3D12_HEAP         = 4,
            CU_EXTERNAL_MEMORY_HANDLE_TYPE_D3D12_RESOURCE     = 5,
            CU_EXTERNAL_MEMORY_HANDLE_TYPE_D3D11_RESOURCE     = 6,
            CU_EXTERNAL_MEMORY_HANDLE_TYPE_D3D11_RESOURCE_KMT = 7,
            CU_EXTERNAL_MEMORY_HANDLE_TYPE_NVSCIBUF           = 8,
        } CUexternalMemoryHandleType;
 * \endcode
 *
 * If ::CUDA_EXTERNAL_MEMORY_HANDLE_DESC::type is
 * ::CU_EXTERNAL_MEMORY_HANDLE_TYPE_OPAQUE_FD, then
 * ::CUDA_EXTERNAL_MEMORY_HANDLE_DESC::handle::fd must be a valid
 * file descriptor referencing a memory object. Ownership of
 * the file descriptor is transferred to the CUDA driver when the
 * handle is imported successfully. Performing any operations on the
 * file descriptor after it is imported results in undefined behavior.
 *
 * If ::CUDA_EXTERNAL_MEMORY_HANDLE_DESC::type is
 * ::CU_EXTERNAL_MEMORY_HANDLE_TYPE_OPAQUE_WIN32, then exactly one
 * of ::CUDA_EXTERNAL_MEMORY_HANDLE_DESC::handle::win32::handle and
 * ::CUDA_EXTERNAL_MEMORY_HANDLE_DESC::handle::win32::name must not be
 * NULL. If ::CUDA_EXTERNAL_MEMORY_HANDLE_DESC::handle::win32::handle
 * is not NULL, then it must represent a valid shared NT handle that
 * references a memory object. Ownership of this handle is
 * not transferred to CUDA after the import operation, so the
 * application must release the handle using the appropriate system
 * call. If ::CUDA_EXTERNAL_MEMORY_HANDLE_DESC::handle::win32::name
 * is not NULL, then it must point to a NULL-terminated array of
 * UTF-16 characters that refers to a memory object.
 *
 * If ::CUDA_EXTERNAL_MEMORY_HANDLE_DESC::type is
 * ::CU_EXTERNAL_MEMORY_HANDLE_TYPE_OPAQUE_WIN32_KMT, then
 * ::CUDA_EXTERNAL_MEMORY_HANDLE_DESC::handle::win32::handle must
 * be non-NULL and
 * ::CUDA_EXTERNAL_MEMORY_HANDLE_DESC::handle::win32::name
 * must be NULL. The handle specified must be a globally shared KMT
 * handle. This handle does not hold a reference to the underlying
 * object, and thus will be invalid when all references to the
 * memory object are destroyed.
 *
 * If ::CUDA_EXTERNAL_MEMORY_HANDLE_DESC::type is
 * ::CU_EXTERNAL_MEMORY_HANDLE_TYPE_D3D12_HEAP, then exactly one
 * of ::CUDA_EXTERNAL_MEMORY_HANDLE_DESC::handle::win32::handle and
 * ::CUDA_EXTERNAL_MEMORY_HANDLE_DESC::handle::win32::name must not be
 * NULL. If ::CUDA_EXTERNAL_MEMORY_HANDLE_DESC::handle::win32::handle
 * is not NULL, then it must represent a valid shared NT handle that
 * is returned by ID3D12Device::CreateSharedHandle when referring to a
 * ID3D12Heap object. This handle holds a reference to the underlying
 * object. If ::CUDA_EXTERNAL_MEMORY_HANDLE_DESC::handle::win32::name
 * is not NULL, then it must point to a NULL-terminated array of
 * UTF-16 characters that refers to a ID3D12Heap object.
 *
 * If ::CUDA_EXTERNAL_MEMORY_HANDLE_DESC::type is
 * ::CU_EXTERNAL_MEMORY_HANDLE_TYPE_D3D12_RESOURCE, then exactly one
 * of ::CUDA_EXTERNAL_MEMORY_HANDLE_DESC::handle::win32::handle and
 * ::CUDA_EXTERNAL_MEMORY_HANDLE_DESC::handle::win32::name must not be
 * NULL. If ::CUDA_EXTERNAL_MEMORY_HANDLE_DESC::handle::win32::handle
 * is not NULL, then it must represent a valid shared NT handle that
 * is returned by ID3D12Device::CreateSharedHandle when referring to a
 * ID3D12Resource object. This handle holds a reference to the
 * underlying object. If
 * ::CUDA_EXTERNAL_MEMORY_HANDLE_DESC::handle::win32::name
 * is not NULL, then it must point to a NULL-terminated array of
 * UTF-16 characters that refers to a ID3D12Resource object.
 *
 * If ::CUDA_EXTERNAL_MEMORY_HANDLE_DESC::type is
 * ::CU_EXTERNAL_MEMORY_HANDLE_TYPE_D3D11_RESOURCE, then
 * ::CUDA_EXTERNAL_MEMORY_HANDLE_DESC::handle::win32::handle must
 * represent a valid shared NT handle that is returned by
 * IDXGIResource1::CreateSharedHandle when referring to a
 * ID3D11Resource object. If
 * ::CUDA_EXTERNAL_MEMORY_HANDLE_DESC::handle::win32::name
 * is not NULL, then it must point to a NULL-terminated array of
 * UTF-16 characters that refers to a ID3D11Resource object.
 *
 * If ::CUDA_EXTERNAL_MEMORY_HANDLE_DESC::type is
 * ::CU_EXTERNAL_MEMORY_HANDLE_TYPE_D3D11_RESOURCE_KMT, then
 * ::CUDA_EXTERNAL_MEMORY_HANDLE_DESC::handle::win32::handle must
 * represent a valid shared KMT handle that is returned by
 * IDXGIResource::GetSharedHandle when referring to a
 * ID3D11Resource object and
 * ::CUDA_EXTERNAL_MEMORY_HANDLE_DESC::handle::win32::name
 * must be NULL.
 *
 * If ::CUDA_EXTERNAL_MEMORY_HANDLE_DESC::type is
 * ::CU_EXTERNAL_MEMORY_HANDLE_TYPE_NVSCIBUF, then
 * ::CUDA_EXTERNAL_MEMORY_HANDLE_DESC::handle::nvSciBufObject must be non-NULL
 * and reference a valid NvSciBuf object.
 * If the NvSciBuf object imported into CUDA is also mapped by other drivers, then the
 * application must use ::cuWaitExternalSemaphoresAsync or ::cuSignalExternalSemaphoresAsync
 * as appropriate barriers to maintain coherence between CUDA and the other drivers.
 * See ::CUDA_EXTERNAL_SEMAPHORE_SIGNAL_SKIP_NVSCIBUF_MEMSYNC and ::CUDA_EXTERNAL_SEMAPHORE_WAIT_SKIP_NVSCIBUF_MEMSYNC
 * for memory synchronization.
 *
 *
 * The size of the memory object must be specified in
 * ::CUDA_EXTERNAL_MEMORY_HANDLE_DESC::size.
 *
 * Specifying the flag ::CUDA_EXTERNAL_MEMORY_DEDICATED in
 * ::CUDA_EXTERNAL_MEMORY_HANDLE_DESC::flags indicates that the
 * resource is a dedicated resource. The definition of what a
 * dedicated resource is outside the scope of this extension.
 * This flag must be set if ::CUDA_EXTERNAL_MEMORY_HANDLE_DESC::type
 * is one of the following:
 * ::CU_EXTERNAL_MEMORY_HANDLE_TYPE_D3D12_RESOURCE
 * ::CU_EXTERNAL_MEMORY_HANDLE_TYPE_D3D11_RESOURCE
 * ::CU_EXTERNAL_MEMORY_HANDLE_TYPE_D3D11_RESOURCE_KMT
 *
 * \param extMem_out    - Returned handle to an external memory object
 * \param memHandleDesc - Memory import handle descriptor
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_OPERATING_SYSTEM
 * \notefnerr
 *
 * \note If the Vulkan memory imported into CUDA is mapped on the CPU then the
 * application must use vkInvalidateMappedMemoryRanges/vkFlushMappedMemoryRanges
 * as well as appropriate Vulkan pipeline barriers to maintain coherence between
 * CPU and GPU. For more information on these APIs, please refer to "Synchronization
 * and Cache Control" chapter from Vulkan specification.
 *
 * \sa ::cuDestroyExternalMemory,
 * ::cuExternalMemoryGetMappedBuffer,
 * ::cuExternalMemoryGetMappedMipmappedArray
 */
CUresult CUDAAPI cuImportExternalMemory(CUexternalMemory *extMem_out, const CUDA_EXTERNAL_MEMORY_HANDLE_DESC *memHandleDesc);

/**
 * \brief Maps a buffer onto an imported memory object
 *
 * Maps a buffer onto an imported memory object and returns a device
 * pointer in \p devPtr.
 *
 * The properties of the buffer being mapped must be described in
 * \p bufferDesc. The ::CUDA_EXTERNAL_MEMORY_BUFFER_DESC structure is
 * defined as follows:
 *
 * \code
        typedef struct CUDA_EXTERNAL_MEMORY_BUFFER_DESC_st {
            unsigned long long offset;
            unsigned long long size;
            unsigned int flags;
        } CUDA_EXTERNAL_MEMORY_BUFFER_DESC;
 * \endcode
 *
 * where ::CUDA_EXTERNAL_MEMORY_BUFFER_DESC::offset is the offset in
 * the memory object where the buffer's base address is.
 * ::CUDA_EXTERNAL_MEMORY_BUFFER_DESC::size is the size of the buffer.
 * ::CUDA_EXTERNAL_MEMORY_BUFFER_DESC::flags must be zero.
 *
 * The offset and size have to be suitably aligned to match the
 * requirements of the external API. Mapping two buffers whose ranges
 * overlap may or may not result in the same virtual address being
 * returned for the overlapped portion. In such cases, the application
 * must ensure that all accesses to that region from the GPU are
 * volatile. Otherwise writes made via one address are not guaranteed
 * to be visible via the other address, even if they're issued by the
 * same thread. It is recommended that applications map the combined
 * range instead of mapping separate buffers and then apply the
 * appropriate offsets to the returned pointer to derive the
 * individual buffers.
 *
 * The returned pointer \p devPtr must be freed using ::cuMemFree.
 *
 * \param devPtr     - Returned device pointer to buffer
 * \param extMem     - Handle to external memory object
 * \param bufferDesc - Buffer descriptor
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_HANDLE
 * \notefnerr
 *
 * \sa ::cuImportExternalMemory,
 * ::cuDestroyExternalMemory,
 * ::cuExternalMemoryGetMappedMipmappedArray
 */
CUresult CUDAAPI cuExternalMemoryGetMappedBuffer(CUdeviceptr *devPtr, CUexternalMemory extMem, const CUDA_EXTERNAL_MEMORY_BUFFER_DESC *bufferDesc);

/**
 * \brief Maps a CUDA mipmapped array onto an external memory object
 *
 * Maps a CUDA mipmapped array onto an external object and returns a
 * handle to it in \p mipmap.
 *
 * The properties of the CUDA mipmapped array being mapped must be
 * described in \p mipmapDesc. The structure
 * ::CUDA_EXTERNAL_MEMORY_MIPMAPPED_ARRAY_DESC is defined as follows:
 *
 * \code
        typedef struct CUDA_EXTERNAL_MEMORY_MIPMAPPED_ARRAY_DESC_st {
            unsigned long long offset;
            CUDA_ARRAY3D_DESCRIPTOR arrayDesc;
            unsigned int numLevels;
        } CUDA_EXTERNAL_MEMORY_MIPMAPPED_ARRAY_DESC;
 * \endcode
 *
 * where ::CUDA_EXTERNAL_MEMORY_MIPMAPPED_ARRAY_DESC::offset is the
 * offset in the memory object where the base level of the mipmap
 * chain is.
 * ::CUDA_EXTERNAL_MEMORY_MIPMAPPED_ARRAY_DESC::arrayDesc describes
 * the format, dimensions and type of the base level of the mipmap
 * chain. For further details on these parameters, please refer to the
 * documentation for ::cuMipmappedArrayCreate. Note that if the mipmapped
 * array is bound as a color target in the graphics API, then the flag
 * ::CUDA_ARRAY3D_COLOR_ATTACHMENT must be specified in
 * ::CUDA_EXTERNAL_MEMORY_MIPMAPPED_ARRAY_DESC::arrayDesc::Flags.
 * ::CUDA_EXTERNAL_MEMORY_MIPMAPPED_ARRAY_DESC::numLevels specifies
 * the total number of levels in the mipmap chain.
 *
 * If \p extMem was imported from a handle of type ::CU_EXTERNAL_MEMORY_HANDLE_TYPE_NVSCIBUF, then
 * ::CUDA_EXTERNAL_MEMORY_MIPMAPPED_ARRAY_DESC::numLevels must be equal to 1.
 *
 *
 * The returned CUDA mipmapped array must be freed using ::cuMipmappedArrayDestroy.
 *
 * \param mipmap     - Returned CUDA mipmapped array
 * \param extMem     - Handle to external memory object
 * \param mipmapDesc - CUDA array descriptor
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_HANDLE
 * \notefnerr
 *
 * \sa ::cuImportExternalMemory,
 * ::cuDestroyExternalMemory,
 * ::cuExternalMemoryGetMappedBuffer
 */
CUresult CUDAAPI cuExternalMemoryGetMappedMipmappedArray(CUmipmappedArray *mipmap, CUexternalMemory extMem, const CUDA_EXTERNAL_MEMORY_MIPMAPPED_ARRAY_DESC *mipmapDesc);

/**
 * \brief Destroys an external memory object.
 *
 * Destroys the specified external memory object. Any existing buffers
 * and CUDA mipmapped arrays mapped onto this object must no longer be
 * used and must be explicitly freed using ::cuMemFree and
 * ::cuMipmappedArrayDestroy respectively.
 *
 * \param extMem - External memory object to be destroyed
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_HANDLE
 * \notefnerr
 *
 * \sa ::cuImportExternalMemory,
 * ::cuExternalMemoryGetMappedBuffer,
 * ::cuExternalMemoryGetMappedMipmappedArray
 */
CUresult CUDAAPI cuDestroyExternalMemory(CUexternalMemory extMem);

/**
 * \brief Imports an external semaphore
 *
 * Imports an externally allocated synchronization object and returns
 * a handle to that in \p extSem_out.
 *
 * The properties of the handle being imported must be described in
 * \p semHandleDesc. The ::CUDA_EXTERNAL_SEMAPHORE_HANDLE_DESC is
 * defined as follows:
 *
 * \code
        typedef struct CUDA_EXTERNAL_SEMAPHORE_HANDLE_DESC_st {
            CUexternalSemaphoreHandleType type;
            union {
                int fd;
                struct {
                    void *handle;
                    const void *name;
                } win32;
                const void* NvSciSyncObj;
            } handle;
            unsigned int flags;
        } CUDA_EXTERNAL_SEMAPHORE_HANDLE_DESC;
 * \endcode
 *
 * where ::CUDA_EXTERNAL_SEMAPHORE_HANDLE_DESC::type specifies the type of
 * handle being imported. ::CUexternalSemaphoreHandleType is defined
 * as:
 *
 * \code
        typedef enum CUexternalSemaphoreHandleType_enum {
            CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_OPAQUE_FD                = 1,
            CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_OPAQUE_WIN32             = 2,
            CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_OPAQUE_WIN32_KMT         = 3,
            CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_D3D12_FENCE              = 4,
            CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_D3D11_FENCE              = 5,
            CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_NVSCISYNC                = 6,
            CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_D3D11_KEYED_MUTEX        = 7,
            CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_D3D11_KEYED_MUTEX_KMT    = 8,
            CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_TIMELINE_SEMAPHORE_FD    = 9,
            CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_TIMELINE_SEMAPHORE_WIN32 = 10
        } CUexternalSemaphoreHandleType;
 * \endcode
 *
 * If ::CUDA_EXTERNAL_SEMAPHORE_HANDLE_DESC::type is
 * ::CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_OPAQUE_FD, then
 * ::CUDA_EXTERNAL_SEMAPHORE_HANDLE_DESC::handle::fd must be a valid
 * file descriptor referencing a synchronization object. Ownership of
 * the file descriptor is transferred to the CUDA driver when the
 * handle is imported successfully. Performing any operations on the
 * file descriptor after it is imported results in undefined behavior.
 *
 * If ::CUDA_EXTERNAL_SEMAPHORE_HANDLE_DESC::type is
 * ::CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_OPAQUE_WIN32, then exactly one
 * of ::CUDA_EXTERNAL_SEMAPHORE_HANDLE_DESC::handle::win32::handle and
 * ::CUDA_EXTERNAL_SEMAPHORE_HANDLE_DESC::handle::win32::name must not be
 * NULL. If
 * ::CUDA_EXTERNAL_SEMAPHORE_HANDLE_DESC::handle::win32::handle
 * is not NULL, then it must represent a valid shared NT handle that
 * references a synchronization object. Ownership of this handle is
 * not transferred to CUDA after the import operation, so the
 * application must release the handle using the appropriate system
 * call. If ::CUDA_EXTERNAL_SEMAPHORE_HANDLE_DESC::handle::win32::name
 * is not NULL, then it must name a valid synchronization object.
 *
 * If ::CUDA_EXTERNAL_SEMAPHORE_HANDLE_DESC::type is
 * ::CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_OPAQUE_WIN32_KMT, then
 * ::CUDA_EXTERNAL_SEMAPHORE_HANDLE_DESC::handle::win32::handle must
 * be non-NULL and
 * ::CUDA_EXTERNAL_SEMAPHORE_HANDLE_DESC::handle::win32::name
 * must be NULL. The handle specified must be a globally shared KMT
 * handle. This handle does not hold a reference to the underlying
 * object, and thus will be invalid when all references to the
 * synchronization object are destroyed.
 *
 * If ::CUDA_EXTERNAL_SEMAPHORE_HANDLE_DESC::type is
 * ::CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_D3D12_FENCE, then exactly one
 * of ::CUDA_EXTERNAL_SEMAPHORE_HANDLE_DESC::handle::win32::handle and
 * ::CUDA_EXTERNAL_SEMAPHORE_HANDLE_DESC::handle::win32::name must not be
 * NULL. If
 * ::CUDA_EXTERNAL_SEMAPHORE_HANDLE_DESC::handle::win32::handle
 * is not NULL, then it must represent a valid shared NT handle that
 * is returned by ID3D12Device::CreateSharedHandle when referring to a
 * ID3D12Fence object. This handle holds a reference to the underlying
 * object. If
 * ::CUDA_EXTERNAL_SEMAPHORE_HANDLE_DESC::handle::win32::name
 * is not NULL, then it must name a valid synchronization object that
 * refers to a valid ID3D12Fence object.
 *
 * If ::CUDA_EXTERNAL_SEMAPHORE_HANDLE_DESC::type is
 * ::CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_D3D11_FENCE, then
 * ::CUDA_EXTERNAL_SEMAPHORE_HANDLE_DESC::handle::win32::handle
 * represents a valid shared NT handle that is returned by
 * ID3D11Fence::CreateSharedHandle. If
 * ::CUDA_EXTERNAL_SEMAPHORE_HANDLE_DESC::handle::win32::name
 * is not NULL, then it must name a valid synchronization object that
 * refers to a valid ID3D11Fence object.
 *
 * If ::CUDA_EXTERNAL_SEMAPHORE_HANDLE_DESC::type is
 * ::CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_NVSCISYNC, then
 * ::CUDA_EXTERNAL_SEMAPHORE_HANDLE_DESC::handle::nvSciSyncObj
 * represents a valid NvSciSyncObj.
 *
 * ::CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_D3D11_KEYED_MUTEX, then
 * ::CUDA_EXTERNAL_SEMAPHORE_HANDLE_DESC::handle::win32::handle
 * represents a valid shared NT handle that
 * is returned by IDXGIResource1::CreateSharedHandle when referring to
 * a IDXGIKeyedMutex object. If
 * ::CUDA_EXTERNAL_SEMAPHORE_HANDLE_DESC::handle::win32::name
 * is not NULL, then it must name a valid synchronization object that
 * refers to a valid IDXGIKeyedMutex object.
 *
 * If ::CUDA_EXTERNAL_SEMAPHORE_HANDLE_DESC::type is
 * ::CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_D3D11_KEYED_MUTEX_KMT, then
 * ::CUDA_EXTERNAL_SEMAPHORE_HANDLE_DESC::handle::win32::handle
 * represents a valid shared KMT handle that
 * is returned by IDXGIResource::GetSharedHandle when referring to
 * a IDXGIKeyedMutex object and
 * ::CUDA_EXTERNAL_SEMAPHORE_HANDLE_DESC::handle::win32::name must be NULL.
 * 
 * If ::CUDA_EXTERNAL_SEMAPHORE_HANDLE_DESC::type is
 * ::CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_TIMELINE_SEMAPHORE_FD, then
 * ::CUDA_EXTERNAL_SEMAPHORE_HANDLE_DESC::handle::fd must be a valid
 * file descriptor referencing a synchronization object. Ownership of
 * the file descriptor is transferred to the CUDA driver when the
 * handle is imported successfully. Performing any operations on the
 * file descriptor after it is imported results in undefined behavior.
 * 
 * If ::CUDA_EXTERNAL_SEMAPHORE_HANDLE_DESC::type is
 * ::CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_TIMELINE_SEMAPHORE_WIN32, then exactly one
 * of ::CUDA_EXTERNAL_SEMAPHORE_HANDLE_DESC::handle::win32::handle and
 * ::CUDA_EXTERNAL_SEMAPHORE_HANDLE_DESC::handle::win32::name must not be
 * NULL. If
 * ::CUDA_EXTERNAL_SEMAPHORE_HANDLE_DESC::handle::win32::handle
 * is not NULL, then it must represent a valid shared NT handle that
 * references a synchronization object. Ownership of this handle is
 * not transferred to CUDA after the import operation, so the
 * application must release the handle using the appropriate system
 * call. If ::CUDA_EXTERNAL_SEMAPHORE_HANDLE_DESC::handle::win32::name
 * is not NULL, then it must name a valid synchronization object.
 *
 * \param extSem_out    - Returned handle to an external semaphore
 * \param semHandleDesc - Semaphore import handle descriptor
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_NOT_SUPPORTED,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_OPERATING_SYSTEM
 * \notefnerr
 *
 * \sa ::cuDestroyExternalSemaphore,
 * ::cuSignalExternalSemaphoresAsync,
 * ::cuWaitExternalSemaphoresAsync
 */
CUresult CUDAAPI cuImportExternalSemaphore(CUexternalSemaphore *extSem_out, const CUDA_EXTERNAL_SEMAPHORE_HANDLE_DESC *semHandleDesc);

/**
 * \brief Signals a set of external semaphore objects
 *
 * Enqueues a signal operation on a set of externally allocated
 * semaphore object in the specified stream. The operations will be
 * executed when all prior operations in the stream complete.
 *
 * The exact semantics of signaling a semaphore depends on the type of
 * the object.
 *
 * If the semaphore object is any one of the following types:
 * ::CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_OPAQUE_FD,
 * ::CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_OPAQUE_WIN32,
 * ::CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_OPAQUE_WIN32_KMT
 * then signaling the semaphore will set it to the signaled state.
 *
 * If the semaphore object is any one of the following types:
 * ::CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_D3D12_FENCE,
 * ::CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_D3D11_FENCE,
 * ::CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_TIMELINE_SEMAPHORE_FD,
 * ::CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_TIMELINE_SEMAPHORE_WIN32
 * then the semaphore will be set to the value specified in
 * ::CUDA_EXTERNAL_SEMAPHORE_SIGNAL_PARAMS::params::fence::value.
 *
 * If the semaphore object is of the type ::CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_NVSCISYNC
 * this API sets ::CUDA_EXTERNAL_SEMAPHORE_SIGNAL_PARAMS::params::nvSciSync::fence
 * to a value that can be used by subsequent waiters of the same NvSciSync object
 * to order operations with those currently submitted in \p stream. Such an update
 * will overwrite previous contents of
 * ::CUDA_EXTERNAL_SEMAPHORE_SIGNAL_PARAMS::params::nvSciSync::fence. By default,
 * signaling such an external semaphore object causes appropriate memory synchronization
 * operations to be performed over all external memory objects that are imported as
 * ::CU_EXTERNAL_MEMORY_HANDLE_TYPE_NVSCIBUF. This ensures that any subsequent accesses
 * made by other importers of the same set of NvSciBuf memory object(s) are coherent.
 * These operations can be skipped by specifying the flag
 * ::CUDA_EXTERNAL_SEMAPHORE_SIGNAL_SKIP_NVSCIBUF_MEMSYNC, which can be used as a
 * performance optimization when data coherency is not required. But specifying this
 * flag in scenarios where data coherency is required results in undefined behavior.
 * Also, for semaphore object of the type ::CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_NVSCISYNC,
 * if the NvSciSyncAttrList used to create the NvSciSyncObj had not set the flags in
 * ::cuDeviceGetNvSciSyncAttributes to CUDA_NVSCISYNC_ATTR_SIGNAL, this API will return
 * CUDA_ERROR_NOT_SUPPORTED.
 * NvSciSyncFence associated with semaphore object of the type 
 * ::CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_NVSCISYNC can be deterministic. For this the 
 * NvSciSyncAttrList used to create the semaphore object must have value of 
 * NvSciSyncAttrKey_RequireDeterministicFences key set to true. Deterministic fences 
 * allow users to enqueue a wait over the semaphore object even before corresponding
 * signal is enqueued. For such a semaphore object, CUDA guarantees that each signal 
 * operation will increment the fence value by '1'. Users are expected to track count 
 * of signals enqueued on the semaphore object and insert waits accordingly. When such 
 * a semaphore object is signaled from multiple streams, due to concurrent stream 
 * execution, it is possible that the order in which the semaphore gets signaled is 
 * indeterministic. This could lead to waiters of the semaphore getting unblocked 
 * incorrectly. Users are expected to handle such situations, either by not using the 
 * same semaphore object with deterministic fence support enabled in different streams 
 * or by adding explicit dependency amongst such streams so that the semaphore is 
 * signaled in order.
 *
 * If the semaphore object is any one of the following types:
 * ::CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_D3D11_KEYED_MUTEX,
 * ::CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_D3D11_KEYED_MUTEX_KMT
 * then the keyed mutex will be released with the key specified in
 * ::CUDA_EXTERNAL_SEMAPHORE_PARAMS::params::keyedmutex::key.
 *
 * \param extSemArray - Set of external semaphores to be signaled
 * \param paramsArray - Array of semaphore parameters
 * \param numExtSems  - Number of semaphores to signal
 * \param stream      - Stream to enqueue the signal operations in
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_NOT_SUPPORTED
 * \notefnerr
 *
 * \sa ::cuImportExternalSemaphore,
 * ::cuDestroyExternalSemaphore,
 * ::cuWaitExternalSemaphoresAsync
 */
CUresult CUDAAPI cuSignalExternalSemaphoresAsync(const CUexternalSemaphore *extSemArray, const CUDA_EXTERNAL_SEMAPHORE_SIGNAL_PARAMS *paramsArray, unsigned int numExtSems, CUstream stream);

/**
 * \brief Waits on a set of external semaphore objects
 *
 * Enqueues a wait operation on a set of externally allocated
 * semaphore object in the specified stream. The operations will be
 * executed when all prior operations in the stream complete.
 *
 * The exact semantics of waiting on a semaphore depends on the type
 * of the object.
 *
 * If the semaphore object is any one of the following types:
 * ::CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_OPAQUE_FD,
 * ::CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_OPAQUE_WIN32,
 * ::CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_OPAQUE_WIN32_KMT
 * then waiting on the semaphore will wait until the semaphore reaches
 * the signaled state. The semaphore will then be reset to the
 * unsignaled state. Therefore for every signal operation, there can
 * only be one wait operation.
 *
 * If the semaphore object is any one of the following types:
 * ::CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_D3D12_FENCE,
 * ::CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_D3D11_FENCE,
 * ::CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_TIMELINE_SEMAPHORE_FD,
 * ::CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_TIMELINE_SEMAPHORE_WIN32
 * then waiting on the semaphore will wait until the value of the
 * semaphore is greater than or equal to
 * ::CUDA_EXTERNAL_SEMAPHORE_WAIT_PARAMS::params::fence::value.
 *
 * If the semaphore object is of the type ::CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_NVSCISYNC
 * then, waiting on the semaphore will wait until the
 * ::CUDA_EXTERNAL_SEMAPHORE_SIGNAL_PARAMS::params::nvSciSync::fence is signaled by the
 * signaler of the NvSciSyncObj that was associated with this semaphore object.
 * By default, waiting on such an external semaphore object causes appropriate
 * memory synchronization operations to be performed over all external memory objects
 * that are imported as ::CU_EXTERNAL_MEMORY_HANDLE_TYPE_NVSCIBUF. This ensures that
 * any subsequent accesses made by other importers of the same set of NvSciBuf memory
 * object(s) are coherent. These operations can be skipped by specifying the flag
 * ::CUDA_EXTERNAL_SEMAPHORE_WAIT_SKIP_NVSCIBUF_MEMSYNC, which can be used as a
 * performance optimization when data coherency is not required. But specifying this
 * flag in scenarios where data coherency is required results in undefined behavior.
 * Also, for semaphore object of the type ::CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_NVSCISYNC,
 * if the NvSciSyncAttrList used to create the NvSciSyncObj had not set the flags in
 * ::cuDeviceGetNvSciSyncAttributes to CUDA_NVSCISYNC_ATTR_WAIT, this API will return
 * CUDA_ERROR_NOT_SUPPORTED.
 *
 * If the semaphore object is any one of the following types:
 * ::CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_D3D11_KEYED_MUTEX,
 * ::CU_EXTERNAL_SEMAPHORE_HANDLE_TYPE_D3D11_KEYED_MUTEX_KMT
 * then the keyed mutex will be acquired when it is released with the key 
 * specified in ::CUDA_EXTERNAL_SEMAPHORE_WAIT_PARAMS::params::keyedmutex::key 
 * or until the timeout specified by
 * ::CUDA_EXTERNAL_SEMAPHORE_WAIT_PARAMS::params::keyedmutex::timeoutMs
 * has lapsed. The timeout interval can either be a finite value
 * specified in milliseconds or an infinite value. In case an infinite
 * value is specified the timeout never elapses. The windows INFINITE
 * macro must be used to specify infinite timeout.
 *
 * \param extSemArray - External semaphores to be waited on
 * \param paramsArray - Array of semaphore parameters
 * \param numExtSems  - Number of semaphores to wait on
 * \param stream      - Stream to enqueue the wait operations in
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_NOT_SUPPORTED,
 * ::CUDA_ERROR_TIMEOUT
 * \notefnerr
 *
 * \sa ::cuImportExternalSemaphore,
 * ::cuDestroyExternalSemaphore,
 * ::cuSignalExternalSemaphoresAsync
 */
CUresult CUDAAPI cuWaitExternalSemaphoresAsync(const CUexternalSemaphore *extSemArray, const CUDA_EXTERNAL_SEMAPHORE_WAIT_PARAMS *paramsArray, unsigned int numExtSems, CUstream stream);

/**
 * \brief Destroys an external semaphore
 *
 * Destroys an external semaphore object and releases any references
 * to the underlying resource. Any outstanding signals or waits must
 * have completed before the semaphore is destroyed.
 *
 * \param extSem - External semaphore to be destroyed
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_HANDLE
 * \notefnerr
 *
 * \sa ::cuImportExternalSemaphore,
 * ::cuSignalExternalSemaphoresAsync,
 * ::cuWaitExternalSemaphoresAsync
 */
CUresult CUDAAPI cuDestroyExternalSemaphore(CUexternalSemaphore extSem);

/** @} */ /* END CUDA_EXTRES_INTEROP */

/**
 * \defgroup CUDA_MEMOP Stream Memory Operations
 *
 * ___MANBRIEF___ Stream memory operations of the low-level CUDA driver API
 * (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the stream memory operations of the low-level CUDA
 * driver application programming interface.
 *
 * Support for the ::CU_STREAM_WAIT_VALUE_NOR flag can be queried with
 * ::CU_DEVICE_ATTRIBUTE_CAN_USE_STREAM_WAIT_VALUE_NOR_V2.
 *
 * Support for the ::cuStreamWriteValue64() and ::cuStreamWaitValue64()
 * functions, as well as for the ::CU_STREAM_MEM_OP_WAIT_VALUE_64 and
 * ::CU_STREAM_MEM_OP_WRITE_VALUE_64 flags, can be queried with
 * ::CU_DEVICE_ATTRIBUTE_CAN_USE_64_BIT_STREAM_MEM_OPS.
 *
 * Support for both ::CU_STREAM_WAIT_VALUE_FLUSH and
 * ::CU_STREAM_MEM_OP_FLUSH_REMOTE_WRITES requires dedicated platform
 * hardware features and can be queried with ::cuDeviceGetAttribute() and
 * ::CU_DEVICE_ATTRIBUTE_CAN_FLUSH_REMOTE_WRITES.
 *
 * Note that all memory pointers passed as parameters to these operations
 * are device pointers. Where necessary a device pointer should be
 * obtained, for example with ::cuMemHostGetDevicePointer().
 *
 * None of the operations accepts pointers to managed memory buffers
 * (::cuMemAllocManaged).
 *
 * \note
 * Warning:
 * Improper use of these APIs may deadlock the application. Synchronization 
 * ordering established through these APIs is not visible to CUDA. CUDA tasks 
 * that are (even indirectly) ordered by these APIs should also have that order
 * expressed with CUDA-visible dependencies such as events. This ensures that 
 * the scheduler does not serialize them in an improper order.
 *
 * @{
 */

/**
 * \brief Wait on a memory location
 *
 * Enqueues a synchronization of the stream on the given memory location. Work
 * ordered after the operation will block until the given condition on the
 * memory is satisfied. By default, the condition is to wait for
 * (int32_t)(*addr - value) >= 0, a cyclic greater-or-equal.
 * Other condition types can be specified via \p flags.
 *
 * If the memory was registered via ::cuMemHostRegister(), the device pointer
 * should be obtained with ::cuMemHostGetDevicePointer(). This function cannot
 * be used with managed memory (::cuMemAllocManaged).
 *
 * Support for CU_STREAM_WAIT_VALUE_NOR can be queried with ::cuDeviceGetAttribute() and
 * ::CU_DEVICE_ATTRIBUTE_CAN_USE_STREAM_WAIT_VALUE_NOR_V2.
 *
 * \note
 * Warning:
 * Improper use of this API may deadlock the application. Synchronization 
 * ordering established through this API is not visible to CUDA. CUDA tasks 
 * that are (even indirectly) ordered by this API should also have that order
 * expressed with CUDA-visible dependencies such as events. This ensures that 
 * the scheduler does not serialize them in an improper order.
 *
 * \param stream The stream to synchronize on the memory location.
 * \param addr The memory location to wait on.
 * \param value The value to compare with the memory location.
 * \param flags See ::CUstreamWaitValue_flags.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_NOT_SUPPORTED
 * \notefnerr
 *
 * \sa ::cuStreamWaitValue64,
 * ::cuStreamWriteValue32,
 * ::cuStreamWriteValue64,
 * ::cuStreamBatchMemOp,
 * ::cuMemHostRegister,
 * ::cuStreamWaitEvent
 */
CUresult CUDAAPI cuStreamWaitValue32(CUstream stream, CUdeviceptr addr, cuuint32_t value, unsigned int flags);

/**
 * \brief Wait on a memory location
 *
 * Enqueues a synchronization of the stream on the given memory location. Work
 * ordered after the operation will block until the given condition on the
 * memory is satisfied. By default, the condition is to wait for
 * (int64_t)(*addr - value) >= 0, a cyclic greater-or-equal.
 * Other condition types can be specified via \p flags.
 *
 * If the memory was registered via ::cuMemHostRegister(), the device pointer
 * should be obtained with ::cuMemHostGetDevicePointer().
 *
 * Support for this can be queried with ::cuDeviceGetAttribute() and
 * ::CU_DEVICE_ATTRIBUTE_CAN_USE_64_BIT_STREAM_MEM_OPS.
 *
 * \note
 * Warning:
 * Improper use of this API may deadlock the application. Synchronization 
 * ordering established through this API is not visible to CUDA. CUDA tasks 
 * that are (even indirectly) ordered by this API should also have that order
 * expressed with CUDA-visible dependencies such as events. This ensures that 
 * the scheduler does not serialize them in an improper order.
 *
 * \param stream The stream to synchronize on the memory location.
 * \param addr The memory location to wait on.
 * \param value The value to compare with the memory location.
 * \param flags See ::CUstreamWaitValue_flags.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_NOT_SUPPORTED
 * \notefnerr
 *
 * \sa ::cuStreamWaitValue32,
 * ::cuStreamWriteValue32,
 * ::cuStreamWriteValue64,
 * ::cuStreamBatchMemOp,
 * ::cuMemHostRegister,
 * ::cuStreamWaitEvent
 */
CUresult CUDAAPI cuStreamWaitValue64(CUstream stream, CUdeviceptr addr, cuuint64_t value, unsigned int flags);

/**
 * \brief Write a value to memory
 *
 * Write a value to memory.
 *
 * If the memory was registered via ::cuMemHostRegister(), the device pointer
 * should be obtained with ::cuMemHostGetDevicePointer(). This function cannot
 * be used with managed memory (::cuMemAllocManaged).
 *
 * \param stream The stream to do the write in.
 * \param addr The device address to write to.
 * \param value The value to write.
 * \param flags See ::CUstreamWriteValue_flags.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_NOT_SUPPORTED
 * \notefnerr
 *
 * \sa ::cuStreamWriteValue64,
 * ::cuStreamWaitValue32,
 * ::cuStreamWaitValue64,
 * ::cuStreamBatchMemOp,
 * ::cuMemHostRegister,
 * ::cuEventRecord
 */
CUresult CUDAAPI cuStreamWriteValue32(CUstream stream, CUdeviceptr addr, cuuint32_t value, unsigned int flags);

/**
 * \brief Write a value to memory
 *
 * Write a value to memory.
 *
 * If the memory was registered via ::cuMemHostRegister(), the device pointer
 * should be obtained with ::cuMemHostGetDevicePointer().
 *
 * Support for this can be queried with ::cuDeviceGetAttribute() and
 * ::CU_DEVICE_ATTRIBUTE_CAN_USE_64_BIT_STREAM_MEM_OPS.
 *
 * \param stream The stream to do the write in.
 * \param addr The device address to write to.
 * \param value The value to write.
 * \param flags See ::CUstreamWriteValue_flags.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_NOT_SUPPORTED
 * \notefnerr
 *
 * \sa ::cuStreamWriteValue32,
 * ::cuStreamWaitValue32,
 * ::cuStreamWaitValue64,
 * ::cuStreamBatchMemOp,
 * ::cuMemHostRegister,
 * ::cuEventRecord
 */
CUresult CUDAAPI cuStreamWriteValue64(CUstream stream, CUdeviceptr addr, cuuint64_t value, unsigned int flags);

/**
 * \brief Batch operations to synchronize the stream via memory operations
 *
 * This is a batch version of ::cuStreamWaitValue32() and ::cuStreamWriteValue32().
 * Batching operations may avoid some performance overhead in both the API call
 * and the device execution versus adding them to the stream in separate API
 * calls. The operations are enqueued in the order they appear in the array.
 *
 * See ::CUstreamBatchMemOpType for the full set of supported operations, and
 * ::cuStreamWaitValue32(), ::cuStreamWaitValue64(), ::cuStreamWriteValue32(),
 * and ::cuStreamWriteValue64() for details of specific operations.
 *
 * See related APIs for details on querying support for specific operations.
 *
 * \note
 * Warning:
 * Improper use of this API may deadlock the application. Synchronization 
 * ordering established through this API is not visible to CUDA. CUDA tasks 
 * that are (even indirectly) ordered by this API should also have that order
 * expressed with CUDA-visible dependencies such as events. This ensures that 
 * the scheduler does not serialize them in an improper order. For more 
 * information, see the Stream Memory Operations section in the programming 
 * guide(https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html).
 *
 * \param stream The stream to enqueue the operations in.
 * \param count The number of operations in the array. Must be less than 256.
 * \param paramArray The types and parameters of the individual operations.
 * \param flags Reserved for future expansion; must be 0.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_NOT_SUPPORTED
 * \notefnerr
 *
 * \sa ::cuStreamWaitValue32,
 * ::cuStreamWaitValue64,
 * ::cuStreamWriteValue32,
 * ::cuStreamWriteValue64,
 * ::cuMemHostRegister
 */
CUresult CUDAAPI cuStreamBatchMemOp(CUstream stream, unsigned int count, CUstreamBatchMemOpParams *paramArray, unsigned int flags);

/** @} */ /* END CUDA_MEMOP */

/**
 * \defgroup CUDA_EXEC Execution Control
 *
 * ___MANBRIEF___ execution control functions of the low-level CUDA driver API
 * (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the execution control functions of the low-level CUDA
 * driver application programming interface.
 *
 * @{
 */

/**
 * \brief Returns information about a function
 *
 * Returns in \p *pi the integer value of the attribute \p attrib on the kernel
 * given by \p hfunc. The supported attributes are:
 * - ::CU_FUNC_ATTRIBUTE_MAX_THREADS_PER_BLOCK: The maximum number of threads
 *   per block, beyond which a launch of the function would fail. This number
 *   depends on both the function and the device on which the function is
 *   currently loaded.
 * - ::CU_FUNC_ATTRIBUTE_SHARED_SIZE_BYTES: The size in bytes of
 *   statically-allocated shared memory per block required by this function.
 *   This does not include dynamically-allocated shared memory requested by
 *   the user at runtime.
 * - ::CU_FUNC_ATTRIBUTE_CONST_SIZE_BYTES: The size in bytes of user-allocated
 *   constant memory required by this function.
 * - ::CU_FUNC_ATTRIBUTE_LOCAL_SIZE_BYTES: The size in bytes of local memory
 *   used by each thread of this function.
 * - ::CU_FUNC_ATTRIBUTE_NUM_REGS: The number of registers used by each thread
 *   of this function.
 * - ::CU_FUNC_ATTRIBUTE_PTX_VERSION: The PTX virtual architecture version for
 *   which the function was compiled. This value is the major PTX version * 10
 *   + the minor PTX version, so a PTX version 1.3 function would return the
 *   value 13. Note that this may return the undefined value of 0 for cubins
 *   compiled prior to CUDA 3.0.
 * - ::CU_FUNC_ATTRIBUTE_BINARY_VERSION: The binary architecture version for
 *   which the function was compiled. This value is the major binary
 *   version * 10 + the minor binary version, so a binary version 1.3 function
 *   would return the value 13. Note that this will return a value of 10 for
 *   legacy cubins that do not have a properly-encoded binary architecture
 *   version.
 * - ::CU_FUNC_CACHE_MODE_CA: The attribute to indicate whether the function has
 *   been compiled with user specified option "-Xptxas --dlcm=ca" set .
 * - ::CU_FUNC_ATTRIBUTE_MAX_DYNAMIC_SHARED_SIZE_BYTES: The maximum size in bytes of
 *   dynamically-allocated shared memory.
 * - ::CU_FUNC_ATTRIBUTE_PREFERRED_SHARED_MEMORY_CARVEOUT: Preferred shared memory-L1
 *   cache split ratio in percent of total shared memory.
 * - ::CU_FUNC_ATTRIBUTE_CLUSTER_SIZE_MUST_BE_SET: If this attribute is set, the
 *   kernel must launch with a valid cluster size specified.
 * - ::CU_FUNC_ATTRIBUTE_REQUIRED_CLUSTER_WIDTH: The required cluster width in
 *   blocks.
 * - ::CU_FUNC_ATTRIBUTE_REQUIRED_CLUSTER_HEIGHT: The required cluster height in
 *   blocks.
 * - ::CU_FUNC_ATTRIBUTE_REQUIRED_CLUSTER_DEPTH: The required cluster depth in
 *   blocks.
 * - ::CU_FUNC_ATTRIBUTE_NON_PORTABLE_CLUSTER_SIZE_ALLOWED: Indicates whether
 *   the function can be launched with non-portable cluster size. 1 is allowed,
 *   0 is disallowed. A non-portable cluster size may only function on the
 *   specific SKUs the program is tested on. The launch might fail if the
 *   program is run on a different hardware platform. CUDA API provides
 *   cudaOccupancyMaxActiveClusters to assist with checking whether the desired
 *   size can be launched on the current device. A portable cluster size is
 *   guaranteed to be functional on all compute capabilities higher than the
 *   target compute capability. The portable cluster size for sm_90 is 8 blocks
 *   per cluster. This value may increase for future compute capabilities. The
 *   specific hardware unit may support higher cluster sizes that’s not
 *   guaranteed to be portable.
 * - ::CU_FUNC_ATTRIBUTE_CLUSTER_SCHEDULING_POLICY_PREFERENCE: The block
 *   scheduling policy of a function. The value type is CUclusterSchedulingPolicy.
 *
 * With a few execeptions, function attributes may also be queried on unloaded
 * function handles returned from ::cuModuleEnumerateFunctions.
 * ::CUDA_ERROR_FUNCTION_NOT_LOADED is returned if the attribute requires a fully
 * loaded function but the function is not loaded. The loading state of a function
 * may be queried using ::cuFuncIsloaded. ::cuFuncLoad may be called to explicitly
 * load a function before querying the following attributes that require the function
 * to be loaded:
 * - ::CU_FUNC_ATTRIBUTE_MAX_THREADS_PER_BLOCK
 * - ::CU_FUNC_ATTRIBUTE_CONST_SIZE_BYTES
 * - ::CU_FUNC_ATTRIBUTE_MAX_DYNAMIC_SHARED_SIZE_BYTES
 *
 * \param pi     - Returned attribute value
 * \param attrib - Attribute requested
 * \param hfunc  - Function to query attribute of
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_FUNCTION_NOT_LOADED
 * \notefnerr
 *
 * \sa ::cuCtxGetCacheConfig,
 * ::cuCtxSetCacheConfig,
 * ::cuFuncSetCacheConfig,
 * ::cuLaunchKernel,
 * ::cudaFuncGetAttributes,
 * ::cudaFuncSetAttribute,
 * ::cuFuncIsLoaded,
 * ::cuFuncLoad,
 * ::cuKernelGetAttribute
 */
CUresult CUDAAPI cuFuncGetAttribute(int *pi, CUfunction_attribute attrib, CUfunction hfunc);

/**
 * \brief Sets information about a function
 *
 * This call sets the value of a specified attribute \p attrib on the kernel given
 * by \p hfunc to an integer value specified by \p val
 * This function returns CUDA_SUCCESS if the new value of the attribute could be
 * successfully set. If the set fails, this call will return an error.
 * Not all attributes can have values set. Attempting to set a value on a read-only
 * attribute will result in an error (CUDA_ERROR_INVALID_VALUE)
 *
 * Supported attributes for the cuFuncSetAttribute call are:
 * - ::CU_FUNC_ATTRIBUTE_MAX_DYNAMIC_SHARED_SIZE_BYTES: This maximum size in bytes of
 *   dynamically-allocated shared memory. The value should contain the requested
 *   maximum size of dynamically-allocated shared memory. The sum of this value and
 *   the function attribute ::CU_FUNC_ATTRIBUTE_SHARED_SIZE_BYTES cannot exceed the
 *   device attribute ::CU_DEVICE_ATTRIBUTE_MAX_SHARED_MEMORY_PER_BLOCK_OPTIN.
 *   The maximal size of requestable dynamic shared memory may differ by GPU
 *   architecture.
 * - ::CU_FUNC_ATTRIBUTE_PREFERRED_SHARED_MEMORY_CARVEOUT: On devices where the L1
 *   cache and shared memory use the same hardware resources, this sets the shared memory
 *   carveout preference, in percent of the total shared memory. 
 *   See ::CU_DEVICE_ATTRIBUTE_MAX_SHARED_MEMORY_PER_MULTIPROCESSOR
 *   This is only a hint, and the driver can choose a different ratio if required to execute the function.
 * - ::CU_FUNC_ATTRIBUTE_REQUIRED_CLUSTER_WIDTH: The required cluster width in
 *   blocks. The width, height, and depth values must either all be 0 or all be
 *   positive. The validity of the cluster dimensions is checked at launch time.
 *   If the value is set during compile time, it cannot be set at runtime.
 *   Setting it at runtime will return CUDA_ERROR_NOT_PERMITTED.
 * - ::CU_FUNC_ATTRIBUTE_REQUIRED_CLUSTER_HEIGHT: The required cluster height in
 *   blocks. The width, height, and depth values must either all be 0 or all be
 *   positive. The validity of the cluster dimensions is checked at launch time.
 *   If the value is set during compile time, it cannot be set at runtime.
 *   Setting it at runtime will return CUDA_ERROR_NOT_PERMITTED.
 * - ::CU_FUNC_ATTRIBUTE_REQUIRED_CLUSTER_DEPTH: The required cluster depth in
 *   blocks. The width, height, and depth values must either all be 0 or all be
 *   positive. The validity of the cluster dimensions is checked at launch time.
 *   If the value is set during compile time, it cannot be set at runtime.
 *   Setting it at runtime will return CUDA_ERROR_NOT_PERMITTED.
 * - ::CU_FUNC_ATTRIBUTE_NON_PORTABLE_CLUSTER_SIZE_ALLOWED: Indicates whether
 *   the function can be launched with non-portable cluster size. 1 is allowed,
 *   0 is disallowed.
 * - ::CU_FUNC_ATTRIBUTE_CLUSTER_SCHEDULING_POLICY_PREFERENCE: The block
 *   scheduling policy of a function. The value type is CUclusterSchedulingPolicy.
 *
 * \param hfunc  - Function to query attribute of
 * \param attrib - Attribute requested
 * \param value   - The value to set
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 *
 * \sa ::cuCtxGetCacheConfig,
 * ::cuCtxSetCacheConfig,
 * ::cuFuncSetCacheConfig,
 * ::cuLaunchKernel,
 * ::cudaFuncGetAttributes,
 * ::cudaFuncSetAttribute,
 * ::cuKernelSetAttribute
 */
CUresult CUDAAPI cuFuncSetAttribute(CUfunction hfunc, CUfunction_attribute attrib, int value);

/**
 * \brief Sets the preferred cache configuration for a device function
 *
 * On devices where the L1 cache and shared memory use the same hardware
 * resources, this sets through \p config the preferred cache configuration for
 * the device function \p hfunc. This is only a preference. The driver will use
 * the requested configuration if possible, but it is free to choose a different
 * configuration if required to execute \p hfunc.  Any context-wide preference
 * set via ::cuCtxSetCacheConfig() will be overridden by this per-function
 * setting unless the per-function setting is ::CU_FUNC_CACHE_PREFER_NONE. In
 * that case, the current context-wide setting will be used.
 *
 * This setting does nothing on devices where the size of the L1 cache and
 * shared memory are fixed.
 *
 * Launching a kernel with a different preference than the most recent
 * preference setting may insert a device-side synchronization point.
 *
 *
 * The supported cache configurations are:
 * - ::CU_FUNC_CACHE_PREFER_NONE: no preference for shared memory or L1 (default)
 * - ::CU_FUNC_CACHE_PREFER_SHARED: prefer larger shared memory and smaller L1 cache
 * - ::CU_FUNC_CACHE_PREFER_L1: prefer larger L1 cache and smaller shared memory
 * - ::CU_FUNC_CACHE_PREFER_EQUAL: prefer equal sized L1 cache and shared memory
 *
 * \param hfunc  - Kernel to configure cache for
 * \param config - Requested cache configuration
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT
 * \notefnerr
 *
 * \sa ::cuCtxGetCacheConfig,
 * ::cuCtxSetCacheConfig,
 * ::cuFuncGetAttribute,
 * ::cuLaunchKernel,
 * ::cudaFuncSetCacheConfig,
 * ::cuKernelSetCacheConfig
 */
CUresult CUDAAPI cuFuncSetCacheConfig(CUfunction hfunc, CUfunc_cache config);


/**
 * \brief Returns a module handle
 *
 * Returns in \p *hmod the handle of the module that function \p hfunc
 * is located in. The lifetime of the module corresponds to the lifetime of
 * the context it was loaded in or until the module is explicitly unloaded.
 *
 * The CUDA runtime manages its own modules loaded into the primary context.
 * If the handle returned by this API refers to a module loaded by the CUDA runtime,
 * calling ::cuModuleUnload() on that module will result in undefined behavior.
 *
 * \param hmod - Returned module handle
 * \param hfunc   - Function to retrieve module for
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_NOT_FOUND
 * \notefnerr
 *
 */
CUresult CUDAAPI cuFuncGetModule(CUmodule *hmod, CUfunction hfunc);

/**
 * \brief Returns the function name for a ::CUfunction handle
 *
 * Returns in \p **name the function name associated with the function handle \p hfunc .
 * The function name is returned as a null-terminated string. The returned name is only 
 * valid when the function handle is valid. If the module is unloaded or reloaded, one 
 * must call the API again to get the updated name. This API may return a mangled name if
 * the function is not declared as having C linkage. If either \p **name or \p hfunc 
 * is NULL, ::CUDA_ERROR_INVALID_VALUE is returned.
 *
 * \param name - The returned name of the function
 * \param hfunc - The function handle to retrieve the name for 
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * \notefnerr
 *
 */
CUresult CUDAAPI cuFuncGetName(const char **name, CUfunction hfunc);

/**
 * \brief Returns the offset and size of a kernel parameter in the device-side parameter layout
 *
 * Queries the kernel parameter at \p paramIndex into \p func's list of parameters, and returns
 * in \p paramOffset and \p paramSize the offset and size, respectively, where the parameter
 * will reside in the device-side parameter layout. This information can be used to update kernel
 * node parameters from the device via ::cudaGraphKernelNodeSetParam() and
 * ::cudaGraphKernelNodeUpdatesApply(). \p paramIndex must be less than the number of parameters
 * that \p func takes. \p paramSize can be set to NULL if only the parameter offset is desired.
 *
 * \param func        - The function to query
 * \param paramIndex  - The parameter index to query
 * \param paramOffset - Returns the offset into the device-side parameter layout at which the parameter resides
 * \param paramSize   - Optionally returns the size of the parameter in the device-side parameter layout
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * \notefnerr
 *
* \sa ::cuKernelGetParamInfo
 */
CUresult CUDAAPI cuFuncGetParamInfo(CUfunction func, size_t paramIndex, size_t *paramOffset, size_t *paramSize);

typedef enum CUfunctionLoadingState_enum {
    CU_FUNCTION_LOADING_STATE_UNLOADED = 0,
    CU_FUNCTION_LOADING_STATE_LOADED = 1,
    CU_FUNCTION_LOADING_STATE_MAX
} CUfunctionLoadingState;

/**
 * \brief Returns if the function is loaded
 *
 * Returns in \p state the loading state of \p function.
 *
 * \param state - returned loading state
 * \param function - the function to check
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa ::cuFuncLoad,
 * ::cuModuleEnumerateFunctions
 */
CUresult CUDAAPI cuFuncIsLoaded(CUfunctionLoadingState *state, CUfunction function);

/**
 * \brief Loads a function
 *
 * Finalizes function loading for \p function. Calling this API with a
 * fully loaded function has no effect.
 *
 * \param function - the function to load
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa ::cuModuleEnumerateFunctions,
 * ::cuFuncIsLoaded
 */
CUresult CUDAAPI cuFuncLoad(CUfunction function);

/**
 * \brief Launches a CUDA function ::CUfunction or a CUDA kernel ::CUkernel
 *
 * Invokes the function ::CUfunction or the kernel ::CUkernel \p f
 * on a \p gridDimX x \p gridDimY x \p gridDimZ grid of blocks.
 * Each block contains \p blockDimX x \p blockDimY x
 * \p blockDimZ threads.
 *
 * \p sharedMemBytes sets the amount of dynamic shared memory that will be
 * available to each thread block.
 *
 * Kernel parameters to \p f can be specified in one of two ways:
 *
 * 1) Kernel parameters can be specified via \p kernelParams.  If \p f
 * has N parameters, then \p kernelParams needs to be an array of N
 * pointers.  Each of \p kernelParams[0] through \p kernelParams[N-1]
 * must point to a region of memory from which the actual kernel
 * parameter will be copied.  The number of kernel parameters and their
 * offsets and sizes do not need to be specified as that information is
 * retrieved directly from the kernel's image.
 *
 * 2) Kernel parameters can also be packaged by the application into
 * a single buffer that is passed in via the \p extra parameter.
 * This places the burden on the application of knowing each kernel
 * parameter's size and alignment/padding within the buffer.  Here is
 * an example of using the \p extra parameter in this manner:
 * \code
    size_t argBufferSize;
    char argBuffer[256];

    // populate argBuffer and argBufferSize

    void *config[] = {
        CU_LAUNCH_PARAM_BUFFER_POINTER, argBuffer,
        CU_LAUNCH_PARAM_BUFFER_SIZE,    &argBufferSize,
        CU_LAUNCH_PARAM_END
    };
    status = cuLaunchKernel(f, gx, gy, gz, bx, by, bz, sh, s, NULL, config);
 * \endcode
 *
 * The \p extra parameter exists to allow ::cuLaunchKernel to take
 * additional less commonly used arguments.  \p extra specifies a list of
 * names of extra settings and their corresponding values.  Each extra
 * setting name is immediately followed by the corresponding value.  The
 * list must be terminated with either NULL or ::CU_LAUNCH_PARAM_END.
 *
 * - ::CU_LAUNCH_PARAM_END, which indicates the end of the \p extra
 *   array;
 * - ::CU_LAUNCH_PARAM_BUFFER_POINTER, which specifies that the next
 *   value in \p extra will be a pointer to a buffer containing all
 *   the kernel parameters for launching kernel \p f;
 * - ::CU_LAUNCH_PARAM_BUFFER_SIZE, which specifies that the next
 *   value in \p extra will be a pointer to a size_t containing the
 *   size of the buffer specified with ::CU_LAUNCH_PARAM_BUFFER_POINTER;
 *
 * The error ::CUDA_ERROR_INVALID_VALUE will be returned if kernel
 * parameters are specified with both \p kernelParams and \p extra
 * (i.e. both \p kernelParams and \p extra are non-NULL).
 *
 * Calling ::cuLaunchKernel() invalidates the persistent function state
 * set through the following deprecated APIs:
 *  ::cuFuncSetBlockShape(),
 *  ::cuFuncSetSharedSize(),
 *  ::cuParamSetSize(),
 *  ::cuParamSeti(),
 *  ::cuParamSetf(),
 *  ::cuParamSetv().
 *
 * Note that to use ::cuLaunchKernel(), the kernel \p f must either have
 * been compiled with toolchain version 3.2 or later so that it will
 * contain kernel parameter information, or have no kernel parameters.
 * If either of these conditions is not met, then ::cuLaunchKernel() will
 * return ::CUDA_ERROR_INVALID_IMAGE.
 *
 * Note that the API can also be used to launch context-less kernel ::CUkernel
 * by querying the handle using ::cuLibraryGetKernel() and then passing it
 * to the API by casting to ::CUfunction. Here, the context to launch
 * the kernel on will either be taken from the specified stream \p hStream
 * or the current context in case of NULL stream.
 *
 * \param f              - Function ::CUfunction or Kernel ::CUkernel to launch
 * \param gridDimX       - Width of grid in blocks
 * \param gridDimY       - Height of grid in blocks
 * \param gridDimZ       - Depth of grid in blocks
 * \param blockDimX      - X dimension of each thread block
 * \param blockDimY      - Y dimension of each thread block
 * \param blockDimZ      - Z dimension of each thread block
 * \param sharedMemBytes - Dynamic shared-memory size per thread block in bytes
 * \param hStream        - Stream identifier
 * \param kernelParams   - Array of pointers to kernel parameters
 * \param extra          - Extra options
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_INVALID_IMAGE,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_LAUNCH_FAILED,
 * ::CUDA_ERROR_LAUNCH_OUT_OF_RESOURCES,
 * ::CUDA_ERROR_LAUNCH_TIMEOUT,
 * ::CUDA_ERROR_LAUNCH_INCOMPATIBLE_TEXTURING,
 * ::CUDA_ERROR_SHARED_OBJECT_INIT_FAILED,
 * ::CUDA_ERROR_NOT_FOUND
 * \note_null_stream
 * \notefnerr
 *
 * \sa ::cuCtxGetCacheConfig,
 * ::cuCtxSetCacheConfig,
 * ::cuFuncSetCacheConfig,
 * ::cuFuncGetAttribute,
 * ::cudaLaunchKernel,
 * ::cuLibraryGetKernel,
 * ::cuKernelSetCacheConfig,
 * ::cuKernelGetAttribute,
 * ::cuKernelSetAttribute
 */
CUresult CUDAAPI cuLaunchKernel(CUfunction f,
                                unsigned int gridDimX,
                                unsigned int gridDimY,
                                unsigned int gridDimZ,
                                unsigned int blockDimX,
                                unsigned int blockDimY,
                                unsigned int blockDimZ,
                                unsigned int sharedMemBytes,
                                CUstream hStream,
                                void **kernelParams,
                                void **extra);

/**
 * \brief Launches a CUDA function ::CUfunction or a CUDA kernel ::CUkernel with launch-time configuration
 *
 * Invokes the function ::CUfunction or the kernel ::CUkernel \p f with the specified launch-time configuration
 * \p config.
 *
 * The ::CUlaunchConfig structure is defined as:
 *
 * \code
 *       typedef struct CUlaunchConfig_st {
 *     unsigned int gridDimX;
 *     unsigned int gridDimY;
 *     unsigned int gridDimZ;
 *     unsigned int blockDimX;
 *     unsigned int blockDimY;
 *     unsigned int blockDimZ;
 *     unsigned int sharedMemBytes;
 *     CUstream hStream;
 *     CUlaunchAttribute *attrs;
 *     unsigned int numAttrs;
 * } CUlaunchConfig;
 * \endcode
 *
 * where:
 * - ::CUlaunchConfig::gridDimX is the width of the grid in blocks.
 * - ::CUlaunchConfig::gridDimY is the height of the grid in blocks.
 * - ::CUlaunchConfig::gridDimZ is the depth of the grid in blocks.
 * - ::CUlaunchConfig::blockDimX is the X dimension of each thread block.
 * - ::CUlaunchConfig::blockDimX is the Y dimension of each thread block.
 * - ::CUlaunchConfig::blockDimZ is the Z dimension of each thread block.
 * - ::CUlaunchConfig::sharedMemBytes is the dynamic shared-memory size per
 *   thread block in bytes.
 * - ::CUlaunchConfig::hStream is the handle to the stream to perform the launch
 *   in. The CUDA context associated with this stream must match that associated
 *   with function f.
 * - ::CUlaunchConfig::attrs is an array of ::CUlaunchConfig::numAttrs
 *   continguous ::CUlaunchAttribute elements. The value of this pointer is not
 *   considered if ::CUlaunchConfig::numAttrs is zero. However, in that case, it
 *   is recommended to set the pointer to NULL.
 * - ::CUlaunchConfig::numAttrs is the number of attributes populating the
 *   first ::CUlaunchConfig::numAttrs positions of the ::CUlaunchConfig::attrs
 *   array.
 *
 * Launch-time configuration is specified by adding entries to
 * ::CUlaunchConfig::attrs. Each entry is an attribute ID and a corresponding
 * attribute value.
 *
 * The ::CUlaunchAttribute structure is defined as:
 * \code
 *       typedef struct CUlaunchAttribute_st {
 *     CUlaunchAttributeID id;
 *     CUlaunchAttributeValue value;
 * } CUlaunchAttribute;
 * \endcode
 * where:
 * - ::CUlaunchAttribute::id is a unique enum identifying the attribute.
 * - ::CUlaunchAttribute::value is a union that hold the attribute value.
 *
 * An example of using the \p config parameter:
 * \code
 *       CUlaunchAttribute coopAttr = {.id = CU_LAUNCH_ATTRIBUTE_COOPERATIVE,
 *                               .value = 1};
 * CUlaunchConfig config = {... // set block and grid dimensions
 *                        .attrs = &coopAttr,
 *                        .numAttrs = 1};
 *
 * cuLaunchKernelEx(&config, kernel, NULL, NULL);
 * \endcode
 *
 * The ::CUlaunchAttributeID enum is defined as:
 * \code
 *       typedef enum CUlaunchAttributeID_enum {
 *     CU_LAUNCH_ATTRIBUTE_IGNORE = 0,
 *     CU_LAUNCH_ATTRIBUTE_ACCESS_POLICY_WINDOW   = 1,
 *     CU_LAUNCH_ATTRIBUTE_COOPERATIVE            = 2,
 *     CU_LAUNCH_ATTRIBUTE_SYNCHRONIZATION_POLICY = 3,
 *     CU_LAUNCH_ATTRIBUTE_CLUSTER_DIMENSION                    = 4,
 *     CU_LAUNCH_ATTRIBUTE_CLUSTER_SCHEDULING_POLICY_PREFERENCE = 5,
 *     CU_LAUNCH_ATTRIBUTE_PROGRAMMATIC_STREAM_SERIALIZATION    = 6,
 *     CU_LAUNCH_ATTRIBUTE_PROGRAMMATIC_EVENT                   = 7,
 *     CU_LAUNCH_ATTRIBUTE_PRIORITY               = 8,
 *     CU_LAUNCH_ATTRIBUTE_MEM_SYNC_DOMAIN_MAP    = 9,
 *     CU_LAUNCH_ATTRIBUTE_MEM_SYNC_DOMAIN        = 10,
 *     CU_LAUNCH_ATTRIBUTE_PREFERRED_CLUSTER_DIMENSION = 11,
 *     CU_LAUNCH_ATTRIBUTE_LAUNCH_COMPLETION_EVENT = 12,
 *     CU_LAUNCH_ATTRIBUTE_DEVICE_UPDATABLE_KERNEL_NODE = 13,
 * } CUlaunchAttributeID;
 * \endcode
 *
 * and the corresponding ::CUlaunchAttributeValue union as :
 * \code
 *       typedef union CUlaunchAttributeValue_union {
 *     CUaccessPolicyWindow accessPolicyWindow;
 *     int cooperative;
 *     CUsynchronizationPolicy syncPolicy;
 *     struct {
 *         unsigned int x;
 *         unsigned int y;
 *         unsigned int z;
 *     } clusterDim;
 *     CUclusterSchedulingPolicy clusterSchedulingPolicyPreference;
 *     int programmaticStreamSerializationAllowed;
 *     struct {
 *         CUevent event;
 *         int flags;
 *         int triggerAtBlockStart;
 *     } programmaticEvent;
 *     int priority;
 *     CUlaunchMemSyncDomainMap memSyncDomainMap;
 *     CUlaunchMemSyncDomain memSyncDomain;
 *     struct {
 *         unsigned int x;
 *         unsigned int y;
 *         unsigned int z;
 *     } preferredClusterDim;
 *     struct {
 *         CUevent event;
 *         int flags;
 *     } launchCompletionEvent;
 *     struct {
 *         int deviceUpdatable;
 *         CUgraphDeviceNode devNode;
 *     } deviceUpdatableKernelNode;
 * } CUlaunchAttributeValue;
 * \endcode
 *
 * Setting ::CU_LAUNCH_ATTRIBUTE_COOPERATIVE to a non-zero value causes the
 * kernel launch to be a cooperative launch, with exactly the same usage and
 * semantics of ::cuLaunchCooperativeKernel.
 *
 * Setting ::CU_LAUNCH_ATTRIBUTE_PROGRAMMATIC_STREAM_SERIALIZATION to a non-zero
 * values causes the kernel to use programmatic means to resolve its stream
 * dependency -- enabling the CUDA runtime to opportunistically allow the grid's
 * execution to overlap with the previous kernel in the stream, if that kernel
 * requests the overlap.
 *
 * ::CU_LAUNCH_ATTRIBUTE_PROGRAMMATIC_EVENT records an event along with the
 * kernel launch. Event recorded through this launch attribute is guaranteed to
 * only trigger after all block in the associated kernel trigger the event. A
 * block can trigger the event through PTX launchdep.release or CUDA builtin
 * function cudaTriggerProgrammaticLaunchCompletion(). A trigger can also be
 * inserted at the beginning of each block's execution if triggerAtBlockStart is
 * set to non-0. Note that dependents (including the CPU thread calling
 * cuEventSynchronize()) are not guaranteed to observe the release precisely
 * when it is released. For example, cuEventSynchronize() may only observe the
 * event trigger long after the associated kernel has completed. This recording
 * type is primarily meant for establishing programmatic dependency between
 * device tasks. The event supplied must not be an interprocess or interop
 * event. The event must disable timing (i.e. created with
 * ::CU_EVENT_DISABLE_TIMING flag set).
 *
 * ::CU_LAUNCH_ATTRIBUTE_LAUNCH_COMPLETION_EVENT records an event along with
 * the kernel launch. Nominally, the event is triggered once all blocks of the
 * kernel have begun execution. Currently this is a best effort. If a kernel B
 * has a launch completion dependency on a kernel A, B may wait until A is
 * complete. Alternatively, blocks of B may begin before all blocks of A have
 * begun, for example:
 *
 *  - If B can claim execution resources unavaiable to A, for example if they
 *    run on different GPUs.
 *  - If B is a higher priority than A.
 *
 * Exercise caution if such an ordering inversion could lead to deadlock. The
 * event supplied must not be an interprocess or interop event. The event must
 * disable timing (i.e. must be created with the ::CU_EVENT_DISABLE_TIMING flag
 * set).
 *
 * Setting ::CU_LAUNCH_ATTRIBUTE_DEVICE_UPDATABLE_KERNEL_NODE to 1
 * on a captured launch causes the resulting kernel node to be device-updatable.
 * This attribute is specific to graphs, and passing it to a launch in a
 * non-capturing stream results in an error. Passing a value other than 0 or 1 is
 * not allowed.
 *
 * On success, a handle will be returned via
 * ::CUlaunchAttributeValue::deviceUpdatableKernelNode::devNode which can be passed
 * to the various device-side update functions to update the node's kernel parameters
 * from within another kernel. For more information on the types of device updates
 * that can be made, as well as the relevant limitations thereof, see
 * ::cudaGraphKernelNodeUpdatesApply.
 *
 * Kernel nodes which are device-updatable have additional restrictions compared to regular
 * kernel nodes. Firstly, device-updatable nodes cannot be removed from their graph via
 * ::cuGraphDestroyNode. Additionally, once opted-in to this functionality, a node cannot
 * opt out, and any attempt to set the attribute to 0 will result in an error. Graphs
 * containing one or more device-updatable node also do not allow multiple instantiation.
 *
 * ::CU_LAUNCH_ATTRIBUTE_PREFERRED_CLUSTER_DIMENSION allows the kernel launch to
 * specify a preferred substitute cluster dimension. Blocks may be grouped
 * according to either the dimensions specified with this attribute (grouped
 * into a "preferred substitute cluster"), or the one specified with
 * ::CU_LAUNCH_ATTRIBUTE_CLUSTER_DIMENSION attribute (grouped into a "regular
 * cluster"). The cluster dimensions of a "preferred substitute cluster" shall
 * be an integer multiple greater than zero of the regular cluster dimensions.
 * The device will attempt - on a best-effort basis - to group thread blocks
 * into preferred clusters over grouping them into regular clusters. When it
 * deems necessary (primarily when the device temporarily runs out of physical
 * resources to launch the larger preferred clusters), the device may switch to
 * launch the regular clusters instead to attempt to utilize as much of the
 * physical device resources as possible.
 *
 * Each type of cluster will have its enumeration / coordinate setup as if the
 * grid consists solely of its type of cluster. For example, if the preferred
 * substitute cluster dimensions double the regular cluster dimensions, there
 * might be simultaneously a regular cluster indexed at (1,0,0), and a preferred
 * cluster indexed at (1,0,0). In this example, the preferred substitute cluster
 * (1,0,0) replaces regular clusters (2,0,0) and (3,0,0) and groups their
 * blocks.
 *
 * This attribute will only take effect when a regular cluster dimension has
 * been specified. The preferred substitute The preferred substitute cluster
 * dimension must be an integer multiple greater than zero of the regular
 * cluster dimension and must divide the grid. It must also be no more than
 * `maxBlocksPerCluster`, if it is set in the kernel's `__launch_bounds__`.
 * Otherwise it must be less than the maximum value the driver can support.
 * Otherwise, setting this attribute to a value physically unable to fit on any
 * particular device is permitted.
 *
 * The effect of other attributes is consistent with their effect when set via
 * persistent APIs.
 *
 * See ::cuStreamSetAttribute for
 * - ::CU_LAUNCH_ATTRIBUTE_ACCESS_POLICY_WINDOW
 * - ::CU_LAUNCH_ATTRIBUTE_SYNCHRONIZATION_POLICY
 *
 * See ::cuFuncSetAttribute for
 * - ::CU_LAUNCH_ATTRIBUTE_CLUSTER_DIMENSION
 * - ::CU_LAUNCH_ATTRIBUTE_CLUSTER_SCHEDULING_POLICY_PREFERENCE
 *
 * Kernel parameters to \p f can be specified in the same ways that they can be
 * using ::cuLaunchKernel.
 *
 * Note that the API can also be used to launch context-less kernel ::CUkernel
 * by querying the handle using ::cuLibraryGetKernel() and then passing it
 * to the API by casting to ::CUfunction. Here, the context to launch
 * the kernel on will either be taken from the specified stream ::CUlaunchConfig::hStream
 * or the current context in case of NULL stream.
 *
 * \param config         - Config to launch
 * \param f              - Function ::CUfunction or Kernel ::CUkernel to launch
 * \param kernelParams   - Array of pointers to kernel parameters
 * \param extra          - Extra options
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_INVALID_IMAGE,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_LAUNCH_FAILED,
 * ::CUDA_ERROR_LAUNCH_OUT_OF_RESOURCES,
 * ::CUDA_ERROR_LAUNCH_TIMEOUT,
 * ::CUDA_ERROR_LAUNCH_INCOMPATIBLE_TEXTURING,
 * ::CUDA_ERROR_COOPERATIVE_LAUNCH_TOO_LARGE,
 * ::CUDA_ERROR_SHARED_OBJECT_INIT_FAILED,
 * ::CUDA_ERROR_NOT_FOUND
 * \note_null_stream
 * \notefnerr
 *
 * \sa ::cuCtxGetCacheConfig,
 * ::cuCtxSetCacheConfig,
 * ::cuFuncSetCacheConfig,
 * ::cuFuncGetAttribute,
 * ::cudaLaunchKernel,
 * ::cudaLaunchKernelEx,
 * ::cuLibraryGetKernel,
 * ::cuKernelSetCacheConfig,
 * ::cuKernelGetAttribute,
 * ::cuKernelSetAttribute
 */
CUresult CUDAAPI cuLaunchKernelEx(const CUlaunchConfig *config,
                                  CUfunction f,
                                  void **kernelParams,
                                  void **extra);

/**
 * \brief Launches a CUDA function ::CUfunction or a CUDA kernel ::CUkernel where thread blocks
 * can cooperate and synchronize as they execute
 *
 * Invokes the function ::CUfunction or the kernel ::CUkernel \p f on a \p gridDimX x \p gridDimY x \p gridDimZ
 * grid of blocks. Each block contains \p blockDimX x \p blockDimY x
 * \p blockDimZ threads.
 *
 * \p sharedMemBytes sets the amount of dynamic shared memory that will be
 * available to each thread block.
 *
 * The device on which this kernel is invoked must have a non-zero value for
 * the device attribute ::CU_DEVICE_ATTRIBUTE_COOPERATIVE_LAUNCH.
 *
 * The total number of blocks launched cannot exceed the maximum number of blocks per
 * multiprocessor as returned by ::cuOccupancyMaxActiveBlocksPerMultiprocessor (or
 * ::cuOccupancyMaxActiveBlocksPerMultiprocessorWithFlags) times the number of multiprocessors
 * as specified by the device attribute ::CU_DEVICE_ATTRIBUTE_MULTIPROCESSOR_COUNT.
 *
 * The kernel cannot make use of CUDA dynamic parallelism.
 *
 * Kernel parameters must be specified via \p kernelParams.  If \p f
 * has N parameters, then \p kernelParams needs to be an array of N
 * pointers.  Each of \p kernelParams[0] through \p kernelParams[N-1]
 * must point to a region of memory from which the actual kernel
 * parameter will be copied.  The number of kernel parameters and their
 * offsets and sizes do not need to be specified as that information is
 * retrieved directly from the kernel's image.
 *
 * Calling ::cuLaunchCooperativeKernel() sets persistent function state that is
 * the same as function state set through ::cuLaunchKernel API
 *
 * When the kernel \p f is launched via ::cuLaunchCooperativeKernel(), the previous
 * block shape, shared size and parameter info associated with \p f
 * is overwritten.
 *
 * Note that to use ::cuLaunchCooperativeKernel(), the kernel \p f must either have
 * been compiled with toolchain version 3.2 or later so that it will
 * contain kernel parameter information, or have no kernel parameters.
 * If either of these conditions is not met, then ::cuLaunchCooperativeKernel() will
 * return ::CUDA_ERROR_INVALID_IMAGE.
 *
 * Note that the API can also be used to launch context-less kernel ::CUkernel
 * by querying the handle using ::cuLibraryGetKernel() and then passing it
 * to the API by casting to ::CUfunction. Here, the context to launch
 * the kernel on will either be taken from the specified stream \p hStream
 * or the current context in case of NULL stream.
 *
 * \param f              - Function ::CUfunction or Kernel ::CUkernel to launch
 * \param gridDimX       - Width of grid in blocks
 * \param gridDimY       - Height of grid in blocks
 * \param gridDimZ       - Depth of grid in blocks
 * \param blockDimX      - X dimension of each thread block
 * \param blockDimY      - Y dimension of each thread block
 * \param blockDimZ      - Z dimension of each thread block
 * \param sharedMemBytes - Dynamic shared-memory size per thread block in bytes
 * \param hStream        - Stream identifier
 * \param kernelParams   - Array of pointers to kernel parameters
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_INVALID_IMAGE,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_LAUNCH_FAILED,
 * ::CUDA_ERROR_LAUNCH_OUT_OF_RESOURCES,
 * ::CUDA_ERROR_LAUNCH_TIMEOUT,
 * ::CUDA_ERROR_LAUNCH_INCOMPATIBLE_TEXTURING,
 * ::CUDA_ERROR_COOPERATIVE_LAUNCH_TOO_LARGE,
 * ::CUDA_ERROR_SHARED_OBJECT_INIT_FAILED,
 * ::CUDA_ERROR_NOT_FOUND
 * \note_null_stream
 * \notefnerr
 *
 * \sa ::cuCtxGetCacheConfig,
 * ::cuCtxSetCacheConfig,
 * ::cuFuncSetCacheConfig,
 * ::cuFuncGetAttribute,
 * ::cuLaunchCooperativeKernelMultiDevice,
 * ::cudaLaunchCooperativeKernel,
 * ::cuLibraryGetKernel,
 * ::cuKernelSetCacheConfig,
 * ::cuKernelGetAttribute,
 * ::cuKernelSetAttribute
 */
CUresult CUDAAPI cuLaunchCooperativeKernel(CUfunction f,
                                unsigned int gridDimX,
                                unsigned int gridDimY,
                                unsigned int gridDimZ,
                                unsigned int blockDimX,
                                unsigned int blockDimY,
                                unsigned int blockDimZ,
                                unsigned int sharedMemBytes,
                                CUstream hStream,
                                void **kernelParams);

/**
 * \brief Launches CUDA functions on multiple devices where thread blocks can cooperate and synchronize as they execute
 *
 * \deprecated This function is deprecated as of CUDA 11.3.
 *
 * Invokes kernels as specified in the \p launchParamsList array where each element
 * of the array specifies all the parameters required to perform a single kernel launch.
 * These kernels can cooperate and synchronize as they execute. The size of the array is
 * specified by \p numDevices.
 *
 * No two kernels can be launched on the same device. All the devices targeted by this
 * multi-device launch must be identical. All devices must have a non-zero value for the
 * device attribute ::CU_DEVICE_ATTRIBUTE_COOPERATIVE_MULTI_DEVICE_LAUNCH.
 *
 * All kernels launched must be identical with respect to the compiled code. Note that
 * any __device__, __constant__ or __managed__ variables present in the module that owns
 * the kernel launched on each device, are independently instantiated on every device.
 * It is the application's responsibility to ensure these variables are initialized and
 * used appropriately.
 *
 * The size of the grids as specified in blocks, the size of the blocks themselves
 * and the amount of shared memory used by each thread block must also match across
 * all launched kernels.
 *
 * The streams used to launch these kernels must have been created via either ::cuStreamCreate
 * or ::cuStreamCreateWithPriority. The NULL stream or ::CU_STREAM_LEGACY or ::CU_STREAM_PER_THREAD
 * cannot be used.
 *
 * The total number of blocks launched per kernel cannot exceed the maximum number of blocks
 * per multiprocessor as returned by ::cuOccupancyMaxActiveBlocksPerMultiprocessor (or
 * ::cuOccupancyMaxActiveBlocksPerMultiprocessorWithFlags) times the number of multiprocessors
 * as specified by the device attribute ::CU_DEVICE_ATTRIBUTE_MULTIPROCESSOR_COUNT. Since the
 * total number of blocks launched per device has to match across all devices, the maximum
 * number of blocks that can be launched per device will be limited by the device with the
 * least number of multiprocessors.
 *
 * The kernels cannot make use of CUDA dynamic parallelism.
 *
 * The ::CUDA_LAUNCH_PARAMS structure is defined as:
 * \code
        typedef struct CUDA_LAUNCH_PARAMS_st
        {
            CUfunction function;
            unsigned int gridDimX;
            unsigned int gridDimY;
            unsigned int gridDimZ;
            unsigned int blockDimX;
            unsigned int blockDimY;
            unsigned int blockDimZ;
            unsigned int sharedMemBytes;
            CUstream hStream;
            void **kernelParams;
        } CUDA_LAUNCH_PARAMS;
 * \endcode
 * where:
 * - ::CUDA_LAUNCH_PARAMS::function specifies the kernel to be launched. All functions must
 *   be identical with respect to the compiled code.
 *   Note that you can also specify context-less kernel ::CUkernel by querying the handle
 *   using ::cuLibraryGetKernel() and then casting to ::CUfunction. In this case, the context to
 *   launch the kernel on be taken from the specified stream ::CUDA_LAUNCH_PARAMS::hStream.
 * - ::CUDA_LAUNCH_PARAMS::gridDimX is the width of the grid in blocks. This must match across
 *   all kernels launched.
 * - ::CUDA_LAUNCH_PARAMS::gridDimY is the height of the grid in blocks. This must match across
 *   all kernels launched.
 * - ::CUDA_LAUNCH_PARAMS::gridDimZ is the depth of the grid in blocks. This must match across
 *   all kernels launched.
 * - ::CUDA_LAUNCH_PARAMS::blockDimX is the X dimension of each thread block. This must match across
 *   all kernels launched.
 * - ::CUDA_LAUNCH_PARAMS::blockDimX is the Y dimension of each thread block. This must match across
 *   all kernels launched.
 * - ::CUDA_LAUNCH_PARAMS::blockDimZ is the Z dimension of each thread block. This must match across
 *   all kernels launched.
 * - ::CUDA_LAUNCH_PARAMS::sharedMemBytes is the dynamic shared-memory size per thread block in bytes.
 *   This must match across all kernels launched.
 * - ::CUDA_LAUNCH_PARAMS::hStream is the handle to the stream to perform the launch in. This cannot
 *   be the NULL stream or ::CU_STREAM_LEGACY or ::CU_STREAM_PER_THREAD. The CUDA context associated
 *   with this stream must match that associated with ::CUDA_LAUNCH_PARAMS::function.
 * - ::CUDA_LAUNCH_PARAMS::kernelParams is an array of pointers to kernel parameters. If
 *   ::CUDA_LAUNCH_PARAMS::function has N parameters, then ::CUDA_LAUNCH_PARAMS::kernelParams
 *   needs to be an array of N pointers. Each of ::CUDA_LAUNCH_PARAMS::kernelParams[0] through
 *   ::CUDA_LAUNCH_PARAMS::kernelParams[N-1] must point to a region of memory from which the actual
 *   kernel parameter will be copied. The number of kernel parameters and their offsets and sizes
 *   do not need to be specified as that information is retrieved directly from the kernel's image.
 *
 * By default, the kernel won't begin execution on any GPU until all prior work in all the specified
 * streams has completed. This behavior can be overridden by specifying the flag
 * ::CUDA_COOPERATIVE_LAUNCH_MULTI_DEVICE_NO_PRE_LAUNCH_SYNC. When this flag is specified, each kernel
 * will only wait for prior work in the stream corresponding to that GPU to complete before it begins
 * execution.
 *
 * Similarly, by default, any subsequent work pushed in any of the specified streams will not begin
 * execution until the kernels on all GPUs have completed. This behavior can be overridden by specifying
 * the flag ::CUDA_COOPERATIVE_LAUNCH_MULTI_DEVICE_NO_POST_LAUNCH_SYNC. When this flag is specified,
 * any subsequent work pushed in any of the specified streams will only wait for the kernel launched
 * on the GPU corresponding to that stream to complete before it begins execution.
 *
 * Calling ::cuLaunchCooperativeKernelMultiDevice() sets persistent function state that is
 * the same as function state set through ::cuLaunchKernel API when called individually for each
 * element in \p launchParamsList.
 *
 * When kernels are launched via ::cuLaunchCooperativeKernelMultiDevice(), the previous
 * block shape, shared size and parameter info associated with each ::CUDA_LAUNCH_PARAMS::function
 * in \p launchParamsList is overwritten.
 *
 * Note that to use ::cuLaunchCooperativeKernelMultiDevice(), the kernels must either have
 * been compiled with toolchain version 3.2 or later so that it will
 * contain kernel parameter information, or have no kernel parameters.
 * If either of these conditions is not met, then ::cuLaunchCooperativeKernelMultiDevice() will
 * return ::CUDA_ERROR_INVALID_IMAGE.
 *
 * \param launchParamsList - List of launch parameters, one per device
 * \param numDevices       - Size of the \p launchParamsList array
 * \param flags            - Flags to control launch behavior
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_INVALID_IMAGE,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_LAUNCH_FAILED,
 * ::CUDA_ERROR_LAUNCH_OUT_OF_RESOURCES,
 * ::CUDA_ERROR_LAUNCH_TIMEOUT,
 * ::CUDA_ERROR_LAUNCH_INCOMPATIBLE_TEXTURING,
 * ::CUDA_ERROR_COOPERATIVE_LAUNCH_TOO_LARGE,
 * ::CUDA_ERROR_SHARED_OBJECT_INIT_FAILED
 * \note_null_stream
 * \notefnerr
 *
 * \sa ::cuCtxGetCacheConfig,
 * ::cuCtxSetCacheConfig,
 * ::cuFuncSetCacheConfig,
 * ::cuFuncGetAttribute,
 * ::cuLaunchCooperativeKernel,
 * ::cudaLaunchCooperativeKernelMultiDevice
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuLaunchCooperativeKernelMultiDevice(CUDA_LAUNCH_PARAMS *launchParamsList, unsigned int numDevices, unsigned int flags);

/**
 * \brief Enqueues a host function call in a stream
 *
 * Enqueues a host function to run in a stream.  The function will be called
 * after currently enqueued work and will block work added after it.
 *
 * The host function must not make any CUDA API calls.  Attempting to use a
 * CUDA API may result in ::CUDA_ERROR_NOT_PERMITTED, but this is not required.
 * The host function must not perform any synchronization that may depend on
 * outstanding CUDA work not mandated to run earlier.  Host functions without a
 * mandated order (such as in independent streams) execute in undefined order
 * and may be serialized.
 *
 * For the purposes of Unified Memory, execution makes a number of guarantees:
 * <ul>
 *   <li>The stream is considered idle for the duration of the function's
 *   execution.  Thus, for example, the function may always use memory attached
 *   to the stream it was enqueued in.</li>
 *   <li>The start of execution of the function has the same effect as
 *   synchronizing an event recorded in the same stream immediately prior to
 *   the function.  It thus synchronizes streams which have been "joined"
 *   prior to the function.</li>
 *   <li>Adding device work to any stream does not have the effect of making
 *   the stream active until all preceding host functions and stream callbacks
 *   have executed.  Thus, for
 *   example, a function might use global attached memory even if work has
 *   been added to another stream, if the work has been ordered behind the
 *   function call with an event.</li>
 *   <li>Completion of the function does not cause a stream to become
 *   active except as described above.  The stream will remain idle
 *   if no device work follows the function, and will remain idle across
 *   consecutive host functions or stream callbacks without device work in
 *   between.  Thus, for example,
 *   stream synchronization can be done by signaling from a host function at the
 *   end of the stream.</li>
 * </ul>
 *
 * Note that, in contrast to ::cuStreamAddCallback, the function will not be
 * called in the event of an error in the CUDA context.
 *
 * \param hStream  - Stream to enqueue function call in
 * \param fn       - The function to call once preceding stream operations are complete
 * \param userData - User-specified data to be passed to the function
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_NOT_SUPPORTED
 * \note_null_stream
 * \notefnerr
 *
 * \sa ::cuStreamCreate,
 * ::cuStreamQuery,
 * ::cuStreamSynchronize,
 * ::cuStreamWaitEvent,
 * ::cuStreamDestroy,
 * ::cuMemAllocManaged,
 * ::cuStreamAttachMemAsync,
 * ::cuStreamAddCallback
 */
CUresult CUDAAPI cuLaunchHostFunc(CUstream hStream, CUhostFn fn, void *userData);

/** @} */ /* END CUDA_EXEC */

/**
 * \defgroup CUDA_EXEC_DEPRECATED Execution Control [DEPRECATED]
 *
 * ___MANBRIEF___ deprecated execution control functions of the low-level CUDA
 * driver API (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the deprecated execution control functions of the
 * low-level CUDA driver application programming interface.
 *
 * @{
 */

/**
 * \brief Sets the block-dimensions for the function
 *
 * \deprecated
 *
 * Specifies the \p x, \p y, and \p z dimensions of the thread blocks that are
 * created when the kernel given by \p hfunc is launched.
 *
 * \param hfunc - Kernel to specify dimensions of
 * \param x     - X dimension
 * \param y     - Y dimension
 * \param z     - Z dimension
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 *
 * \sa ::cuFuncSetSharedSize,
 * ::cuFuncSetCacheConfig,
 * ::cuFuncGetAttribute,
 * ::cuParamSetSize,
 * ::cuParamSeti,
 * ::cuParamSetf,
 * ::cuParamSetv,
 * ::cuLaunch,
 * ::cuLaunchGrid,
 * ::cuLaunchGridAsync,
 * ::cuLaunchKernel
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuFuncSetBlockShape(CUfunction hfunc, int x, int y, int z);

/**
 * \brief Sets the dynamic shared-memory size for the function
 *
 * \deprecated
 *
 * Sets through \p bytes the amount of dynamic shared memory that will be
 * available to each thread block when the kernel given by \p hfunc is launched.
 *
 * \param hfunc - Kernel to specify dynamic shared-memory size for
 * \param bytes - Dynamic shared-memory size per thread in bytes
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 *
 * \sa ::cuFuncSetBlockShape,
 * ::cuFuncSetCacheConfig,
 * ::cuFuncGetAttribute,
 * ::cuParamSetSize,
 * ::cuParamSeti,
 * ::cuParamSetf,
 * ::cuParamSetv,
 * ::cuLaunch,
 * ::cuLaunchGrid,
 * ::cuLaunchGridAsync,
 * ::cuLaunchKernel
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuFuncSetSharedSize(CUfunction hfunc, unsigned int bytes);

/**
 * \brief Sets the parameter size for the function
 *
 * \deprecated
 *
 * Sets through \p numbytes the total size in bytes needed by the function
 * parameters of the kernel corresponding to \p hfunc.
 *
 * \param hfunc    - Kernel to set parameter size for
 * \param numbytes - Size of parameter list in bytes
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 *
 * \sa ::cuFuncSetBlockShape,
 * ::cuFuncSetSharedSize,
 * ::cuFuncGetAttribute,
 * ::cuParamSetf,
 * ::cuParamSeti,
 * ::cuParamSetv,
 * ::cuLaunch,
 * ::cuLaunchGrid,
 * ::cuLaunchGridAsync,
 * ::cuLaunchKernel
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuParamSetSize(CUfunction hfunc, unsigned int numbytes);

/**
 * \brief Adds an integer parameter to the function's argument list
 *
 * \deprecated
 *
 * Sets an integer parameter that will be specified the next time the
 * kernel corresponding to \p hfunc will be invoked. \p offset is a byte offset.
 *
 * \param hfunc  - Kernel to add parameter to
 * \param offset - Offset to add parameter to argument list
 * \param value  - Value of parameter
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 *
 * \sa ::cuFuncSetBlockShape,
 * ::cuFuncSetSharedSize,
 * ::cuFuncGetAttribute,
 * ::cuParamSetSize,
 * ::cuParamSetf,
 * ::cuParamSetv,
 * ::cuLaunch,
 * ::cuLaunchGrid,
 * ::cuLaunchGridAsync,
 * ::cuLaunchKernel
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuParamSeti(CUfunction hfunc, int offset, unsigned int value);

/**
 * \brief Adds a floating-point parameter to the function's argument list
 *
 * \deprecated
 *
 * Sets a floating-point parameter that will be specified the next time the
 * kernel corresponding to \p hfunc will be invoked. \p offset is a byte offset.
 *
 * \param hfunc  - Kernel to add parameter to
 * \param offset - Offset to add parameter to argument list
 * \param value  - Value of parameter
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 *
 * \sa ::cuFuncSetBlockShape,
 * ::cuFuncSetSharedSize,
 * ::cuFuncGetAttribute,
 * ::cuParamSetSize,
 * ::cuParamSeti,
 * ::cuParamSetv,
 * ::cuLaunch,
 * ::cuLaunchGrid,
 * ::cuLaunchGridAsync,
 * ::cuLaunchKernel
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuParamSetf(CUfunction hfunc, int offset, float value);

/**
 * \brief Adds arbitrary data to the function's argument list
 *
 * \deprecated
 *
 * Copies an arbitrary amount of data (specified in \p numbytes) from \p ptr
 * into the parameter space of the kernel corresponding to \p hfunc. \p offset
 * is a byte offset.
 *
 * \param hfunc    - Kernel to add data to
 * \param offset   - Offset to add data to argument list
 * \param ptr      - Pointer to arbitrary data
 * \param numbytes - Size of data to copy in bytes
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 *
 * \sa ::cuFuncSetBlockShape,
 * ::cuFuncSetSharedSize,
 * ::cuFuncGetAttribute,
 * ::cuParamSetSize,
 * ::cuParamSetf,
 * ::cuParamSeti,
 * ::cuLaunch,
 * ::cuLaunchGrid,
 * ::cuLaunchGridAsync,
 * ::cuLaunchKernel
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuParamSetv(CUfunction hfunc, int offset, void *ptr, unsigned int numbytes);

/**
 * \brief Launches a CUDA function
 *
 * \deprecated
 *
 * Invokes the kernel \p f on a 1 x 1 x 1 grid of blocks. The block
 * contains the number of threads specified by a previous call to
 * ::cuFuncSetBlockShape().
 *
 * The block shape, dynamic shared memory size, and parameter information
 * must be set using
 *  ::cuFuncSetBlockShape(),
 *  ::cuFuncSetSharedSize(),
 *  ::cuParamSetSize(),
 *  ::cuParamSeti(),
 *  ::cuParamSetf(), and
 *  ::cuParamSetv()
 * prior to calling this function.
 *
 * Launching a function via ::cuLaunchKernel() invalidates the function's
 * block shape, dynamic shared memory size, and parameter information. After
 * launching via cuLaunchKernel, this state must be re-initialized prior to
 * calling this function. Failure to do so results in undefined behavior.
 *
 * \param f - Kernel to launch
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_LAUNCH_FAILED,
 * ::CUDA_ERROR_LAUNCH_OUT_OF_RESOURCES,
 * ::CUDA_ERROR_LAUNCH_TIMEOUT,
 * ::CUDA_ERROR_LAUNCH_INCOMPATIBLE_TEXTURING,
 * ::CUDA_ERROR_SHARED_OBJECT_INIT_FAILED
 * \notefnerr
 *
 * \sa ::cuFuncSetBlockShape,
 * ::cuFuncSetSharedSize,
 * ::cuFuncGetAttribute,
 * ::cuParamSetSize,
 * ::cuParamSetf,
 * ::cuParamSeti,
 * ::cuParamSetv,
 * ::cuLaunchGrid,
 * ::cuLaunchGridAsync,
 * ::cuLaunchKernel
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuLaunch(CUfunction f);

/**
 * \brief Launches a CUDA function
 *
 * \deprecated
 *
 * Invokes the kernel \p f on a \p grid_width x \p grid_height grid of
 * blocks. Each block contains the number of threads specified by a previous
 * call to ::cuFuncSetBlockShape().
 *
 * The block shape, dynamic shared memory size, and parameter information
 * must be set using
 *  ::cuFuncSetBlockShape(),
 *  ::cuFuncSetSharedSize(),
 *  ::cuParamSetSize(),
 *  ::cuParamSeti(),
 *  ::cuParamSetf(), and
 *  ::cuParamSetv()
 * prior to calling this function.
 *
 * Launching a function via ::cuLaunchKernel() invalidates the function's
 * block shape, dynamic shared memory size, and parameter information. After
 * launching via cuLaunchKernel, this state must be re-initialized prior to
 * calling this function. Failure to do so results in undefined behavior.
 *
 * \param f           - Kernel to launch
 * \param grid_width  - Width of grid in blocks
 * \param grid_height - Height of grid in blocks
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_LAUNCH_FAILED,
 * ::CUDA_ERROR_LAUNCH_OUT_OF_RESOURCES,
 * ::CUDA_ERROR_LAUNCH_TIMEOUT,
 * ::CUDA_ERROR_LAUNCH_INCOMPATIBLE_TEXTURING,
 * ::CUDA_ERROR_SHARED_OBJECT_INIT_FAILED
 * \notefnerr
 *
 * \sa ::cuFuncSetBlockShape,
 * ::cuFuncSetSharedSize,
 * ::cuFuncGetAttribute,
 * ::cuParamSetSize,
 * ::cuParamSetf,
 * ::cuParamSeti,
 * ::cuParamSetv,
 * ::cuLaunch,
 * ::cuLaunchGridAsync,
 * ::cuLaunchKernel
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuLaunchGrid(CUfunction f, int grid_width, int grid_height);

/**
 * \brief Launches a CUDA function
 *
 * \deprecated
 *
 * Invokes the kernel \p f on a \p grid_width x \p grid_height grid of
 * blocks. Each block contains the number of threads specified by a previous
 * call to ::cuFuncSetBlockShape().
 *
 * The block shape, dynamic shared memory size, and parameter information
 * must be set using
 *  ::cuFuncSetBlockShape(),
 *  ::cuFuncSetSharedSize(),
 *  ::cuParamSetSize(),
 *  ::cuParamSeti(),
 *  ::cuParamSetf(), and
 *  ::cuParamSetv()
 * prior to calling this function.
 *
 * Launching a function via ::cuLaunchKernel() invalidates the function's
 * block shape, dynamic shared memory size, and parameter information. After
 * launching via cuLaunchKernel, this state must be re-initialized prior to
 * calling this function. Failure to do so results in undefined behavior.
 *
 * \param f           - Kernel to launch
 * \param grid_width  - Width of grid in blocks
 * \param grid_height - Height of grid in blocks
 * \param hStream     - Stream identifier
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_LAUNCH_FAILED,
 * ::CUDA_ERROR_LAUNCH_OUT_OF_RESOURCES,
 * ::CUDA_ERROR_LAUNCH_TIMEOUT,
 * ::CUDA_ERROR_LAUNCH_INCOMPATIBLE_TEXTURING,
 * ::CUDA_ERROR_SHARED_OBJECT_INIT_FAILED
 *
 * \note In certain cases where cubins are created with no ABI (i.e., using \p ptxas \p --abi-compile \p no),
 *       this function may serialize kernel launches. The CUDA driver retains asynchronous behavior by
 *       growing the per-thread stack as needed per launch and not shrinking it afterwards.
 *
 * \note_null_stream
 * \notefnerr
 *
 * \sa ::cuFuncSetBlockShape,
 * ::cuFuncSetSharedSize,
 * ::cuFuncGetAttribute,
 * ::cuParamSetSize,
 * ::cuParamSetf,
 * ::cuParamSeti,
 * ::cuParamSetv,
 * ::cuLaunch,
 * ::cuLaunchGrid,
 * ::cuLaunchKernel
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuLaunchGridAsync(CUfunction f, int grid_width, int grid_height, CUstream hStream);


/**
 * \brief Adds a texture-reference to the function's argument list
 *
 * \deprecated
 *
 * Makes the CUDA array or linear memory bound to the texture reference
 * \p hTexRef available to a device program as a texture. In this version of
 * CUDA, the texture-reference must be obtained via ::cuModuleGetTexRef() and
 * the \p texunit parameter must be set to ::CU_PARAM_TR_DEFAULT.
 *
 * \param hfunc   - Kernel to add texture-reference to
 * \param texunit - Texture unit (must be ::CU_PARAM_TR_DEFAULT)
 * \param hTexRef - Texture-reference to add to argument list
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuParamSetTexRef(CUfunction hfunc, int texunit, CUtexref hTexRef);

/**
 * \brief Sets the shared memory configuration for a device function.
 *
 * \deprecated
 *
 * On devices with configurable shared memory banks, this function will
 * force all subsequent launches of the specified device function to have
 * the given shared memory bank size configuration. On any given launch of the
 * function, the shared memory configuration of the device will be temporarily
 * changed if needed to suit the function's preferred configuration. Changes in
 * shared memory configuration between subsequent launches of functions,
 * may introduce a device side synchronization point.
 *
 * Any per-function setting of shared memory bank size set via
 * ::cuFuncSetSharedMemConfig will override the context wide setting set with
 * ::cuCtxSetSharedMemConfig.
 *
 * Changing the shared memory bank size will not increase shared memory usage
 * or affect occupancy of kernels, but may have major effects on performance.
 * Larger bank sizes will allow for greater potential bandwidth to shared memory,
 * but will change what kinds of accesses to shared memory will result in bank
 * conflicts.
 *
 * This function will do nothing on devices with fixed shared memory bank size.
 *
 * The supported bank configurations are:
 * - ::CU_SHARED_MEM_CONFIG_DEFAULT_BANK_SIZE: use the context's shared memory
 *   configuration when launching this function.
 * - ::CU_SHARED_MEM_CONFIG_FOUR_BYTE_BANK_SIZE: set shared memory bank width to
 *   be natively four bytes when launching this function.
 * - ::CU_SHARED_MEM_CONFIG_EIGHT_BYTE_BANK_SIZE: set shared memory bank width to
 *   be natively eight bytes when launching this function.
 *
 * \param hfunc  - kernel to be given a shared memory config
 * \param config - requested shared memory configuration
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT
 * \notefnerr
 *
 * \sa ::cuCtxGetCacheConfig,
 * ::cuCtxSetCacheConfig,
 * ::cuCtxGetSharedMemConfig,
 * ::cuCtxSetSharedMemConfig,
 * ::cuFuncGetAttribute,
 * ::cuLaunchKernel,
 * ::cudaFuncSetSharedMemConfig
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuFuncSetSharedMemConfig(CUfunction hfunc, CUsharedconfig config);

/** @} */ /* END CUDA_EXEC_DEPRECATED */

/**
 * \defgroup CUDA_GRAPH Graph Management
 *
 * ___MANBRIEF___ graph management functions of the low-level CUDA driver API
 * (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the graph management functions of the low-level CUDA
 * driver application programming interface.
 *
 * @{
 */

/**
 * \brief Creates a graph
 *
 * Creates an empty graph, which is returned via \p phGraph.
 *
 * \param phGraph - Returns newly created graph
 * \param flags   - Graph creation flags, must be 0
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_OUT_OF_MEMORY
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphAddChildGraphNode,
 * ::cuGraphAddEmptyNode,
 * ::cuGraphAddKernelNode,
 * ::cuGraphAddHostNode,
 * ::cuGraphAddMemcpyNode,
 * ::cuGraphAddMemsetNode,
 * ::cuGraphInstantiate,
 * ::cuGraphDestroy,
 * ::cuGraphGetNodes,
 * ::cuGraphGetRootNodes,
 * ::cuGraphGetEdges,
 * ::cuGraphClone
 */
CUresult CUDAAPI cuGraphCreate(CUgraph *phGraph, unsigned int flags);

/**
 * \brief Creates a kernel execution node and adds it to a graph
 *
 * Creates a new kernel execution node and adds it to \p hGraph with \p numDependencies
 * dependencies specified via \p dependencies and arguments specified in \p nodeParams.
 * It is possible for \p numDependencies to be 0, in which case the node will be placed
 * at the root of the graph. \p dependencies may not have any duplicate entries.
 * A handle to the new node will be returned in \p phGraphNode.
 *
 * The CUDA_KERNEL_NODE_PARAMS structure is defined as:
 *
 * \code
 *  typedef struct CUDA_KERNEL_NODE_PARAMS_st {
 *      CUfunction func;
 *      unsigned int gridDimX;
 *      unsigned int gridDimY;
 *      unsigned int gridDimZ;
 *      unsigned int blockDimX;
 *      unsigned int blockDimY;
 *      unsigned int blockDimZ;
 *      unsigned int sharedMemBytes;
 *      void **kernelParams;
 *      void **extra;
 *      CUkernel kern;
 *      CUcontext ctx;
 *  } CUDA_KERNEL_NODE_PARAMS;
 * \endcode
 *
 * When the graph is launched, the node will invoke kernel \p func on a (\p gridDimX x
 * \p gridDimY x \p gridDimZ) grid of blocks. Each block contains
 * (\p blockDimX x \p blockDimY x \p blockDimZ) threads.
 *
 * \p sharedMemBytes sets the amount of dynamic shared memory that will be
 * available to each thread block.
 *
 * Kernel parameters to \p func can be specified in one of two ways:
 *
 * 1) Kernel parameters can be specified via \p kernelParams. If the kernel has N
 * parameters, then \p kernelParams needs to be an array of N pointers. Each pointer,
 * from \p kernelParams[0] to \p kernelParams[N-1], points to the region of memory from which the actual
 * parameter will be copied. The number of kernel parameters and their offsets and sizes do not need
 * to be specified as that information is retrieved directly from the kernel's image.
 *
 * 2) Kernel parameters for non-cooperative kernels can also be packaged by the application into a single
 * buffer that is passed in via \p extra. This places the burden on the application of knowing each
 * kernel parameter's size and alignment/padding within the buffer. The \p extra parameter exists
 * to allow this function to take additional less commonly used arguments. \p extra specifies
 * a list of names of extra settings and their corresponding values. Each extra setting name is
 * immediately followed by the corresponding value. The list must be terminated with either NULL or
 * CU_LAUNCH_PARAM_END.
 *
 * - ::CU_LAUNCH_PARAM_END, which indicates the end of the \p extra
 *   array;
 * - ::CU_LAUNCH_PARAM_BUFFER_POINTER, which specifies that the next
 *   value in \p extra will be a pointer to a buffer
 *   containing all the kernel parameters for launching kernel
 *   \p func;
 * - ::CU_LAUNCH_PARAM_BUFFER_SIZE, which specifies that the next
 *   value in \p extra will be a pointer to a size_t
 *   containing the size of the buffer specified with
 *   ::CU_LAUNCH_PARAM_BUFFER_POINTER;
 *
 * The error ::CUDA_ERROR_INVALID_VALUE will be returned if kernel parameters are specified with both
 * \p kernelParams and \p extra (i.e. both \p kernelParams and \p extra are non-NULL).
 * ::CUDA_ERROR_INVALID_VALUE will be returned if \p extra is used for a cooperative kernel.
 *
 * The \p kernelParams or \p extra array, as well as the argument values it points to,
 * are copied during this call.
 *
 * \note Kernels launched using graphs must not use texture and surface references. Reading or
 *       writing through any texture or surface reference is undefined behavior.
 *       This restriction does not apply to texture and surface objects.
 *
 * \param phGraphNode     - Returns newly created node
 * \param hGraph          - Graph to which to add the node
 * \param dependencies    - Dependencies of the node
 * \param numDependencies - Number of dependencies
 * \param nodeParams      - Parameters for the GPU execution node
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphAddNode,
 * ::cuLaunchKernel,
 * ::cuLaunchCooperativeKernel,
 * ::cuGraphKernelNodeGetParams,
 * ::cuGraphKernelNodeSetParams,
 * ::cuGraphCreate,
 * ::cuGraphDestroyNode,
 * ::cuGraphAddChildGraphNode,
 * ::cuGraphAddEmptyNode,
 * ::cuGraphAddHostNode,
 * ::cuGraphAddMemcpyNode,
 * ::cuGraphAddMemsetNode
 */
CUresult CUDAAPI cuGraphAddKernelNode(CUgraphNode *phGraphNode, CUgraph hGraph, const CUgraphNode *dependencies, size_t numDependencies, const CUDA_KERNEL_NODE_PARAMS *nodeParams);

/**
 * \brief Returns a kernel node's parameters
 *
 * Returns the parameters of kernel node \p hNode in \p nodeParams.
 * The \p kernelParams or \p extra array returned in \p nodeParams,
 * as well as the argument values it points to, are owned by the node.
 * This memory remains valid until the node is destroyed or its
 * parameters are modified, and should not be modified
 * directly. Use ::cuGraphKernelNodeSetParams to update the
 * parameters of this node.
 *
 * The params will contain either \p kernelParams or \p extra,
 * according to which of these was most recently set on the node.
 *
 * \param hNode      - Node to get the parameters for
 * \param nodeParams - Pointer to return the parameters
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuLaunchKernel,
 * ::cuGraphAddKernelNode,
 * ::cuGraphKernelNodeSetParams
 */
CUresult CUDAAPI cuGraphKernelNodeGetParams(CUgraphNode hNode, CUDA_KERNEL_NODE_PARAMS *nodeParams);

/**
 * \brief Sets a kernel node's parameters
 *
 * Sets the parameters of kernel node \p hNode to \p nodeParams.
 *
 * \param hNode      - Node to set the parameters for
 * \param nodeParams - Parameters to copy
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_OUT_OF_MEMORY
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphNodeSetParams,
 * ::cuLaunchKernel,
 * ::cuGraphAddKernelNode,
 * ::cuGraphKernelNodeGetParams
 */
CUresult CUDAAPI cuGraphKernelNodeSetParams(CUgraphNode hNode, const CUDA_KERNEL_NODE_PARAMS *nodeParams);

/**
 * \brief Creates a memcpy node and adds it to a graph
 *
 * Creates a new memcpy node and adds it to \p hGraph with \p numDependencies
 * dependencies specified via \p dependencies.
 * It is possible for \p numDependencies to be 0, in which case the node will be placed
 * at the root of the graph. \p dependencies may not have any duplicate entries.
 * A handle to the new node will be returned in \p phGraphNode.
 *
 * When the graph is launched, the node will perform the memcpy described by \p copyParams.
 * See ::cuMemcpy3D() for a description of the structure and its restrictions.
 *
 * Memcpy nodes have some additional restrictions with regards to managed memory, if the
 * system contains at least one device which has a zero value for the device attribute
 * ::CU_DEVICE_ATTRIBUTE_CONCURRENT_MANAGED_ACCESS. If one or more of the operands refer
 * to managed memory, then using the memory type ::CU_MEMORYTYPE_UNIFIED is disallowed
 * for those operand(s). The managed memory will be treated as residing on either the
 * host or the device, depending on which memory type is specified.
 *
 * \param phGraphNode     - Returns newly created node
 * \param hGraph          - Graph to which to add the node
 * \param dependencies    - Dependencies of the node
 * \param numDependencies - Number of dependencies
 * \param copyParams      - Parameters for the memory copy
 * \param ctx             - Context on which to run the node
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphAddNode,
 * ::cuMemcpy3D,
 * ::cuGraphMemcpyNodeGetParams,
 * ::cuGraphMemcpyNodeSetParams,
 * ::cuGraphCreate,
 * ::cuGraphDestroyNode,
 * ::cuGraphAddChildGraphNode,
 * ::cuGraphAddEmptyNode,
 * ::cuGraphAddKernelNode,
 * ::cuGraphAddHostNode,
 * ::cuGraphAddMemsetNode
 */
CUresult CUDAAPI cuGraphAddMemcpyNode(CUgraphNode *phGraphNode, CUgraph hGraph, const CUgraphNode *dependencies, size_t numDependencies, const CUDA_MEMCPY3D *copyParams, CUcontext ctx);

/**
 * \brief Returns a memcpy node's parameters
 *
 * Returns the parameters of memcpy node \p hNode in \p nodeParams.
 *
 * \param hNode      - Node to get the parameters for
 * \param nodeParams - Pointer to return the parameters
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuMemcpy3D,
 * ::cuGraphAddMemcpyNode,
 * ::cuGraphMemcpyNodeSetParams
 */
CUresult CUDAAPI cuGraphMemcpyNodeGetParams(CUgraphNode hNode, CUDA_MEMCPY3D *nodeParams);

/**
 * \brief Sets a memcpy node's parameters
 *
 * Sets the parameters of memcpy node \p hNode to \p nodeParams.
 *
 * \param hNode      - Node to set the parameters for
 * \param nodeParams - Parameters to copy
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE,
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphNodeSetParams,
 * ::cuMemcpy3D,
 * ::cuGraphAddMemcpyNode,
 * ::cuGraphMemcpyNodeGetParams
 */
CUresult CUDAAPI cuGraphMemcpyNodeSetParams(CUgraphNode hNode, const CUDA_MEMCPY3D *nodeParams);

/**
 * \brief Creates a memset node and adds it to a graph
 *
 * Creates a new memset node and adds it to \p hGraph with \p numDependencies
 * dependencies specified via \p dependencies.
 * It is possible for \p numDependencies to be 0, in which case the node will be placed
 * at the root of the graph. \p dependencies may not have any duplicate entries.
 * A handle to the new node will be returned in \p phGraphNode.
 *
 * The element size must be 1, 2, or 4 bytes.
 * When the graph is launched, the node will perform the memset described by \p memsetParams.
 *
 * \param phGraphNode     - Returns newly created node
 * \param hGraph          - Graph to which to add the node
 * \param dependencies    - Dependencies of the node
 * \param numDependencies - Number of dependencies
 * \param memsetParams    - Parameters for the memory set
 * \param ctx             - Context on which to run the node
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_CONTEXT
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphAddNode,
 * ::cuMemsetD2D32,
 * ::cuGraphMemsetNodeGetParams,
 * ::cuGraphMemsetNodeSetParams,
 * ::cuGraphCreate,
 * ::cuGraphDestroyNode,
 * ::cuGraphAddChildGraphNode,
 * ::cuGraphAddEmptyNode,
 * ::cuGraphAddKernelNode,
 * ::cuGraphAddHostNode,
 * ::cuGraphAddMemcpyNode
 */
CUresult CUDAAPI cuGraphAddMemsetNode(CUgraphNode *phGraphNode, CUgraph hGraph, const CUgraphNode *dependencies, size_t numDependencies, const CUDA_MEMSET_NODE_PARAMS *memsetParams, CUcontext ctx);

/**
 * \brief Returns a memset node's parameters
 *
 * Returns the parameters of memset node \p hNode in \p nodeParams.
 *
 * \param hNode      - Node to get the parameters for
 * \param nodeParams - Pointer to return the parameters
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuMemsetD2D32,
 * ::cuGraphAddMemsetNode,
 * ::cuGraphMemsetNodeSetParams
 */
CUresult CUDAAPI cuGraphMemsetNodeGetParams(CUgraphNode hNode, CUDA_MEMSET_NODE_PARAMS *nodeParams);

/**
 * \brief Sets a memset node's parameters
 *
 * Sets the parameters of memset node \p hNode to \p nodeParams.
 *
 * \param hNode      - Node to set the parameters for
 * \param nodeParams - Parameters to copy
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphNodeSetParams,
 * ::cuMemsetD2D32,
 * ::cuGraphAddMemsetNode,
 * ::cuGraphMemsetNodeGetParams
 */
CUresult CUDAAPI cuGraphMemsetNodeSetParams(CUgraphNode hNode, const CUDA_MEMSET_NODE_PARAMS *nodeParams);

/**
 * \brief Creates a host execution node and adds it to a graph
 *
 * Creates a new CPU execution node and adds it to \p hGraph with \p numDependencies
 * dependencies specified via \p dependencies and arguments specified in \p nodeParams.
 * It is possible for \p numDependencies to be 0, in which case the node will be placed
 * at the root of the graph. \p dependencies may not have any duplicate entries.
 * A handle to the new node will be returned in \p phGraphNode.
 *
 * When the graph is launched, the node will invoke the specified CPU function.
 * Host nodes are not supported under MPS with pre-Volta GPUs.
 *
 * \param phGraphNode     - Returns newly created node
 * \param hGraph          - Graph to which to add the node
 * \param dependencies    - Dependencies of the node
 * \param numDependencies - Number of dependencies
 * \param nodeParams      - Parameters for the host node
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_NOT_SUPPORTED,
 * ::CUDA_ERROR_INVALID_VALUE
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphAddNode,
 * ::cuLaunchHostFunc,
 * ::cuGraphHostNodeGetParams,
 * ::cuGraphHostNodeSetParams,
 * ::cuGraphCreate,
 * ::cuGraphDestroyNode,
 * ::cuGraphAddChildGraphNode,
 * ::cuGraphAddEmptyNode,
 * ::cuGraphAddKernelNode,
 * ::cuGraphAddMemcpyNode,
 * ::cuGraphAddMemsetNode
 */
CUresult CUDAAPI cuGraphAddHostNode(CUgraphNode *phGraphNode, CUgraph hGraph, const CUgraphNode *dependencies, size_t numDependencies, const CUDA_HOST_NODE_PARAMS *nodeParams);

/**
 * \brief Returns a host node's parameters
 *
 * Returns the parameters of host node \p hNode in \p nodeParams.
 *
 * \param hNode      - Node to get the parameters for
 * \param nodeParams - Pointer to return the parameters
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuLaunchHostFunc,
 * ::cuGraphAddHostNode,
 * ::cuGraphHostNodeSetParams
 */
CUresult CUDAAPI cuGraphHostNodeGetParams(CUgraphNode hNode, CUDA_HOST_NODE_PARAMS *nodeParams);

/**
 * \brief Sets a host node's parameters
 *
 * Sets the parameters of host node \p hNode to \p nodeParams.
 *
 * \param hNode      - Node to set the parameters for
 * \param nodeParams - Parameters to copy
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphNodeSetParams,
 * ::cuLaunchHostFunc,
 * ::cuGraphAddHostNode,
 * ::cuGraphHostNodeGetParams
 */
CUresult CUDAAPI cuGraphHostNodeSetParams(CUgraphNode hNode, const CUDA_HOST_NODE_PARAMS *nodeParams);

/**
 * \brief Creates a child graph node and adds it to a graph
 *
 * Creates a new node which executes an embedded graph, and adds it to \p hGraph with
 * \p numDependencies dependencies specified via \p dependencies.
 * It is possible for \p numDependencies to be 0, in which case the node will be placed
 * at the root of the graph. \p dependencies may not have any duplicate entries.
 * A handle to the new node will be returned in \p phGraphNode.
 *
 * If \p hGraph contains allocation or free nodes, this call will return an error.
 *
 * The node executes an embedded child graph. The child graph is cloned in this call.
 *
 * \param phGraphNode     - Returns newly created node
 * \param hGraph          - Graph to which to add the node
 * \param dependencies    - Dependencies of the node
 * \param numDependencies - Number of dependencies
 * \param childGraph      - The graph to clone into this node
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE,
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphAddNode,
 * ::cuGraphChildGraphNodeGetGraph,
 * ::cuGraphCreate,
 * ::cuGraphDestroyNode,
 * ::cuGraphAddEmptyNode,
 * ::cuGraphAddKernelNode,
 * ::cuGraphAddHostNode,
 * ::cuGraphAddMemcpyNode,
 * ::cuGraphAddMemsetNode,
 * ::cuGraphClone
 */
CUresult CUDAAPI cuGraphAddChildGraphNode(CUgraphNode *phGraphNode, CUgraph hGraph, const CUgraphNode *dependencies, size_t numDependencies, CUgraph childGraph);

/**
 * \brief Gets a handle to the embedded graph of a child graph node
 *
 * Gets a handle to the embedded graph in a child graph node. This call
 * does not clone the graph. Changes to the graph will be reflected in
 * the node, and the node retains ownership of the graph.
 *
 * Allocation and free nodes cannot be added to the returned graph.
 * Attempting to do so will return an error.
 *
 * \param hNode   - Node to get the embedded graph for
 * \param phGraph - Location to store a handle to the graph
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE,
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphAddChildGraphNode,
 * ::cuGraphNodeFindInClone
 */
CUresult CUDAAPI cuGraphChildGraphNodeGetGraph(CUgraphNode hNode, CUgraph *phGraph);

/**
 * \brief Creates an empty node and adds it to a graph
 *
 * Creates a new node which performs no operation, and adds it to \p hGraph with
 * \p numDependencies dependencies specified via \p dependencies.
 * It is possible for \p numDependencies to be 0, in which case the node will be placed
 * at the root of the graph. \p dependencies may not have any duplicate entries.
 * A handle to the new node will be returned in \p phGraphNode.
 *
 * An empty node performs no operation during execution, but can be used for
 * transitive ordering. For example, a phased execution graph with 2 groups of n
 * nodes with a barrier between them can be represented using an empty node and
 * 2*n dependency edges, rather than no empty node and n^2 dependency edges.
 *
 * \param phGraphNode     - Returns newly created node
 * \param hGraph          - Graph to which to add the node
 * \param dependencies    - Dependencies of the node
 * \param numDependencies - Number of dependencies
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE,
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphAddNode,
 * ::cuGraphCreate,
 * ::cuGraphDestroyNode,
 * ::cuGraphAddChildGraphNode,
 * ::cuGraphAddKernelNode,
 * ::cuGraphAddHostNode,
 * ::cuGraphAddMemcpyNode,
 * ::cuGraphAddMemsetNode
 */
CUresult CUDAAPI cuGraphAddEmptyNode(CUgraphNode *phGraphNode, CUgraph hGraph, const CUgraphNode *dependencies, size_t numDependencies);

/**
 * \brief Creates an event record node and adds it to a graph
 *
 * Creates a new event record node and adds it to \p hGraph with \p numDependencies
 * dependencies specified via \p dependencies and event specified in \p event.
 * It is possible for \p numDependencies to be 0, in which case the node will be placed
 * at the root of the graph. \p dependencies may not have any duplicate entries.
 * A handle to the new node will be returned in \p phGraphNode.
 *
 * Each launch of the graph will record \p event to capture execution of the
 * node's dependencies.
 *
 * \param phGraphNode     - Returns newly created node
 * \param hGraph          - Graph to which to add the node
 * \param dependencies    - Dependencies of the node
 * \param numDependencies - Number of dependencies
 * \param event           - Event for the node
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_NOT_SUPPORTED,
 * ::CUDA_ERROR_INVALID_VALUE
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphAddNode,
 * ::cuGraphAddEventWaitNode,
 * ::cuEventRecordWithFlags,
 * ::cuStreamWaitEvent,
 * ::cuGraphCreate,
 * ::cuGraphDestroyNode,
 * ::cuGraphAddChildGraphNode,
 * ::cuGraphAddEmptyNode,
 * ::cuGraphAddKernelNode,
 * ::cuGraphAddMemcpyNode,
 * ::cuGraphAddMemsetNode
 */
CUresult CUDAAPI cuGraphAddEventRecordNode(CUgraphNode *phGraphNode, CUgraph hGraph, const CUgraphNode *dependencies, size_t numDependencies, CUevent event);

/**
 * \brief Returns the event associated with an event record node
 *
 * Returns the event of event record node \p hNode in \p event_out.
 *
 * \param hNode     - Node to get the event for
 * \param event_out - Pointer to return the event
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphAddEventRecordNode,
 * ::cuGraphEventRecordNodeSetEvent,
 * ::cuGraphEventWaitNodeGetEvent,
 * ::cuEventRecordWithFlags,
 * ::cuStreamWaitEvent
 */
CUresult CUDAAPI cuGraphEventRecordNodeGetEvent(CUgraphNode hNode, CUevent *event_out);

/**
 * \brief Sets an event record node's event
 *
 * Sets the event of event record node \p hNode to \p event.
 *
 * \param hNode - Node to set the event for
 * \param event - Event to use
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_OUT_OF_MEMORY
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphNodeSetParams,
 * ::cuGraphAddEventRecordNode,
 * ::cuGraphEventRecordNodeGetEvent,
 * ::cuGraphEventWaitNodeSetEvent,
 * ::cuEventRecordWithFlags,
 * ::cuStreamWaitEvent
 */
CUresult CUDAAPI cuGraphEventRecordNodeSetEvent(CUgraphNode hNode, CUevent event);

/**
 * \brief Creates an event wait node and adds it to a graph
 *
 * Creates a new event wait node and adds it to \p hGraph with \p numDependencies
 * dependencies specified via \p dependencies and event specified in \p event.
 * It is possible for \p numDependencies to be 0, in which case the node will be placed
 * at the root of the graph. \p dependencies may not have any duplicate entries.
 * A handle to the new node will be returned in \p phGraphNode.
 *
 * The graph node will wait for all work captured in \p event.  See ::cuEventRecord()
 * for details on what is captured by an event. \p event may be from a different context
 * or device than the launch stream.
 *
 * \param phGraphNode     - Returns newly created node
 * \param hGraph          - Graph to which to add the node
 * \param dependencies    - Dependencies of the node
 * \param numDependencies - Number of dependencies
 * \param event           - Event for the node
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_NOT_SUPPORTED,
 * ::CUDA_ERROR_INVALID_VALUE
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphAddNode,
 * ::cuGraphAddEventRecordNode,
 * ::cuEventRecordWithFlags,
 * ::cuStreamWaitEvent,
 * ::cuGraphCreate,
 * ::cuGraphDestroyNode,
 * ::cuGraphAddChildGraphNode,
 * ::cuGraphAddEmptyNode,
 * ::cuGraphAddKernelNode,
 * ::cuGraphAddMemcpyNode,
 * ::cuGraphAddMemsetNode
 */
CUresult CUDAAPI cuGraphAddEventWaitNode(CUgraphNode *phGraphNode, CUgraph hGraph, const CUgraphNode *dependencies, size_t numDependencies, CUevent event);

/**
 * \brief Returns the event associated with an event wait node
 *
 * Returns the event of event wait node \p hNode in \p event_out.
 *
 * \param hNode     - Node to get the event for
 * \param event_out - Pointer to return the event
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphAddEventWaitNode,
 * ::cuGraphEventWaitNodeSetEvent,
 * ::cuGraphEventRecordNodeGetEvent,
 * ::cuEventRecordWithFlags,
 * ::cuStreamWaitEvent
 */
CUresult CUDAAPI cuGraphEventWaitNodeGetEvent(CUgraphNode hNode, CUevent *event_out);

/**
 * \brief Sets an event wait node's event
 *
 * Sets the event of event wait node \p hNode to \p event.
 *
 * \param hNode - Node to set the event for
 * \param event - Event to use
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_OUT_OF_MEMORY
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphNodeSetParams,
 * ::cuGraphAddEventWaitNode,
 * ::cuGraphEventWaitNodeGetEvent,
 * ::cuGraphEventRecordNodeSetEvent,
 * ::cuEventRecordWithFlags,
 * ::cuStreamWaitEvent
 */
CUresult CUDAAPI cuGraphEventWaitNodeSetEvent(CUgraphNode hNode, CUevent event);

/**
 * \brief Creates an external semaphore signal node and adds it to a graph
 *
 * Creates a new external semaphore signal node and adds it to \p hGraph with \p
 * numDependencies dependencies specified via \p dependencies and arguments specified
 * in \p nodeParams. It is possible for \p numDependencies to be 0, in which case the
 * node will be placed at the root of the graph. \p dependencies may not have any
 * duplicate entries. A handle to the new node will be returned in \p phGraphNode.
 *
 * Performs a signal operation on a set of externally allocated semaphore objects
 * when the node is launched.  The operation(s) will occur after all of the node's
 * dependencies have completed.
 *
 * \param phGraphNode     - Returns newly created node
 * \param hGraph          - Graph to which to add the node
 * \param dependencies    - Dependencies of the node
 * \param numDependencies - Number of dependencies
 * \param nodeParams      - Parameters for the node
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_NOT_SUPPORTED,
 * ::CUDA_ERROR_INVALID_VALUE
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphAddNode,
 * ::cuGraphExternalSemaphoresSignalNodeGetParams,
 * ::cuGraphExternalSemaphoresSignalNodeSetParams,
 * ::cuGraphExecExternalSemaphoresSignalNodeSetParams,
 * ::cuGraphAddExternalSemaphoresWaitNode,
 * ::cuImportExternalSemaphore,
 * ::cuSignalExternalSemaphoresAsync,
 * ::cuWaitExternalSemaphoresAsync,
 * ::cuGraphCreate,
 * ::cuGraphDestroyNode,
 * ::cuGraphAddEventRecordNode,
 * ::cuGraphAddEventWaitNode,
 * ::cuGraphAddChildGraphNode,
 * ::cuGraphAddEmptyNode,
 * ::cuGraphAddKernelNode,
 * ::cuGraphAddMemcpyNode,
 * ::cuGraphAddMemsetNode
 */
CUresult CUDAAPI cuGraphAddExternalSemaphoresSignalNode(CUgraphNode *phGraphNode, CUgraph hGraph, const CUgraphNode *dependencies, size_t numDependencies, const CUDA_EXT_SEM_SIGNAL_NODE_PARAMS *nodeParams);

/**
 * \brief Returns an external semaphore signal node's parameters
 *
 * Returns the parameters of an external semaphore signal node \p hNode in \p params_out.
 * The \p extSemArray and \p paramsArray returned in \p params_out,
 * are owned by the node.  This memory remains valid until the node is destroyed or its
 * parameters are modified, and should not be modified
 * directly. Use ::cuGraphExternalSemaphoresSignalNodeSetParams to update the
 * parameters of this node.
 *
 * \param hNode      - Node to get the parameters for
 * \param params_out - Pointer to return the parameters
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuLaunchKernel,
 * ::cuGraphAddExternalSemaphoresSignalNode,
 * ::cuGraphExternalSemaphoresSignalNodeSetParams,
 * ::cuGraphAddExternalSemaphoresWaitNode,
 * ::cuSignalExternalSemaphoresAsync,
 * ::cuWaitExternalSemaphoresAsync
 */
CUresult CUDAAPI cuGraphExternalSemaphoresSignalNodeGetParams(CUgraphNode hNode, CUDA_EXT_SEM_SIGNAL_NODE_PARAMS *params_out);

/**
 * \brief Sets an external semaphore signal node's parameters
 *
 * Sets the parameters of an external semaphore signal node \p hNode to \p nodeParams.
 *
 * \param hNode      - Node to set the parameters for
 * \param nodeParams - Parameters to copy
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_OUT_OF_MEMORY
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphNodeSetParams,
 * ::cuGraphAddExternalSemaphoresSignalNode,
 * ::cuGraphExternalSemaphoresSignalNodeSetParams,
 * ::cuGraphAddExternalSemaphoresWaitNode,
 * ::cuSignalExternalSemaphoresAsync,
 * ::cuWaitExternalSemaphoresAsync
 */
CUresult CUDAAPI cuGraphExternalSemaphoresSignalNodeSetParams(CUgraphNode hNode, const CUDA_EXT_SEM_SIGNAL_NODE_PARAMS *nodeParams);

/**
 * \brief Creates an external semaphore wait node and adds it to a graph
 *
 * Creates a new external semaphore wait node and adds it to \p hGraph with \p numDependencies
 * dependencies specified via \p dependencies and arguments specified in \p nodeParams.
 * It is possible for \p numDependencies to be 0, in which case the node will be placed
 * at the root of the graph. \p dependencies may not have any duplicate entries. A handle
 * to the new node will be returned in \p phGraphNode.
 *
 * Performs a wait operation on a set of externally allocated semaphore objects
 * when the node is launched.  The node's dependencies will not be launched until
 * the wait operation has completed.
 *
 * \param phGraphNode     - Returns newly created node
 * \param hGraph          - Graph to which to add the node
 * \param dependencies    - Dependencies of the node
 * \param numDependencies - Number of dependencies
 * \param nodeParams      - Parameters for the node
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_NOT_SUPPORTED,
 * ::CUDA_ERROR_INVALID_VALUE
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphAddNode,
 * ::cuGraphExternalSemaphoresWaitNodeGetParams,
 * ::cuGraphExternalSemaphoresWaitNodeSetParams,
 * ::cuGraphExecExternalSemaphoresWaitNodeSetParams,
 * ::cuGraphAddExternalSemaphoresSignalNode,
 * ::cuImportExternalSemaphore,
 * ::cuSignalExternalSemaphoresAsync,
 * ::cuWaitExternalSemaphoresAsync,
 * ::cuGraphCreate,
 * ::cuGraphDestroyNode,
 * ::cuGraphAddEventRecordNode,
 * ::cuGraphAddEventWaitNode,
 * ::cuGraphAddChildGraphNode,
 * ::cuGraphAddEmptyNode,
 * ::cuGraphAddKernelNode,
 * ::cuGraphAddMemcpyNode,
 * ::cuGraphAddMemsetNode
 */
CUresult CUDAAPI cuGraphAddExternalSemaphoresWaitNode(CUgraphNode *phGraphNode, CUgraph hGraph, const CUgraphNode *dependencies, size_t numDependencies, const CUDA_EXT_SEM_WAIT_NODE_PARAMS *nodeParams);

/**
 * \brief Returns an external semaphore wait node's parameters
 *
 * Returns the parameters of an external semaphore wait node \p hNode in \p params_out.
 * The \p extSemArray and \p paramsArray returned in \p params_out,
 * are owned by the node.  This memory remains valid until the node is destroyed or its
 * parameters are modified, and should not be modified
 * directly. Use ::cuGraphExternalSemaphoresSignalNodeSetParams to update the
 * parameters of this node.
 *
 * \param hNode      - Node to get the parameters for
 * \param params_out - Pointer to return the parameters
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuLaunchKernel,
 * ::cuGraphAddExternalSemaphoresWaitNode,
 * ::cuGraphExternalSemaphoresWaitNodeSetParams,
 * ::cuGraphAddExternalSemaphoresWaitNode,
 * ::cuSignalExternalSemaphoresAsync,
 * ::cuWaitExternalSemaphoresAsync
 */
CUresult CUDAAPI cuGraphExternalSemaphoresWaitNodeGetParams(CUgraphNode hNode, CUDA_EXT_SEM_WAIT_NODE_PARAMS *params_out);

/**
 * \brief Sets an external semaphore wait node's parameters
 *
 * Sets the parameters of an external semaphore wait node \p hNode to \p nodeParams.
 *
 * \param hNode      - Node to set the parameters for
 * \param nodeParams - Parameters to copy
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_OUT_OF_MEMORY
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphNodeSetParams,
 * ::cuGraphAddExternalSemaphoresWaitNode,
 * ::cuGraphExternalSemaphoresWaitNodeSetParams,
 * ::cuGraphAddExternalSemaphoresWaitNode,
 * ::cuSignalExternalSemaphoresAsync,
 * ::cuWaitExternalSemaphoresAsync
 */
CUresult CUDAAPI cuGraphExternalSemaphoresWaitNodeSetParams(CUgraphNode hNode, const CUDA_EXT_SEM_WAIT_NODE_PARAMS *nodeParams);

/**
 * \brief Creates a batch memory operation node and adds it to a graph
 *
 * Creates a new batch memory operation node and adds it to \p hGraph with \p
 * numDependencies dependencies specified via \p dependencies and arguments specified in \p nodeParams.
 * It is possible for \p numDependencies to be 0, in which case the node will be placed
 * at the root of the graph. \p dependencies may not have any duplicate entries.
 * A handle to the new node will be returned in \p phGraphNode.
 *
 * When the node is added, the paramArray inside \p nodeParams is copied and therefore it can be
 * freed after the call returns.
 *
 * \note
 * Warning:
 * Improper use of this API may deadlock the application. Synchronization 
 * ordering established through this API is not visible to CUDA. CUDA tasks 
 * that are (even indirectly) ordered by this API should also have that order
 * expressed with CUDA-visible dependencies such as events. This ensures that 
 * the scheduler does not serialize them in an improper order. For more 
 * information, see the Stream Memory Operations section in the programming 
 * guide(https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html).
 *
 * \param phGraphNode     - Returns newly created node
 * \param hGraph          - Graph to which to add the node
 * \param dependencies    - Dependencies of the node
 * \param numDependencies - Number of dependencies
 * \param nodeParams      - Parameters for the node
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_NOT_SUPPORTED,
 * ::CUDA_ERROR_INVALID_VALUE
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphAddNode,
 * ::cuStreamBatchMemOp,
 * ::cuStreamWaitValue32,
 * ::cuStreamWriteValue32,
 * ::cuStreamWaitValue64,
 * ::cuStreamWriteValue64,
 * ::cuGraphBatchMemOpNodeGetParams,
 * ::cuGraphBatchMemOpNodeSetParams,
 * ::cuGraphCreate,
 * ::cuGraphDestroyNode,
 * ::cuGraphAddChildGraphNode,
 * ::cuGraphAddEmptyNode,
 * ::cuGraphAddKernelNode,
 * ::cuGraphAddMemcpyNode,
 * ::cuGraphAddMemsetNode
 */
CUresult CUDAAPI cuGraphAddBatchMemOpNode(CUgraphNode *phGraphNode, CUgraph hGraph, const CUgraphNode *dependencies, size_t numDependencies, const CUDA_BATCH_MEM_OP_NODE_PARAMS *nodeParams);

/**
 * \brief Returns a batch mem op node's parameters
 *
 * Returns the parameters of batch mem op node \p hNode in \p nodeParams_out.
 * The \p paramArray returned in \p nodeParams_out is owned by the node.
 * This memory remains valid until the node is destroyed or its
 * parameters are modified, and should not be modified
 * directly. Use ::cuGraphBatchMemOpNodeSetParams to update the
 * parameters of this node.
 *
 * \param hNode          - Node to get the parameters for
 * \param nodeParams_out - Pointer to return the parameters
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuStreamBatchMemOp,
 * ::cuGraphAddBatchMemOpNode,
 * ::cuGraphBatchMemOpNodeSetParams
 */
CUresult CUDAAPI cuGraphBatchMemOpNodeGetParams(CUgraphNode hNode, CUDA_BATCH_MEM_OP_NODE_PARAMS *nodeParams_out);

/**
 * \brief Sets a batch mem op node's parameters
 *
 * Sets the parameters of batch mem op node \p hNode to \p nodeParams.
 *
 * The paramArray inside \p nodeParams is copied and therefore it can be
 * freed after the call returns.
 *
 * \param hNode      - Node to set the parameters for
 * \param nodeParams - Parameters to copy
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_OUT_OF_MEMORY
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphNodeSetParams,
 * ::cuStreamBatchMemOp,
 * ::cuGraphAddBatchMemOpNode,
 * ::cuGraphBatchMemOpNodeGetParams
 */
CUresult CUDAAPI cuGraphBatchMemOpNodeSetParams(CUgraphNode hNode, const CUDA_BATCH_MEM_OP_NODE_PARAMS *nodeParams);

/**
 * \brief Sets the parameters for a batch mem op node in the given graphExec
 *
 * Sets the parameters of a batch mem op node in an executable graph \p hGraphExec.
 * The node is identified by the corresponding node \p hNode in the
 * non-executable graph, from which the executable graph was instantiated.
 *
 * The following fields on operations may be modified on an executable graph:
 *
 *  op.waitValue.address
 *  op.waitValue.value[64]
 *  op.waitValue.flags bits corresponding to wait type (i.e. CU_STREAM_WAIT_VALUE_FLUSH bit cannot be modified)
 *  op.writeValue.address
 *  op.writeValue.value[64]
 *
 * Other fields, such as the context, count or type of operations, and other types of operations such as membars, 
 * may not be modified.
 *
 * \p hNode must not have been removed from the original graph.
 *
 * The modifications only affect future launches of \p hGraphExec. Already
 * enqueued or running launches of \p hGraphExec are not affected by this call.
 * \p hNode is also not modified by this call.
 *
 * The paramArray inside \p nodeParams is copied and therefore it can be
 * freed after the call returns.
 *
 * \param hGraphExec - The executable graph in which to set the specified node
 * \param hNode      - Batch mem op node from the graph from which graphExec was instantiated
 * \param nodeParams - Updated Parameters to set
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphExecNodeSetParams,
 * ::cuStreamBatchMemOp,
 * ::cuGraphAddBatchMemOpNode,
 * ::cuGraphBatchMemOpNodeGetParams,
 * ::cuGraphBatchMemOpNodeSetParams,
 * ::cuGraphInstantiate
 */
CUresult CUDAAPI cuGraphExecBatchMemOpNodeSetParams(CUgraphExec hGraphExec, CUgraphNode hNode, const CUDA_BATCH_MEM_OP_NODE_PARAMS *nodeParams);

/**
 * \brief Creates an allocation node and adds it to a graph
 *
 * Creates a new allocation node and adds it to \p hGraph with \p numDependencies
 * dependencies specified via \p dependencies and arguments specified in \p nodeParams.
 * It is possible for \p numDependencies to be 0, in which case the node will be placed
 * at the root of the graph. \p dependencies may not have any duplicate entries. A handle
 * to the new node will be returned in \p phGraphNode.
 *
 * \param phGraphNode     - Returns newly created node
 * \param hGraph          - Graph to which to add the node
 * \param dependencies    - Dependencies of the node
 * \param numDependencies - Number of dependencies
 * \param nodeParams      - Parameters for the node
 *
 * When ::cuGraphAddMemAllocNode creates an allocation node, it returns the address of the allocation in
 * \p nodeParams.dptr.  The allocation's address remains fixed across instantiations and launches.
 *
 * If the allocation is freed in the same graph, by creating a free node using ::cuGraphAddMemFreeNode,
 * the allocation can be accessed by nodes ordered after the allocation node but before the free node.
 * These allocations cannot be freed outside the owning graph, and they can only be freed once in the
 * owning graph.
 *
 * If the allocation is not freed in the same graph, then it can be accessed not only by nodes in the
 * graph which are ordered after the allocation node, but also by stream operations ordered after the
 * graph's execution but before the allocation is freed.
 *
 * Allocations which are not freed in the same graph can be freed by:
 * - passing the allocation to ::cuMemFreeAsync or ::cuMemFree;
 * - launching a graph with a free node for that allocation; or
 * - specifying ::CUDA_GRAPH_INSTANTIATE_FLAG_AUTO_FREE_ON_LAUNCH during instantiation, which makes
 * each launch behave as though it called ::cuMemFreeAsync for every unfreed allocation.
 * 
 * It is not possible to free an allocation in both the owning graph and another graph.  If the allocation
 * is freed in the same graph, a free node cannot be added to another graph.  If the allocation is freed
 * in another graph, a free node can no longer be added to the owning graph.
 *
 * The following restrictions apply to graphs which contain allocation and/or memory free nodes:
 * - Nodes and edges of the graph cannot be deleted.
 * - The graph cannot be used in a child node.
 * - Only one instantiation of the graph may exist at any point in time.
 * - The graph cannot be cloned.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_NOT_SUPPORTED,
 * ::CUDA_ERROR_INVALID_VALUE
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphAddNode,
 * ::cuGraphAddMemFreeNode,
 * ::cuGraphMemAllocNodeGetParams,
 * ::cuDeviceGraphMemTrim,
 * ::cuDeviceGetGraphMemAttribute,
 * ::cuDeviceSetGraphMemAttribute,
 * ::cuMemAllocAsync,
 * ::cuMemFreeAsync,
 * ::cuGraphCreate,
 * ::cuGraphDestroyNode,
 * ::cuGraphAddChildGraphNode,
 * ::cuGraphAddEmptyNode,
 * ::cuGraphAddEventRecordNode,
 * ::cuGraphAddEventWaitNode,
 * ::cuGraphAddExternalSemaphoresSignalNode,
 * ::cuGraphAddExternalSemaphoresWaitNode,
 * ::cuGraphAddKernelNode,
 * ::cuGraphAddMemcpyNode,
 * ::cuGraphAddMemsetNode
 */
CUresult CUDAAPI cuGraphAddMemAllocNode(CUgraphNode *phGraphNode, CUgraph hGraph, const CUgraphNode *dependencies, size_t numDependencies, CUDA_MEM_ALLOC_NODE_PARAMS *nodeParams);

/**
 * \brief Returns a memory alloc node's parameters
 *
 * Returns the parameters of a memory alloc node \p hNode in \p params_out.
 * The \p poolProps and \p accessDescs returned in \p params_out, are owned by the
 * node.  This memory remains valid until the node is destroyed.  The returned
 * parameters must not be modified.
 *
 * \param hNode      - Node to get the parameters for
 * \param params_out - Pointer to return the parameters
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphAddMemAllocNode,
 * ::cuGraphMemFreeNodeGetParams
 */
CUresult CUDAAPI cuGraphMemAllocNodeGetParams(CUgraphNode hNode, CUDA_MEM_ALLOC_NODE_PARAMS *params_out);

/**
 * \brief Creates a memory free node and adds it to a graph
 *
 * Creates a new memory free node and adds it to \p hGraph with \p numDependencies
 * dependencies specified via \p dependencies and arguments specified in \p nodeParams.
 * It is possible for \p numDependencies to be 0, in which case the node will be placed
 * at the root of the graph. \p dependencies may not have any duplicate entries. A handle
 * to the new node will be returned in \p phGraphNode.
 *
 * \param phGraphNode     - Returns newly created node
 * \param hGraph          - Graph to which to add the node
 * \param dependencies    - Dependencies of the node
 * \param numDependencies - Number of dependencies
 * \param dptr            - Address of memory to free
 *
 * ::cuGraphAddMemFreeNode will return ::CUDA_ERROR_INVALID_VALUE if the user attempts to free:
 * - an allocation twice in the same graph.
 * - an address that was not returned by an allocation node.
 * - an invalid address.
 *
 * The following restrictions apply to graphs which contain allocation and/or memory free nodes:
 * - Nodes and edges of the graph cannot be deleted.
 * - The graph cannot be used in a child node.
 * - Only one instantiation of the graph may exist at any point in time.
 * - The graph cannot be cloned.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_NOT_SUPPORTED,
 * ::CUDA_ERROR_INVALID_VALUE
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphAddNode,
 * ::cuGraphAddMemAllocNode,
 * ::cuGraphMemFreeNodeGetParams,
 * ::cuDeviceGraphMemTrim,
 * ::cuDeviceGetGraphMemAttribute,
 * ::cuDeviceSetGraphMemAttribute,
 * ::cuMemAllocAsync,
 * ::cuMemFreeAsync,
 * ::cuGraphCreate,
 * ::cuGraphDestroyNode,
 * ::cuGraphAddChildGraphNode,
 * ::cuGraphAddEmptyNode,
 * ::cuGraphAddEventRecordNode,
 * ::cuGraphAddEventWaitNode,
 * ::cuGraphAddExternalSemaphoresSignalNode,
 * ::cuGraphAddExternalSemaphoresWaitNode,
 * ::cuGraphAddKernelNode,
 * ::cuGraphAddMemcpyNode,
 * ::cuGraphAddMemsetNode
 */
CUresult CUDAAPI cuGraphAddMemFreeNode(CUgraphNode *phGraphNode, CUgraph hGraph, const CUgraphNode *dependencies, size_t numDependencies, CUdeviceptr dptr);

/**
 * \brief Returns a memory free node's parameters
 *
 * Returns the address of a memory free node \p hNode in \p dptr_out.
 *
 * \param hNode    - Node to get the parameters for
 * \param dptr_out - Pointer to return the device address
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphAddMemFreeNode,
 * ::cuGraphMemAllocNodeGetParams
 */
CUresult CUDAAPI cuGraphMemFreeNodeGetParams(CUgraphNode hNode, CUdeviceptr *dptr_out);

/**
 * \brief Free unused memory that was cached on the specified device for use with graphs back to the OS.
 *
 * Blocks which are not in use by a graph that is either currently executing or scheduled to execute are
 * freed back to the operating system.
 *
 * \param device - The device for which cached memory should be freed.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_DEVICE
 *
 * \sa
 * ::cuGraphAddMemAllocNode,
 * ::cuGraphAddMemFreeNode,
 * ::cuDeviceSetGraphMemAttribute,
 * ::cuDeviceGetGraphMemAttribute
 */
CUresult CUDAAPI cuDeviceGraphMemTrim(CUdevice device);

/**
 * \brief Query asynchronous allocation attributes related to graphs
 *
 * Valid attributes are:
 *
 * - ::CU_GRAPH_MEM_ATTR_USED_MEM_CURRENT: Amount of memory, in bytes, currently associated with graphs
 * - ::CU_GRAPH_MEM_ATTR_USED_MEM_HIGH: High watermark of memory, in bytes, associated with graphs since the
 *   last time it was reset.  High watermark can only be reset to zero.
 * - ::CU_GRAPH_MEM_ATTR_RESERVED_MEM_CURRENT: Amount of memory, in bytes, currently allocated for use by
 *   the CUDA graphs asynchronous allocator.
 * - ::CU_GRAPH_MEM_ATTR_RESERVED_MEM_HIGH: High watermark of memory, in bytes, currently allocated for use by
 *   the CUDA graphs asynchronous allocator.
 *
 * \param device - Specifies the scope of the query
 * \param attr - attribute to get
 * \param value - retrieved value
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_DEVICE
 *
 * \sa
 * ::cuDeviceSetGraphMemAttribute,
 * ::cuGraphAddMemAllocNode,
 * ::cuGraphAddMemFreeNode
 */
CUresult CUDAAPI cuDeviceGetGraphMemAttribute(CUdevice device, CUgraphMem_attribute attr, void* value);

/**
 * \brief Set asynchronous allocation attributes related to graphs
 *
 * Valid attributes are:
 *
 * - ::CU_GRAPH_MEM_ATTR_USED_MEM_HIGH: High watermark of memory, in bytes, associated with graphs since the
 *   last time it was reset.  High watermark can only be reset to zero.
 * - ::CU_GRAPH_MEM_ATTR_RESERVED_MEM_HIGH: High watermark of memory, in bytes, currently allocated for use by
 *   the CUDA graphs asynchronous allocator.
 *
 * \param device - Specifies the scope of the query
 * \param attr - attribute to get
 * \param value - pointer to value to set
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_DEVICE
 *
 * \sa
 * ::cuDeviceGetGraphMemAttribute,
 * ::cuGraphAddMemAllocNode,
 * ::cuGraphAddMemFreeNode
 */
CUresult CUDAAPI cuDeviceSetGraphMemAttribute(CUdevice device, CUgraphMem_attribute attr, void* value);

/**
 * \brief Clones a graph
 *
 * This function creates a copy of \p originalGraph and returns it in \p phGraphClone.
 * All parameters are copied into the cloned graph. The original graph may be modified
 * after this call without affecting the clone.
 *
 * Child graph nodes in the original graph are recursively copied into the clone.
 *
 * \param phGraphClone  - Returns newly created cloned graph
 * \param originalGraph - Graph to clone
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_OUT_OF_MEMORY
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphCreate,
 * ::cuGraphNodeFindInClone
 */
CUresult CUDAAPI cuGraphClone(CUgraph *phGraphClone, CUgraph originalGraph);

/**
 * \brief Finds a cloned version of a node
 *
 * This function returns the node in \p hClonedGraph corresponding to \p hOriginalNode
 * in the original graph.
 *
 * \p hClonedGraph must have been cloned from \p hOriginalGraph via ::cuGraphClone.
 * \p hOriginalNode must have been in \p hOriginalGraph at the time of the call to
 * ::cuGraphClone, and the corresponding cloned node in \p hClonedGraph must not have
 * been removed. The cloned node is then returned via \p phClonedNode.
 *
 * \param phNode  - Returns handle to the cloned node
 * \param hOriginalNode - Handle to the original node
 * \param hClonedGraph - Cloned graph to query
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphClone
 */
CUresult CUDAAPI cuGraphNodeFindInClone(CUgraphNode *phNode, CUgraphNode hOriginalNode, CUgraph hClonedGraph);

/**
 * \brief Returns a node's type
 *
 * Returns the node type of \p hNode in \p type.
 *
 * \param hNode - Node to query
 * \param type  - Pointer to return the node type
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphGetNodes,
 * ::cuGraphGetRootNodes,
 * ::cuGraphChildGraphNodeGetGraph,
 * ::cuGraphKernelNodeGetParams,
 * ::cuGraphKernelNodeSetParams,
 * ::cuGraphHostNodeGetParams,
 * ::cuGraphHostNodeSetParams,
 * ::cuGraphMemcpyNodeGetParams,
 * ::cuGraphMemcpyNodeSetParams,
 * ::cuGraphMemsetNodeGetParams,
 * ::cuGraphMemsetNodeSetParams
 */
CUresult CUDAAPI cuGraphNodeGetType(CUgraphNode hNode, CUgraphNodeType *type);

/**
 * \brief Returns a graph's nodes
 *
 * Returns a list of \p hGraph's nodes. \p nodes may be NULL, in which case this
 * function will return the number of nodes in \p numNodes. Otherwise,
 * \p numNodes entries will be filled in. If \p numNodes is higher than the actual
 * number of nodes, the remaining entries in \p nodes will be set to NULL, and the
 * number of nodes actually obtained will be returned in \p numNodes.
 *
 * \param hGraph   - Graph to query
 * \param nodes    - Pointer to return the nodes
 * \param numNodes - See description
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphCreate,
 * ::cuGraphGetRootNodes,
 * ::cuGraphGetEdges,
 * ::cuGraphNodeGetType,
 * ::cuGraphNodeGetDependencies,
 * ::cuGraphNodeGetDependentNodes
 */
CUresult CUDAAPI cuGraphGetNodes(CUgraph hGraph, CUgraphNode *nodes, size_t *numNodes);

/**
 * \brief Returns a graph's root nodes
 *
 * Returns a list of \p hGraph's root nodes. \p rootNodes may be NULL, in which case this
 * function will return the number of root nodes in \p numRootNodes. Otherwise,
 * \p numRootNodes entries will be filled in. If \p numRootNodes is higher than the actual
 * number of root nodes, the remaining entries in \p rootNodes will be set to NULL, and the
 * number of nodes actually obtained will be returned in \p numRootNodes.
 *
 * \param hGraph       - Graph to query
 * \param rootNodes    - Pointer to return the root nodes
 * \param numRootNodes - See description
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphCreate,
 * ::cuGraphGetNodes,
 * ::cuGraphGetEdges,
 * ::cuGraphNodeGetType,
 * ::cuGraphNodeGetDependencies,
 * ::cuGraphNodeGetDependentNodes
 */
CUresult CUDAAPI cuGraphGetRootNodes(CUgraph hGraph, CUgraphNode *rootNodes, size_t *numRootNodes);

/**
 * \brief Returns a graph's dependency edges
 *
 * Returns a list of \p hGraph's dependency edges. Edges are returned via corresponding
 * indices in \p from and \p to; that is, the node in \p to[i] has a dependency on the
 * node in \p from[i]. \p from and \p to may both be NULL, in which
 * case this function only returns the number of edges in \p numEdges. Otherwise,
 * \p numEdges entries will be filled in. If \p numEdges is higher than the actual
 * number of edges, the remaining entries in \p from and \p to will be set to NULL, and
 * the number of edges actually returned will be written to \p numEdges.
 *
 * \param hGraph   - Graph to get the edges from
 * \param from     - Location to return edge endpoints
 * \param to       - Location to return edge endpoints
 * \param numEdges - See description
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphGetNodes,
 * ::cuGraphGetRootNodes,
 * ::cuGraphAddDependencies,
 * ::cuGraphRemoveDependencies,
 * ::cuGraphNodeGetDependencies,
 * ::cuGraphNodeGetDependentNodes
 */
CUresult CUDAAPI cuGraphGetEdges(CUgraph hGraph, CUgraphNode *from, CUgraphNode *to, size_t *numEdges);

/**
 * \brief Returns a graph's dependency edges (12.3+)
 *
 * Returns a list of \p hGraph's dependency edges. Edges are returned via corresponding
 * indices in \p from, \p to and \p edgeData; that is, the node in \p to[i] has a
 * dependency on the node in \p from[i] with data \p edgeData[i]. \p from and \p to may
 * both be NULL, in which case this function only returns the number of edges in
 * \p numEdges. Otherwise, \p numEdges entries will be filled in. If \p numEdges is higher
 * than the actual number of edges, the remaining entries in \p from and \p to will be
 * set to NULL, and the number of edges actually returned will be written to \p numEdges.
 * \p edgeData may alone be NULL, in which case the edges must all have default (zeroed)
 * edge data. Attempting a lossy query via NULL \p edgeData will result in
 * ::CUDA_ERROR_LOSSY_QUERY. If \p edgeData is non-NULL then \p from and \p to must be
 * as well.
 *
 * \param hGraph   - Graph to get the edges from
 * \param from     - Location to return edge endpoints
 * \param to       - Location to return edge endpoints
 * \param edgeData - Optional location to return edge data
 * \param numEdges - See description
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_LOSSY_QUERY,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphGetNodes,
 * ::cuGraphGetRootNodes,
 * ::cuGraphAddDependencies,
 * ::cuGraphRemoveDependencies,
 * ::cuGraphNodeGetDependencies,
 * ::cuGraphNodeGetDependentNodes
 */
CUresult CUDAAPI cuGraphGetEdges_v2(CUgraph hGraph, CUgraphNode *from, CUgraphNode *to, CUgraphEdgeData *edgeData, size_t *numEdges);

/**
 * \brief Returns a node's dependencies
 *
 * Returns a list of \p node's dependencies. \p dependencies may be NULL, in which case this
 * function will return the number of dependencies in \p numDependencies. Otherwise,
 * \p numDependencies entries will be filled in. If \p numDependencies is higher than the actual
 * number of dependencies, the remaining entries in \p dependencies will be set to NULL, and the
 * number of nodes actually obtained will be returned in \p numDependencies.
 *
 * \param hNode           - Node to query
 * \param dependencies    - Pointer to return the dependencies
 * \param numDependencies - See description
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphNodeGetDependentNodes,
 * ::cuGraphGetNodes,
 * ::cuGraphGetRootNodes,
 * ::cuGraphGetEdges,
 * ::cuGraphAddDependencies,
 * ::cuGraphRemoveDependencies
 */
CUresult CUDAAPI cuGraphNodeGetDependencies(CUgraphNode hNode, CUgraphNode *dependencies, size_t *numDependencies);

/**
 * \brief Returns a node's dependencies (12.3+)
 *
 * Returns a list of \p node's dependencies. \p dependencies may be NULL, in which case this
 * function will return the number of dependencies in \p numDependencies. Otherwise,
 * \p numDependencies entries will be filled in. If \p numDependencies is higher than the actual
 * number of dependencies, the remaining entries in \p dependencies will be set to NULL, and the
 * number of nodes actually obtained will be returned in \p numDependencies.
 *
 * Note that if an edge has non-zero (non-default) edge data and \p edgeData is NULL,
 * this API will return ::CUDA_ERROR_LOSSY_QUERY. If \p edgeData is non-NULL, then
 * \p dependencies must be as well.
 *
 * \param hNode           - Node to query
 * \param dependencies    - Pointer to return the dependencies
 * \param edgeData        - Optional array to return edge data for each dependency
 * \param numDependencies - See description
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_LOSSY_QUERY,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphNodeGetDependentNodes,
 * ::cuGraphGetNodes,
 * ::cuGraphGetRootNodes,
 * ::cuGraphGetEdges,
 * ::cuGraphAddDependencies,
 * ::cuGraphRemoveDependencies
 */
CUresult CUDAAPI cuGraphNodeGetDependencies_v2(CUgraphNode hNode, CUgraphNode *dependencies, CUgraphEdgeData *edgeData, size_t *numDependencies);

/**
 * \brief Returns a node's dependent nodes
 *
 * Returns a list of \p node's dependent nodes. \p dependentNodes may be NULL, in which
 * case this function will return the number of dependent nodes in \p numDependentNodes.
 * Otherwise, \p numDependentNodes entries will be filled in. If \p numDependentNodes is
 * higher than the actual number of dependent nodes, the remaining entries in
 * \p dependentNodes will be set to NULL, and the number of nodes actually obtained will
 * be returned in \p numDependentNodes.
 *
 * \param hNode             - Node to query
 * \param dependentNodes    - Pointer to return the dependent nodes
 * \param numDependentNodes - See description
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphNodeGetDependencies,
 * ::cuGraphGetNodes,
 * ::cuGraphGetRootNodes,
 * ::cuGraphGetEdges,
 * ::cuGraphAddDependencies,
 * ::cuGraphRemoveDependencies
 */
CUresult CUDAAPI cuGraphNodeGetDependentNodes(CUgraphNode hNode, CUgraphNode *dependentNodes, size_t *numDependentNodes);

/**
 * \brief Returns a node's dependent nodes (12.3+)
 *
 * Returns a list of \p node's dependent nodes. \p dependentNodes may be NULL, in which
 * case this function will return the number of dependent nodes in \p numDependentNodes.
 * Otherwise, \p numDependentNodes entries will be filled in. If \p numDependentNodes is
 * higher than the actual number of dependent nodes, the remaining entries in
 * \p dependentNodes will be set to NULL, and the number of nodes actually obtained will
 * be returned in \p numDependentNodes.
 *
 * Note that if an edge has non-zero (non-default) edge data and \p edgeData is NULL,
 * this API will return ::CUDA_ERROR_LOSSY_QUERY.  If \p edgeData is non-NULL, then
 * \p dependentNodes must be as well.
 *
 * \param hNode             - Node to query
 * \param dependentNodes    - Pointer to return the dependent nodes
 * \param edgeData          - Optional pointer to return edge data for dependent nodes
 * \param numDependentNodes - See description
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_LOSSY_QUERY,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphNodeGetDependencies,
 * ::cuGraphGetNodes,
 * ::cuGraphGetRootNodes,
 * ::cuGraphGetEdges,
 * ::cuGraphAddDependencies,
 * ::cuGraphRemoveDependencies
 */
CUresult CUDAAPI cuGraphNodeGetDependentNodes_v2(CUgraphNode hNode, CUgraphNode *dependentNodes, CUgraphEdgeData *edgeData, size_t *numDependentNodes);

/**
 * \brief Adds dependency edges to a graph
 *
 * The number of dependencies to be added is defined by \p numDependencies
 * Elements in \p from and \p to at corresponding indices define a dependency.
 * Each node in \p from and \p to must belong to \p hGraph.
 *
 * If \p numDependencies is 0, elements in \p from and \p to will be ignored.
 * Specifying an existing dependency will return an error.
 *
 * \param hGraph - Graph to which dependencies are added
 * \param from - Array of nodes that provide the dependencies
 * \param to - Array of dependent nodes
 * \param numDependencies - Number of dependencies to be added
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphRemoveDependencies,
 * ::cuGraphGetEdges,
 * ::cuGraphNodeGetDependencies,
 * ::cuGraphNodeGetDependentNodes
 */
CUresult CUDAAPI cuGraphAddDependencies(CUgraph hGraph, const CUgraphNode *from, const CUgraphNode *to, size_t numDependencies);

/**
 * \brief Adds dependency edges to a graph (12.3+)
 *
 * The number of dependencies to be added is defined by \p numDependencies
 * Elements in \p from and \p to at corresponding indices define a dependency.
 * Each node in \p from and \p to must belong to \p hGraph.
 *
 * If \p numDependencies is 0, elements in \p from and \p to will be ignored.
 * Specifying an existing dependency will return an error.
 *
 * \param hGraph - Graph to which dependencies are added
 * \param from - Array of nodes that provide the dependencies
 * \param to - Array of dependent nodes
 * \param edgeData - Optional array of edge data. If NULL, default (zeroed) edge data is assumed.
 * \param numDependencies - Number of dependencies to be added
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphRemoveDependencies,
 * ::cuGraphGetEdges,
 * ::cuGraphNodeGetDependencies,
 * ::cuGraphNodeGetDependentNodes
 */
CUresult CUDAAPI cuGraphAddDependencies_v2(CUgraph hGraph, const CUgraphNode *from, const CUgraphNode *to, const CUgraphEdgeData *edgeData, size_t numDependencies);

/**
 * \brief Removes dependency edges from a graph
 *
 * The number of \p dependencies to be removed is defined by \p numDependencies.
 * Elements in \p from and \p to at corresponding indices define a dependency.
 * Each node in \p from and \p to must belong to \p hGraph.
 *
 * If \p numDependencies is 0, elements in \p from and \p to will be ignored.
 * Specifying a non-existing dependency will return an error.
 *
 * Dependencies cannot be removed from graphs which contain allocation or free nodes.
 * Any attempt to do so will return an error.
 *
 * \param hGraph - Graph from which to remove dependencies
 * \param from - Array of nodes that provide the dependencies
 * \param to - Array of dependent nodes
 * \param numDependencies - Number of dependencies to be removed
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphAddDependencies,
 * ::cuGraphGetEdges,
 * ::cuGraphNodeGetDependencies,
 * ::cuGraphNodeGetDependentNodes
 */
CUresult CUDAAPI cuGraphRemoveDependencies(CUgraph hGraph, const CUgraphNode *from, const CUgraphNode *to, size_t numDependencies);

/**
 * \brief Removes dependency edges from a graph (12.3+)
 *
 * The number of \p dependencies to be removed is defined by \p numDependencies.
 * Elements in \p from and \p to at corresponding indices define a dependency.
 * Each node in \p from and \p to must belong to \p hGraph.
 *
 * If \p numDependencies is 0, elements in \p from and \p to will be ignored.
 * Specifying an edge that does not exist in the graph, with data matching
 * \p edgeData, results in an error. \p edgeData is nullable, which is equivalent
 * to passing default (zeroed) data for each edge.
 *
 * Dependencies cannot be removed from graphs which contain allocation or free nodes.
 * Any attempt to do so will return an error.
 *
 * \param hGraph - Graph from which to remove dependencies
 * \param from - Array of nodes that provide the dependencies
 * \param to - Array of dependent nodes
 * \param edgeData - Optional array of edge data. If NULL, edge data is assumed to
 *                   be default (zeroed).
 * \param numDependencies - Number of dependencies to be removed
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphAddDependencies,
 * ::cuGraphGetEdges,
 * ::cuGraphNodeGetDependencies,
 * ::cuGraphNodeGetDependentNodes
 */
CUresult CUDAAPI cuGraphRemoveDependencies_v2(CUgraph hGraph, const CUgraphNode *from, const CUgraphNode *to, const CUgraphEdgeData *edgeData, size_t numDependencies);

/**
 * \brief Remove a node from the graph
 *
 * Removes \p hNode from its graph. This operation also severs any dependencies of other nodes
 * on \p hNode and vice versa.
 *
 * Nodes which belong to a graph which contains allocation or free nodes cannot be destroyed.
 * Any attempt to do so will return an error.
 *
 * \param hNode  - Node to remove
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphAddChildGraphNode,
 * ::cuGraphAddEmptyNode,
 * ::cuGraphAddKernelNode,
 * ::cuGraphAddHostNode,
 * ::cuGraphAddMemcpyNode,
 * ::cuGraphAddMemsetNode
 */
CUresult CUDAAPI cuGraphDestroyNode(CUgraphNode hNode);

/**
 * \brief Creates an executable graph from a graph
 *
 * Instantiates \p hGraph as an executable graph. The graph is validated for any
 * structural constraints or intra-node constraints which were not previously
 * validated. If instantiation is successful, a handle to the instantiated graph
 * is returned in \p phGraphExec.
 *
 * The \p flags parameter controls the behavior of instantiation and subsequent
 * graph launches.  Valid flags are:
 *
 * - ::CUDA_GRAPH_INSTANTIATE_FLAG_AUTO_FREE_ON_LAUNCH, which configures a
 * graph containing memory allocation nodes to automatically free any
 * unfreed memory allocations before the graph is relaunched.
 *
 * - ::CUDA_GRAPH_INSTANTIATE_FLAG_DEVICE_LAUNCH, which configures the graph for launch
 * from the device. If this flag is passed, the executable graph handle returned can be
 * used to launch the graph from both the host and device. This flag can only be used
 * on platforms which support unified addressing. This flag cannot be used in
 * conjunction with ::CUDA_GRAPH_INSTANTIATE_FLAG_AUTO_FREE_ON_LAUNCH.
 *
 * - ::CUDA_GRAPH_INSTANTIATE_FLAG_USE_NODE_PRIORITY, which causes the graph
 * to use the priorities from the per-node attributes rather than the priority
 * of the launch stream during execution. Note that priorities are only available
 * on kernel nodes, and are copied from stream priority during stream capture.
 *
 * If \p hGraph contains any allocation or free nodes, there can be at most one
 * executable graph in existence for that graph at a time. An attempt to instantiate
 * a second executable graph before destroying the first with ::cuGraphExecDestroy
 * will result in an error.
 * The same also applies if \p hGraph contains any device-updatable kernel nodes.
 *
 * If \p hGraph contains kernels which call device-side cudaGraphLaunch() from multiple
 * contexts, this will result in an error.
 *
 * Graphs instantiated for launch on the device have additional restrictions which do not
 * apply to host graphs:
 *
 * - The graph's nodes must reside on a single context.
 * - The graph can only contain kernel nodes, memcpy nodes, memset nodes, and child graph nodes.
 * - The graph cannot be empty and must contain at least one kernel, memcpy, or memset node.
 *   Operation-specific restrictions are outlined below.
 * - Kernel nodes:
 *   - Use of CUDA Dynamic Parallelism is not permitted.
 *   - Cooperative launches are permitted as long as MPS is not in use.
 * - Memcpy nodes:
 *   - Only copies involving device memory and/or pinned device-mapped host memory are permitted.
 *   - Copies involving CUDA arrays are not permitted.
 *   - Both operands must be accessible from the current context, and the current context must
 *     match the context of other nodes in the graph.
 *
 * \param phGraphExec - Returns instantiated graph
 * \param hGraph      - Graph to instantiate
 * \param flags       - Flags to control instantiation.  See ::CUgraphInstantiate_flags.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphInstantiate,
 * ::cuGraphCreate,
 * ::cuGraphUpload,
 * ::cuGraphLaunch,
 * ::cuGraphExecDestroy
 */
CUresult CUDAAPI cuGraphInstantiate(CUgraphExec *phGraphExec, CUgraph hGraph, unsigned long long flags);

/**
 * \brief Creates an executable graph from a graph
 *
 * Instantiates \p hGraph as an executable graph according to the \p instantiateParams structure.
 * The graph is validated for any structural constraints or intra-node constraints
 * which were not previously validated. If instantiation is successful, a handle to
 * the instantiated graph is returned in \p phGraphExec.
 *
 * \p instantiateParams controls the behavior of instantiation and subsequent
 * graph launches, as well as returning more detailed information in the event of an error.
 * ::CUDA_GRAPH_INSTANTIATE_PARAMS is defined as:
 *
 * \code
    typedef struct {
        cuuint64_t flags;
        CUstream hUploadStream;
        CUgraphNode hErrNode_out;
        CUgraphInstantiateResult result_out;
    } CUDA_GRAPH_INSTANTIATE_PARAMS;
 * \endcode
 *
 * The \p flags field controls the behavior of instantiation and subsequent
 * graph launches. Valid flags are:
 *
 * - ::CUDA_GRAPH_INSTANTIATE_FLAG_AUTO_FREE_ON_LAUNCH, which configures a
 * graph containing memory allocation nodes to automatically free any
 * unfreed memory allocations before the graph is relaunched.
 *
 * - ::CUDA_GRAPH_INSTANTIATE_FLAG_UPLOAD, which will perform an upload of the graph
 * into \p hUploadStream once the graph has been instantiated.
 *
 * - ::CUDA_GRAPH_INSTANTIATE_FLAG_DEVICE_LAUNCH, which configures the graph for launch
 * from the device. If this flag is passed, the executable graph handle returned can be
 * used to launch the graph from both the host and device. This flag can only be used
 * on platforms which support unified addressing. This flag cannot be used in
 * conjunction with ::CUDA_GRAPH_INSTANTIATE_FLAG_AUTO_FREE_ON_LAUNCH.
 *
 * - ::CUDA_GRAPH_INSTANTIATE_FLAG_USE_NODE_PRIORITY, which causes the graph
 * to use the priorities from the per-node attributes rather than the priority
 * of the launch stream during execution. Note that priorities are only available
 * on kernel nodes, and are copied from stream priority during stream capture.
 *
 * If \p hGraph contains any allocation or free nodes, there can be at most one
 * executable graph in existence for that graph at a time. An attempt to instantiate a
 * second executable graph before destroying the first with ::cuGraphExecDestroy will
 * result in an error.
 * The same also applies if \p hGraph contains any device-updatable kernel nodes.
 *
 * If \p hGraph contains kernels which call device-side cudaGraphLaunch() from multiple
 * contexts, this will result in an error.
 *
 * Graphs instantiated for launch on the device have additional restrictions which do not
 * apply to host graphs:
 *
 * - The graph's nodes must reside on a single context.
 * - The graph can only contain kernel nodes, memcpy nodes, memset nodes, and child graph nodes.
 * - The graph cannot be empty and must contain at least one kernel, memcpy, or memset node.
 *   Operation-specific restrictions are outlined below.
 * - Kernel nodes:
 *   - Use of CUDA Dynamic Parallelism is not permitted.
 *   - Cooperative launches are permitted as long as MPS is not in use.
 * - Memcpy nodes:
 *   - Only copies involving device memory and/or pinned device-mapped host memory are permitted.
 *   - Copies involving CUDA arrays are not permitted.
 *   - Both operands must be accessible from the current context, and the current context must
 *     match the context of other nodes in the graph.
 *
 * In the event of an error, the \p result_out and \p hErrNode_out fields will contain more
 * information about the nature of the error. Possible error reporting includes:
 *
 * - ::CUDA_GRAPH_INSTANTIATE_ERROR, if passed an invalid value or if an unexpected error occurred
 *   which is described by the return value of the function. \p hErrNode_out will be set to NULL.
 * - ::CUDA_GRAPH_INSTANTIATE_INVALID_STRUCTURE, if the graph structure is invalid. \p hErrNode_out
 *   will be set to one of the offending nodes.
 * - ::CUDA_GRAPH_INSTANTIATE_NODE_OPERATION_NOT_SUPPORTED, if the graph is instantiated for device
 *   launch but contains a node of an unsupported node type, or a node which performs unsupported
 *   operations, such as use of CUDA dynamic parallelism within a kernel node. \p hErrNode_out will
 *   be set to this node.
 * - ::CUDA_GRAPH_INSTANTIATE_MULTIPLE_CTXS_NOT_SUPPORTED, if the graph is instantiated for device
 *   launch but a node’s context differs from that of another node. This error can also be returned
 *   if a graph is not instantiated for device launch and it contains kernels which call device-side
 *   cudaGraphLaunch() from multiple contexts. \p hErrNode_out will be set to this node.
 *
 * If instantiation is successful, \p result_out will be set to ::CUDA_GRAPH_INSTANTIATE_SUCCESS,
 * and \p hErrNode_out will be set to NULL.
 *
 * \param phGraphExec       - Returns instantiated graph
 * \param hGraph            - Graph to instantiate
 * \param instantiateParams - Instantiation parameters
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphCreate,
 * ::cuGraphInstantiate,
 * ::cuGraphExecDestroy
 */
CUresult CUDAAPI cuGraphInstantiateWithParams(CUgraphExec *phGraphExec, CUgraph hGraph, CUDA_GRAPH_INSTANTIATE_PARAMS *instantiateParams);

/**
 * \brief Query the instantiation flags of an executable graph
 *
 * Returns the flags that were passed to instantiation for the given executable graph.
 * ::CUDA_GRAPH_INSTANTIATE_FLAG_UPLOAD will not be returned by this API as it does
 * not affect the resulting executable graph.
 *
 * \param hGraphExec - The executable graph to query
 * \param flags      - Returns the instantiation flags
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphInstantiate,
 * ::cuGraphInstantiateWithParams
 */
CUresult CUDAAPI cuGraphExecGetFlags(CUgraphExec hGraphExec, cuuint64_t *flags);

/**
 * \brief Sets the parameters for a kernel node in the given graphExec
 *
 * Sets the parameters of a kernel node in an executable graph \p hGraphExec. 
 * The node is identified by the corresponding node \p hNode in the 
 * non-executable graph, from which the executable graph was instantiated. 
 *
 * \p hNode must not have been removed from the original graph. All \p nodeParams 
 * fields may change, but the following restrictions apply to \p func updates: 
 *
 *   - The owning context of the function cannot change.
 *   - A node whose function originally did not use CUDA dynamic parallelism cannot be updated
 *     to a function which uses CDP
 *   - A node whose function originally did not make device-side update calls cannot be updated
 *     to a function which makes device-side update calls.
 *   - If \p hGraphExec was not instantiated for device launch, a node whose function originally
 *     did not use device-side cudaGraphLaunch() cannot be updated to a function which uses
 *     device-side cudaGraphLaunch() unless the node resides on the same context as nodes which
 *     contained such calls at instantiate-time. If no such calls were present at instantiation,
 *     these updates cannot be performed at all.
 *
 * The modifications only affect future launches of \p hGraphExec. Already 
 * enqueued or running launches of \p hGraphExec are not affected by this call. 
 * \p hNode is also not modified by this call.
 *
 * If \p hNode is a device-updatable kernel node, the next upload/launch of \p hGraphExec
 * will overwrite any previous device-side updates. Additionally, applying host updates to a
 * device-updatable kernel node while it is being updated from the device will result in
 * undefined behavior.
 * 
 * \param hGraphExec  - The executable graph in which to set the specified node
 * \param hNode       - kernel node from the graph from which graphExec was instantiated
 * \param nodeParams  - Updated Parameters to set
 * 
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphExecNodeSetParams,
 * ::cuGraphAddKernelNode,
 * ::cuGraphKernelNodeSetParams,
 * ::cuGraphExecMemcpyNodeSetParams,
 * ::cuGraphExecMemsetNodeSetParams,
 * ::cuGraphExecHostNodeSetParams,
 * ::cuGraphExecChildGraphNodeSetParams,
 * ::cuGraphExecEventRecordNodeSetEvent,
 * ::cuGraphExecEventWaitNodeSetEvent,
 * ::cuGraphExecExternalSemaphoresSignalNodeSetParams,
 * ::cuGraphExecExternalSemaphoresWaitNodeSetParams,
 * ::cuGraphExecUpdate,
 * ::cuGraphInstantiate
 */
CUresult CUDAAPI cuGraphExecKernelNodeSetParams(CUgraphExec hGraphExec, CUgraphNode hNode, const CUDA_KERNEL_NODE_PARAMS *nodeParams);

/**
 * \brief Sets the parameters for a memcpy node in the given graphExec.
 *
 * Updates the work represented by \p hNode in \p hGraphExec as though \p hNode had 
 * contained \p copyParams at instantiation.  hNode must remain in the graph which was 
 * used to instantiate \p hGraphExec.  Changed edges to and from hNode are ignored.
 *
 * The source and destination memory in \p copyParams must be allocated from the same 
 * contexts as the original source and destination memory.  Both the instantiation-time 
 * memory operands and the memory operands in \p copyParams must be 1-dimensional.
 * Zero-length operations are not supported.
 *
 * The modifications only affect future launches of \p hGraphExec.  Already enqueued 
 * or running launches of \p hGraphExec are not affected by this call.  hNode is also 
 * not modified by this call.
 *
 * Returns CUDA_ERROR_INVALID_VALUE if the memory operands' mappings changed or
 * either the original or new memory operands are multidimensional.
 *
 * \param hGraphExec - The executable graph in which to set the specified node
 * \param hNode      - Memcpy node from the graph which was used to instantiate graphExec
 * \param copyParams - The updated parameters to set
 * \param ctx        - Context on which to run the node
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphExecNodeSetParams,
 * ::cuGraphAddMemcpyNode,
 * ::cuGraphMemcpyNodeSetParams,
 * ::cuGraphExecKernelNodeSetParams,
 * ::cuGraphExecMemsetNodeSetParams,
 * ::cuGraphExecHostNodeSetParams,
 * ::cuGraphExecChildGraphNodeSetParams,
 * ::cuGraphExecEventRecordNodeSetEvent,
 * ::cuGraphExecEventWaitNodeSetEvent,
 * ::cuGraphExecExternalSemaphoresSignalNodeSetParams,
 * ::cuGraphExecExternalSemaphoresWaitNodeSetParams,
 * ::cuGraphExecUpdate,
 * ::cuGraphInstantiate
 */
CUresult CUDAAPI cuGraphExecMemcpyNodeSetParams(CUgraphExec hGraphExec, CUgraphNode hNode, const CUDA_MEMCPY3D *copyParams, CUcontext ctx);

/**
 * \brief Sets the parameters for a memset node in the given graphExec.
 *
 * Updates the work represented by \p hNode in \p hGraphExec as though \p hNode had 
 * contained \p memsetParams at instantiation.  hNode must remain in the graph which was 
 * used to instantiate \p hGraphExec.  Changed edges to and from hNode are ignored.
 *
 * Zero sized operations are not supported.
 *
 * The new destination pointer in memsetParams must be to the same kind of allocation
 * as the original destination pointer and have the same context association and device mapping
 * as the original destination pointer.
 *
 * Both the value and pointer address may be updated.  
 * Changing other aspects of the memset (width, height, element size or pitch) may cause the update to be rejected.
 * Specifically, for 2d memsets, all dimension changes are rejected.
 * For 1d memsets, changes in height are explicitly rejected and other changes are oportunistically allowed
 * if the resulting work maps onto the work resources already allocated for the node.
 *
 * The modifications only affect future launches of \p hGraphExec.  Already enqueued 
 * or running launches of \p hGraphExec are not affected by this call.  hNode is also 
 * not modified by this call.
 *
 * \param hGraphExec   - The executable graph in which to set the specified node
 * \param hNode        - Memset node from the graph which was used to instantiate graphExec
 * \param memsetParams - The updated parameters to set
 * \param ctx          - Context on which to run the node
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphExecNodeSetParams,
 * ::cuGraphAddMemsetNode,
 * ::cuGraphMemsetNodeSetParams,
 * ::cuGraphExecKernelNodeSetParams,
 * ::cuGraphExecMemcpyNodeSetParams,
 * ::cuGraphExecHostNodeSetParams,
 * ::cuGraphExecChildGraphNodeSetParams,
 * ::cuGraphExecEventRecordNodeSetEvent,
 * ::cuGraphExecEventWaitNodeSetEvent,
 * ::cuGraphExecExternalSemaphoresSignalNodeSetParams,
 * ::cuGraphExecExternalSemaphoresWaitNodeSetParams,
 * ::cuGraphExecUpdate,
 * ::cuGraphInstantiate
 */
CUresult CUDAAPI cuGraphExecMemsetNodeSetParams(CUgraphExec hGraphExec, CUgraphNode hNode, const CUDA_MEMSET_NODE_PARAMS *memsetParams, CUcontext ctx);

/**
 * \brief Sets the parameters for a host node in the given graphExec.
 *
 * Updates the work represented by \p hNode in \p hGraphExec as though \p hNode had 
 * contained \p nodeParams at instantiation.  hNode must remain in the graph which was 
 * used to instantiate \p hGraphExec.  Changed edges to and from hNode are ignored.
 *
 * The modifications only affect future launches of \p hGraphExec.  Already enqueued 
 * or running launches of \p hGraphExec are not affected by this call.  hNode is also 
 * not modified by this call.
 *
 * \param hGraphExec - The executable graph in which to set the specified node
 * \param hNode      - Host node from the graph which was used to instantiate graphExec
 * \param nodeParams - The updated parameters to set
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphExecNodeSetParams,
 * ::cuGraphAddHostNode,
 * ::cuGraphHostNodeSetParams,
 * ::cuGraphExecKernelNodeSetParams,
 * ::cuGraphExecMemcpyNodeSetParams,
 * ::cuGraphExecMemsetNodeSetParams,
 * ::cuGraphExecChildGraphNodeSetParams,
 * ::cuGraphExecEventRecordNodeSetEvent,
 * ::cuGraphExecEventWaitNodeSetEvent,
 * ::cuGraphExecExternalSemaphoresSignalNodeSetParams,
 * ::cuGraphExecExternalSemaphoresWaitNodeSetParams,
 * ::cuGraphExecUpdate,
 * ::cuGraphInstantiate
 */
CUresult CUDAAPI cuGraphExecHostNodeSetParams(CUgraphExec hGraphExec, CUgraphNode hNode, const CUDA_HOST_NODE_PARAMS *nodeParams);

/**
 * \brief Updates node parameters in the child graph node in the given graphExec.
 *
 * Updates the work represented by \p hNode in \p hGraphExec as though the nodes contained
 * in \p hNode's graph had the parameters contained in \p childGraph's nodes at instantiation.
 * \p hNode must remain in the graph which was used to instantiate \p hGraphExec.
 * Changed edges to and from \p hNode are ignored.
 *
 * The modifications only affect future launches of \p hGraphExec.  Already enqueued 
 * or running launches of \p hGraphExec are not affected by this call.  \p hNode is also 
 * not modified by this call.
 *
 * The topology of \p childGraph, as well as the node insertion order,  must match that
 * of the graph contained in \p hNode.  See ::cuGraphExecUpdate() for a list of restrictions
 * on what can be updated in an instantiated graph.  The update is recursive, so child graph
 * nodes contained within the top level child graph will also be updated.
 *
 * \param hGraphExec - The executable graph in which to set the specified node
 * \param hNode      - Host node from the graph which was used to instantiate graphExec
 * \param childGraph - The graph supplying the updated parameters
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphExecNodeSetParams,
 * ::cuGraphAddChildGraphNode,
 * ::cuGraphChildGraphNodeGetGraph,
 * ::cuGraphExecKernelNodeSetParams,
 * ::cuGraphExecMemcpyNodeSetParams,
 * ::cuGraphExecMemsetNodeSetParams,
 * ::cuGraphExecHostNodeSetParams,
 * ::cuGraphExecEventRecordNodeSetEvent,
 * ::cuGraphExecEventWaitNodeSetEvent,
 * ::cuGraphExecExternalSemaphoresSignalNodeSetParams,
 * ::cuGraphExecExternalSemaphoresWaitNodeSetParams,
 * ::cuGraphExecUpdate,
 * ::cuGraphInstantiate
 */
CUresult CUDAAPI cuGraphExecChildGraphNodeSetParams(CUgraphExec hGraphExec, CUgraphNode hNode, CUgraph childGraph);

/**
 * \brief Sets the event for an event record node in the given graphExec
 *
 * Sets the event of an event record node in an executable graph \p hGraphExec.
 * The node is identified by the corresponding node \p hNode in the
 * non-executable graph, from which the executable graph was instantiated.
 *
 * The modifications only affect future launches of \p hGraphExec. Already
 * enqueued or running launches of \p hGraphExec are not affected by this call.
 * \p hNode is also not modified by this call.
 *
 * \param hGraphExec - The executable graph in which to set the specified node
 * \param hNode      - event record node from the graph from which graphExec was instantiated
 * \param event      - Updated event to use
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphExecNodeSetParams,
 * ::cuGraphAddEventRecordNode,
 * ::cuGraphEventRecordNodeGetEvent,
 * ::cuGraphEventWaitNodeSetEvent,
 * ::cuEventRecordWithFlags,
 * ::cuStreamWaitEvent,
 * ::cuGraphExecKernelNodeSetParams,
 * ::cuGraphExecMemcpyNodeSetParams,
 * ::cuGraphExecMemsetNodeSetParams,
 * ::cuGraphExecHostNodeSetParams,
 * ::cuGraphExecChildGraphNodeSetParams,
 * ::cuGraphExecEventWaitNodeSetEvent,
 * ::cuGraphExecExternalSemaphoresSignalNodeSetParams,
 * ::cuGraphExecExternalSemaphoresWaitNodeSetParams,
 * ::cuGraphExecUpdate,
 * ::cuGraphInstantiate
 */
CUresult CUDAAPI cuGraphExecEventRecordNodeSetEvent(CUgraphExec hGraphExec, CUgraphNode hNode, CUevent event);

/**
 * \brief Sets the event for an event wait node in the given graphExec
 *
 * Sets the event of an event wait node in an executable graph \p hGraphExec.
 * The node is identified by the corresponding node \p hNode in the
 * non-executable graph, from which the executable graph was instantiated.
 *
 * The modifications only affect future launches of \p hGraphExec. Already
 * enqueued or running launches of \p hGraphExec are not affected by this call.
 * \p hNode is also not modified by this call.
 *
 * \param hGraphExec - The executable graph in which to set the specified node
 * \param hNode      - event wait node from the graph from which graphExec was instantiated
 * \param event      - Updated event to use
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphExecNodeSetParams,
 * ::cuGraphAddEventWaitNode,
 * ::cuGraphEventWaitNodeGetEvent,
 * ::cuGraphEventRecordNodeSetEvent,
 * ::cuEventRecordWithFlags,
 * ::cuStreamWaitEvent,
 * ::cuGraphExecKernelNodeSetParams,
 * ::cuGraphExecMemcpyNodeSetParams,
 * ::cuGraphExecMemsetNodeSetParams,
 * ::cuGraphExecHostNodeSetParams,
 * ::cuGraphExecChildGraphNodeSetParams,
 * ::cuGraphExecEventRecordNodeSetEvent,
 * ::cuGraphExecExternalSemaphoresSignalNodeSetParams,
 * ::cuGraphExecExternalSemaphoresWaitNodeSetParams,
 * ::cuGraphExecUpdate,
 * ::cuGraphInstantiate
 */
CUresult CUDAAPI cuGraphExecEventWaitNodeSetEvent(CUgraphExec hGraphExec, CUgraphNode hNode, CUevent event);

/**
 * \brief Sets the parameters for an external semaphore signal node in the given graphExec
 *
 * Sets the parameters of an external semaphore signal node in an executable graph \p hGraphExec.
 * The node is identified by the corresponding node \p hNode in the
 * non-executable graph, from which the executable graph was instantiated.
 *
 * \p hNode must not have been removed from the original graph.
 *
 * The modifications only affect future launches of \p hGraphExec. Already
 * enqueued or running launches of \p hGraphExec are not affected by this call.
 * \p hNode is also not modified by this call.
 *
 * Changing \p nodeParams->numExtSems is not supported.
 *
 * \param hGraphExec - The executable graph in which to set the specified node
 * \param hNode      - semaphore signal node from the graph from which graphExec was instantiated
 * \param nodeParams - Updated Parameters to set
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphExecNodeSetParams,
 * ::cuGraphAddExternalSemaphoresSignalNode,
 * ::cuImportExternalSemaphore,
 * ::cuSignalExternalSemaphoresAsync,
 * ::cuWaitExternalSemaphoresAsync,
 * ::cuGraphExecKernelNodeSetParams,
 * ::cuGraphExecMemcpyNodeSetParams,
 * ::cuGraphExecMemsetNodeSetParams,
 * ::cuGraphExecHostNodeSetParams,
 * ::cuGraphExecChildGraphNodeSetParams,
 * ::cuGraphExecEventRecordNodeSetEvent,
 * ::cuGraphExecEventWaitNodeSetEvent,
 * ::cuGraphExecExternalSemaphoresWaitNodeSetParams,
 * ::cuGraphExecUpdate,
 * ::cuGraphInstantiate
 */
CUresult CUDAAPI cuGraphExecExternalSemaphoresSignalNodeSetParams(CUgraphExec hGraphExec, CUgraphNode hNode, const CUDA_EXT_SEM_SIGNAL_NODE_PARAMS *nodeParams);

/**
 * \brief Sets the parameters for an external semaphore wait node in the given graphExec
 *
 * Sets the parameters of an external semaphore wait node in an executable graph \p hGraphExec.
 * The node is identified by the corresponding node \p hNode in the
 * non-executable graph, from which the executable graph was instantiated.
 *
 * \p hNode must not have been removed from the original graph.
 *
 * The modifications only affect future launches of \p hGraphExec. Already
 * enqueued or running launches of \p hGraphExec are not affected by this call.
 * \p hNode is also not modified by this call.
 *
 * Changing \p nodeParams->numExtSems is not supported.
 *
 * \param hGraphExec - The executable graph in which to set the specified node
 * \param hNode      - semaphore wait node from the graph from which graphExec was instantiated
 * \param nodeParams - Updated Parameters to set
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphExecNodeSetParams,
 * ::cuGraphAddExternalSemaphoresWaitNode,
 * ::cuImportExternalSemaphore,
 * ::cuSignalExternalSemaphoresAsync,
 * ::cuWaitExternalSemaphoresAsync,
 * ::cuGraphExecKernelNodeSetParams,
 * ::cuGraphExecMemcpyNodeSetParams,
 * ::cuGraphExecMemsetNodeSetParams,
 * ::cuGraphExecHostNodeSetParams,
 * ::cuGraphExecChildGraphNodeSetParams,
 * ::cuGraphExecEventRecordNodeSetEvent,
 * ::cuGraphExecEventWaitNodeSetEvent,
 * ::cuGraphExecExternalSemaphoresSignalNodeSetParams,
 * ::cuGraphExecUpdate,
 * ::cuGraphInstantiate
 */
CUresult CUDAAPI cuGraphExecExternalSemaphoresWaitNodeSetParams(CUgraphExec hGraphExec, CUgraphNode hNode, const CUDA_EXT_SEM_WAIT_NODE_PARAMS *nodeParams);

/**
 * \brief Enables or disables the specified node in the given graphExec
 *
 * Sets \p hNode to be either enabled or disabled. Disabled nodes are functionally equivalent 
 * to empty nodes until they are reenabled. Existing node parameters are not affected by 
 * disabling/enabling the node.
 *  
 * The node is identified by the corresponding node \p hNode in the non-executable 
 * graph, from which the executable graph was instantiated.   
 *
 * \p hNode must not have been removed from the original graph.
 *
 * The modifications only affect future launches of \p hGraphExec. Already
 * enqueued or running launches of \p hGraphExec are not affected by this call.
 * \p hNode is also not modified by this call.
 *
 * If \p hNode is a device-updatable kernel node, the next upload/launch of \p hGraphExec
 * will overwrite any previous device-side updates. Additionally, applying host updates to a
 * device-updatable kernel node while it is being updated from the device will result in
 * undefined behavior.
 *
 * \note Currently only kernel, memset and memcpy nodes are supported. 
 *
 * \param hGraphExec - The executable graph in which to set the specified node
 * \param hNode      - Node from the graph from which graphExec was instantiated
 * \param isEnabled  - Node is enabled if != 0, otherwise the node is disabled
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphNodeGetEnabled,
 * ::cuGraphExecUpdate,
 * ::cuGraphInstantiate
 * ::cuGraphLaunch
 */
CUresult CUDAAPI cuGraphNodeSetEnabled(CUgraphExec hGraphExec, CUgraphNode hNode, unsigned int isEnabled);

/**
 * \brief Query whether a node in the given graphExec is enabled
 *
 * Sets isEnabled to 1 if \p hNode is enabled, or 0 if \p hNode is disabled.
 *
 * The node is identified by the corresponding node \p hNode in the non-executable 
 * graph, from which the executable graph was instantiated.   
 *
 * \p hNode must not have been removed from the original graph.
 *
 * \note Currently only kernel, memset and memcpy nodes are supported. 
 * \note This function will not reflect device-side updates for device-updatable kernel nodes.
 *
 * \param hGraphExec - The executable graph in which to set the specified node
 * \param hNode      - Node from the graph from which graphExec was instantiated
 * \param isEnabled  - Location to return the enabled status of the node
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphNodeSetEnabled,
 * ::cuGraphExecUpdate,
 * ::cuGraphInstantiate
 * ::cuGraphLaunch
 */
CUresult CUDAAPI cuGraphNodeGetEnabled(CUgraphExec hGraphExec, CUgraphNode hNode, unsigned int *isEnabled);

/**
 * \brief Uploads an executable graph in a stream
 *
 * Uploads \p hGraphExec to the device in \p hStream without executing it. Uploads of
 * the same \p hGraphExec will be serialized. Each upload is ordered behind both any
 * previous work in \p hStream and any previous launches of \p hGraphExec.
 * Uses memory cached by \p stream to back the allocations owned by \p hGraphExec.
 *
 * \param hGraphExec - Executable graph to upload
 * \param hStream    - Stream in which to upload the graph
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphInstantiate,
 * ::cuGraphLaunch,
 * ::cuGraphExecDestroy
 */
CUresult CUDAAPI cuGraphUpload(CUgraphExec hGraphExec, CUstream hStream);

/**
 * \brief Launches an executable graph in a stream
 *
 * Executes \p hGraphExec in \p hStream. Only one instance of \p hGraphExec may be executing
 * at a time. Each launch is ordered behind both any previous work in \p hStream
 * and any previous launches of \p hGraphExec. To execute a graph concurrently, it must be
 * instantiated multiple times into multiple executable graphs.
 *
 * If any allocations created by \p hGraphExec remain unfreed (from a previous launch) and
 * \p hGraphExec was not instantiated with ::CUDA_GRAPH_INSTANTIATE_FLAG_AUTO_FREE_ON_LAUNCH,
 * the launch will fail with ::CUDA_ERROR_INVALID_VALUE.
 *
 * \param hGraphExec - Executable graph to launch
 * \param hStream    - Stream in which to launch the graph
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphInstantiate,
 * ::cuGraphUpload,
 * ::cuGraphExecDestroy
 */
CUresult CUDAAPI cuGraphLaunch(CUgraphExec hGraphExec, CUstream hStream);

/**
 * \brief Destroys an executable graph
 *
 * Destroys the executable graph specified by \p hGraphExec, as well
 * as all of its executable nodes. If the executable graph is
 * in-flight, it will not be terminated, but rather freed
 * asynchronously on completion.
 *
 * \param hGraphExec - Executable graph to destroy
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphInstantiate,
 * ::cuGraphUpload,
 * ::cuGraphLaunch
 */
CUresult CUDAAPI cuGraphExecDestroy(CUgraphExec hGraphExec);

/**
 * \brief Destroys a graph
 *
 * Destroys the graph specified by \p hGraph, as well as all of its nodes.
 *
 * \param hGraph - Graph to destroy
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphCreate
 */
CUresult CUDAAPI cuGraphDestroy(CUgraph hGraph);

/**
 * \brief Check whether an executable graph can be updated with a graph and perform the update if possible
 *
 * Updates the node parameters in the instantiated graph specified by \p hGraphExec with the
 * node parameters in a topologically identical graph specified by \p hGraph.
 *
 * Limitations:
 *
 * - Kernel nodes:
 *   - The owning context of the function cannot change.
 *   - A node whose function originally did not use CUDA dynamic parallelism cannot be updated
 *     to a function which uses CDP.
 *   - A node whose function originally did not make device-side update calls cannot be updated
 *     to a function which makes device-side update calls.
 *   - A cooperative node cannot be updated to a non-cooperative node, and vice-versa.
 *   - If the graph was instantiated with CUDA_GRAPH_INSTANTIATE_FLAG_USE_NODE_PRIORITY, the
 *     priority attribute cannot change. Equality is checked on the originally requested
 *     priority values, before they are clamped to the device's supported range.
 *   - If \p hGraphExec was not instantiated for device launch, a node whose function originally
 *     did not use device-side cudaGraphLaunch() cannot be updated to a function which uses
 *     device-side cudaGraphLaunch() unless the node resides on the same context as nodes which
 *     contained such calls at instantiate-time. If no such calls were present at instantiation,
 *     these updates cannot be performed at all.
 *   - Neither \p hGraph nor \p hGraphExec may contain device-updatable kernel nodes.
 * - Memset and memcpy nodes:
 *   - The CUDA device(s) to which the operand(s) was allocated/mapped cannot change.
 *   - The source/destination memory must be allocated from the same contexts as the original
 *     source/destination memory.
 *   - For 2d memsets, only address and assinged value may be updated.
 *   - For 1d memsets, updating dimensions is also allowed, but may fail if the resulting operation doesn't
 *     map onto the work resources already allocated for the node. 
 * - Additional memcpy node restrictions:
 *   - Changing either the source or destination memory type(i.e. CU_MEMORYTYPE_DEVICE,
 *     CU_MEMORYTYPE_ARRAY, etc.) is not supported.
 * - External semaphore wait nodes and record nodes:
 *   - Changing the number of semaphores is not supported.
 * - Conditional nodes:
 *   - Changing node parameters is not supported.
 *   - Changeing parameters of nodes within the conditional body graph is subject to the rules above.
 *   - Conditional handle flags and default values are updated as part of the graph update.
 *
 * Note:  The API may add further restrictions in future releases.  The return code should always be checked.
 *
 * cuGraphExecUpdate sets the result member of \p resultInfo to CU_GRAPH_EXEC_UPDATE_ERROR_TOPOLOGY_CHANGED
 * under the following conditions:
 * - The count of nodes directly in \p hGraphExec and \p hGraph differ, in which case resultInfo->errorNode
 *   is set to NULL.
 * - \p hGraph has more exit nodes than \p hGraph, in which case resultInfo->errorNode is set to one of
 *   the exit nodes in hGraph. 
 * - A node in \p hGraph has a different number of dependencies than the node from \p hGraphExec it is paired with,
 *   in which case resultInfo->errorNode is set to the node from \p hGraph.
 * - A node in \p hGraph has a dependency that does not match with the corresponding dependency of the paired node
 *   from \p hGraphExec. resultInfo->errorNode will be set to the node from \p hGraph. resultInfo->errorFromNode
 *   will be set to the mismatched dependency. The dependencies are paired based on edge order and a dependency
 *   does not match when the nodes are already paired based on other edges examined in the graph.
 *
 * cuGraphExecUpdate sets the result member of \p resultInfo to: 
 * - CU_GRAPH_EXEC_UPDATE_ERROR if passed an invalid value.
 * - CU_GRAPH_EXEC_UPDATE_ERROR_TOPOLOGY_CHANGED if the graph topology changed
 * - CU_GRAPH_EXEC_UPDATE_ERROR_NODE_TYPE_CHANGED if the type of a node changed, in which case
 *   \p hErrorNode_out is set to the node from \p hGraph.
 * - CU_GRAPH_EXEC_UPDATE_ERROR_UNSUPPORTED_FUNCTION_CHANGE if the function changed in an unsupported
 *   way(see note above), in which case \p hErrorNode_out is set to the node from \p hGraph
 * - CU_GRAPH_EXEC_UPDATE_ERROR_PARAMETERS_CHANGED if any parameters to a node changed in a way 
 *   that is not supported, in which case \p hErrorNode_out is set to the node from \p hGraph.
 * - CU_GRAPH_EXEC_UPDATE_ERROR_ATTRIBUTES_CHANGED if any attributes of a node changed in a way
 *   that is not supported, in which case \p hErrorNode_out is set to the node from \p hGraph.
 * - CU_GRAPH_EXEC_UPDATE_ERROR_NOT_SUPPORTED if something about a node is unsupported, like 
 *   the node's type or configuration, in which case \p hErrorNode_out is set to the node from \p hGraph
 *
 * If the update fails for a reason not listed above, the result member of \p resultInfo will be set
 * to CU_GRAPH_EXEC_UPDATE_ERROR. If the update succeeds, the result member will be set to CU_GRAPH_EXEC_UPDATE_SUCCESS.
 *
 * cuGraphExecUpdate returns CUDA_SUCCESS when the updated was performed successfully.  It returns
 * CUDA_ERROR_GRAPH_EXEC_UPDATE_FAILURE if the graph update was not performed because it included 
 * changes which violated constraints specific to instantiated graph update.
 *
 * \param hGraphExec The instantiated graph to be updated
 * \param hGraph The graph containing the updated parameters
 * \param resultInfo the error info structure 
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_GRAPH_EXEC_UPDATE_FAILURE,
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphInstantiate
 */
CUresult CUDAAPI cuGraphExecUpdate(CUgraphExec hGraphExec, CUgraph hGraph, CUgraphExecUpdateResultInfo *resultInfo);

/**
 * \brief Copies attributes from source node to destination node.
 *
 * Copies attributes from source node \p src to destination node \p dst.
 * Both node must have the same context.
 *
 * \param[out] dst Destination node
 * \param[in] src Source node
 * For list of attributes see ::CUkernelNodeAttrID
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 *
 * \sa
 * ::CUaccessPolicyWindow
 */
CUresult CUDAAPI cuGraphKernelNodeCopyAttributes(CUgraphNode dst, CUgraphNode src);

/**
 * \brief Queries node attribute.
 * 
 * Queries attribute \p attr from node \p hNode and stores it in corresponding
 * member of \p value_out.
 *
 * \param[in] hNode
 * \param[in] attr
 * \param[out] value_out 
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_HANDLE
 * \notefnerr
 *  
 * \sa
 * ::CUaccessPolicyWindow
 */
CUresult CUDAAPI cuGraphKernelNodeGetAttribute(CUgraphNode hNode, CUkernelNodeAttrID attr,
                                      CUkernelNodeAttrValue *value_out);
 
/**
 * \brief Sets node attribute.
 * 
 * Sets attribute \p attr on node \p hNode from corresponding attribute of
 * \p value.
 *
 * \param[out] hNode
 * \param[in] attr
 * \param[out] value
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_HANDLE
 * \notefnerr
 *
 * \sa
 * ::CUaccessPolicyWindow
 */
CUresult CUDAAPI cuGraphKernelNodeSetAttribute(CUgraphNode hNode, CUkernelNodeAttrID attr,
                                      const CUkernelNodeAttrValue *value);

/**
 * \brief Write a DOT file describing graph structure
 *
 * Using the provided \p hGraph, write to \p path a DOT formatted description of the graph.
 * By default this includes the graph topology, node types, node id, kernel names and memcpy direction.
 * \p flags can be specified to write more detailed information about each node type such as
 * parameter values, kernel attributes, node and function handles.
 *
 * \param hGraph - The graph to create a DOT file from
 * \param path   - The path to write the DOT file to
 * \param flags  - Flags from CUgraphDebugDot_flags for specifying which additional node information to write
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_OPERATING_SYSTEM
 */
CUresult CUDAAPI cuGraphDebugDotPrint(CUgraph hGraph, const char *path, unsigned int flags);

/**
 * \brief Create a user object
 *
 * Create a user object with the specified destructor callback and initial reference count. The
 * initial references are owned by the caller.
 *
 * Destructor callbacks cannot make CUDA API calls and should avoid blocking behavior, as they
 * are executed by a shared internal thread. Another thread may be signaled to perform such
 * actions, if it does not block forward progress of tasks scheduled through CUDA.
 *
 * See CUDA User Objects in the CUDA C++ Programming Guide for more information on user objects.
 *
 * \param object_out      - Location to return the user object handle
 * \param ptr             - The pointer to pass to the destroy function
 * \param destroy         - Callback to free the user object when it is no longer in use
 * \param initialRefcount - The initial refcount to create the object with, typically 1. The
 *                          initial references are owned by the calling thread.
 * \param flags           - Currently it is required to pass ::CU_USER_OBJECT_NO_DESTRUCTOR_SYNC,
 *                          which is the only defined flag. This indicates that the destroy
 *                          callback cannot be waited on by any CUDA API. Users requiring
 *                          synchronization of the callback should signal its completion
 *                          manually.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa
 * ::cuUserObjectRetain,
 * ::cuUserObjectRelease,
 * ::cuGraphRetainUserObject,
 * ::cuGraphReleaseUserObject,
 * ::cuGraphCreate
 */
CUresult CUDAAPI cuUserObjectCreate(CUuserObject *object_out, void *ptr, CUhostFn destroy,
                                    unsigned int initialRefcount, unsigned int flags);

/**
 * \brief Retain a reference to a user object
 *
 * Retains new references to a user object. The new references are owned by the caller.
 *
 * See CUDA User Objects in the CUDA C++ Programming Guide for more information on user objects.
 *
 * \param object - The object to retain
 * \param count  - The number of references to retain, typically 1. Must be nonzero
 *                 and not larger than INT_MAX.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa
 * ::cuUserObjectCreate,
 * ::cuUserObjectRelease,
 * ::cuGraphRetainUserObject,
 * ::cuGraphReleaseUserObject,
 * ::cuGraphCreate
 */
CUresult CUDAAPI cuUserObjectRetain(CUuserObject object, unsigned int count);

/**
 * \brief Release a reference to a user object
 *
 * Releases user object references owned by the caller. The object's destructor is invoked if
 * the reference count reaches zero.
 *
 * It is undefined behavior to release references not owned by the caller, or to use a user
 * object handle after all references are released.
 *
 * See CUDA User Objects in the CUDA C++ Programming Guide for more information on user objects.
 *
 * \param object - The object to release
 * \param count  - The number of references to release, typically 1. Must be nonzero
 *                 and not larger than INT_MAX.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa
 * ::cuUserObjectCreate,
 * ::cuUserObjectRetain,
 * ::cuGraphRetainUserObject,
 * ::cuGraphReleaseUserObject,
 * ::cuGraphCreate
 */
CUresult CUDAAPI cuUserObjectRelease(CUuserObject object, unsigned int count);

/**
 * \brief Retain a reference to a user object from a graph
 *
 * Creates or moves user object references that will be owned by a CUDA graph.
 *
 * See CUDA User Objects in the CUDA C++ Programming Guide for more information on user objects.
 *
 * \param graph  - The graph to associate the reference with
 * \param object - The user object to retain a reference for
 * \param count  - The number of references to add to the graph, typically 1. Must be
 *                 nonzero and not larger than INT_MAX.
 * \param flags  - The optional flag ::CU_GRAPH_USER_OBJECT_MOVE transfers references
 *                 from the calling thread, rather than create new references. Pass 0
 *                 to create new references.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa
 * ::cuUserObjectCreate,
 * ::cuUserObjectRetain,
 * ::cuUserObjectRelease,
 * ::cuGraphReleaseUserObject,
 * ::cuGraphCreate
 */
CUresult CUDAAPI cuGraphRetainUserObject(CUgraph graph, CUuserObject object, unsigned int count, unsigned int flags);

/**
 * \brief Release a user object reference from a graph
 *
 * Releases user object references owned by a graph.
 *
 * See CUDA User Objects in the CUDA C++ Programming Guide for more information on user objects.
 *
 * \param graph  - The graph that will release the reference
 * \param object - The user object to release a reference for
 * \param count  - The number of references to release, typically 1. Must be nonzero
 *                 and not larger than INT_MAX.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa
 * ::cuUserObjectCreate,
 * ::cuUserObjectRetain,
 * ::cuUserObjectRelease,
 * ::cuGraphRetainUserObject,
 * ::cuGraphCreate
 */
CUresult CUDAAPI cuGraphReleaseUserObject(CUgraph graph, CUuserObject object, unsigned int count);

/**
 * \brief Adds a node of arbitrary type to a graph
 *
 * Creates a new node in \p hGraph described by \p nodeParams with \p numDependencies
 * dependencies specified via \p dependencies. \p numDependencies may be 0.
 * \p dependencies may be null if \p numDependencies is 0. \p dependencies may not have
 * any duplicate entries.
 *
 * \p nodeParams is a tagged union. The node type should be specified in the \p type field,
 * and type-specific parameters in the corresponding union member. All unused bytes - that
 * is, \p reserved0 and all bytes past the utilized union member - must be set to zero.
 * It is recommended to use brace initialization or memset to ensure all bytes are
 * initialized.
 *
 * Note that for some node types, \p nodeParams may contain "out parameters" which are
 * modified during the call, such as \p nodeParams->alloc.dptr.
 *
 * A handle to the new node will be returned in \p phGraphNode.
 *
 * \param phGraphNode     - Returns newly created node
 * \param hGraph          - Graph to which to add the node
 * \param dependencies    - Dependencies of the node
 * \param numDependencies - Number of dependencies
 * \param nodeParams      - Specification of the node
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_NOT_SUPPORTED
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphCreate,
 * ::cuGraphNodeSetParams,
 * ::cuGraphExecNodeSetParams
 */
CUresult CUDAAPI cuGraphAddNode(CUgraphNode *phGraphNode, CUgraph hGraph, const CUgraphNode *dependencies, size_t numDependencies, CUgraphNodeParams *nodeParams);

/**
 * \brief Adds a node of arbitrary type to a graph (12.3+)
 *
 * Creates a new node in \p hGraph described by \p nodeParams with \p numDependencies
 * dependencies specified via \p dependencies. \p numDependencies may be 0.
 * \p dependencies may be null if \p numDependencies is 0. \p dependencies may not have
 * any duplicate entries.
 *
 * \p nodeParams is a tagged union. The node type should be specified in the \p type field,
 * and type-specific parameters in the corresponding union member. All unused bytes - that
 * is, \p reserved0 and all bytes past the utilized union member - must be set to zero.
 * It is recommended to use brace initialization or memset to ensure all bytes are
 * initialized.
 *
 * Note that for some node types, \p nodeParams may contain "out parameters" which are
 * modified during the call, such as \p nodeParams->alloc.dptr.
 *
 * A handle to the new node will be returned in \p phGraphNode.
 *
 * \param phGraphNode     - Returns newly created node
 * \param hGraph          - Graph to which to add the node
 * \param dependencies    - Dependencies of the node
 * \param dependencyData  - Optional edge data for the dependencies. If NULL, the data is
 *                          assumed to be default (zeroed) for all dependencies.
 * \param numDependencies - Number of dependencies
 * \param nodeParams      - Specification of the node
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_NOT_SUPPORTED
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphCreate,
 * ::cuGraphNodeSetParams,
 * ::cuGraphExecNodeSetParams
 */
CUresult CUDAAPI cuGraphAddNode_v2(CUgraphNode *phGraphNode, CUgraph hGraph, const CUgraphNode *dependencies, const CUgraphEdgeData *dependencyData, size_t numDependencies, CUgraphNodeParams *nodeParams);

/**
 * \brief Update's a graph node's parameters
 *
 * Sets the parameters of graph node \p hNode to \p nodeParams. The node type specified by
 * \p nodeParams->type must match the type of \p hNode. \p nodeParams must be fully
 * initialized and all unused bytes (reserved, padding) zeroed.
 *
 * Modifying parameters is not supported for node types CU_GRAPH_NODE_TYPE_MEM_ALLOC and
 * CU_GRAPH_NODE_TYPE_MEM_FREE.
 *
 * \param hNode      - Node to set the parameters for
 * \param nodeParams - Parameters to copy
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_NOT_SUPPORTED
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphAddNode,
 * ::cuGraphExecNodeSetParams
 */
CUresult CUDAAPI cuGraphNodeSetParams(CUgraphNode hNode, CUgraphNodeParams *nodeParams);

/**
 * \brief Update's a graph node's parameters in an instantiated graph
 *
 * Sets the parameters of a node in an executable graph \p hGraphExec. The node is identified
 * by the corresponding node \p hNode in the non-executable graph from which the executable
 * graph was instantiated. \p hNode must not have been removed from the original graph.
 *
 * The modifications only affect future launches of \p hGraphExec. Already
 * enqueued or running launches of \p hGraphExec are not affected by this call.
 * \p hNode is also not modified by this call.
 *
 * Allowed changes to parameters on executable graphs are as follows:
 * <table>
 *   <tr><th>Node type<th>Allowed changes
 *   <tr><td>kernel<td>See ::cuGraphExecKernelNodeSetParams
 *   <tr><td>memcpy<td>Addresses for 1-dimensional copies if allocated in same context; see ::cuGraphExecMemcpyNodeSetParams
 *   <tr><td>memset<td>Addresses for 1-dimensional memsets if allocated in same context; see ::cuGraphExecMemsetNodeSetParams
 *   <tr><td>host<td>Unrestricted
 *   <tr><td>child graph<td>Topology must match and restrictions apply recursively; see ::cuGraphExecUpdate
 *   <tr><td>event wait<td>Unrestricted
 *   <tr><td>event record<td>Unrestricted
 *   <tr><td>external semaphore signal<td>Number of semaphore operations cannot change
 *   <tr><td>external semaphore wait<td>Number of semaphore operations cannot change
 *   <tr><td>memory allocation<td>API unsupported
 *   <tr><td>memory free<td>API unsupported
 *   <tr><td>batch memops<td>Addresses, values, and operation type for wait operations; see ::cuGraphExecBatchMemOpNodeSetParams
 * </table>
 *
 * \param hGraphExec  - The executable graph in which to update the specified node
 * \param hNode       - Corresponding node from the graph from which graphExec was instantiated
 * \param nodeParams  - Updated Parameters to set
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_NOT_SUPPORTED
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphAddNode,
 * ::cuGraphNodeSetParams
 * ::cuGraphExecUpdate,
 * ::cuGraphInstantiate
 */
CUresult CUDAAPI cuGraphExecNodeSetParams(CUgraphExec hGraphExec, CUgraphNode hNode, CUgraphNodeParams *nodeParams);

/**
 * \brief Create a conditional handle
 *
 * Creates a conditional handle associated with \p hGraph. 
 *  
 * The conditional handle must be associated with a conditional node in this graph or one of its children.
 *  
 * Handles not associated with a conditional node may cause graph instantiation to fail. 
 *  
 * Handles can only be set from the context with which they are associated. 
 *
 * \param pHandle_out        - Pointer used to return the handle to the caller.
 * \param hGraph             - Graph which will contain the conditional node using this handle.
 * \param ctx                - Context for the handle and associated conditional node.
 * \param defaultLaunchValue - Optional initial value for the conditional variable.
 *                             Applied at the beginning of each graph execution if CU_GRAPH_COND_ASSIGN_DEFAULT is set in \p flags.
 * \param flags              - Currently must be CU_GRAPH_COND_ASSIGN_DEFAULT or 0.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_NOT_SUPPORTED
 * \note_graph_thread_safety
 * \notefnerr
 *
 * \sa
 * ::cuGraphAddNode
 */
CUresult CUDAAPI cuGraphConditionalHandleCreate(CUgraphConditionalHandle *pHandle_out, CUgraph hGraph, CUcontext ctx, unsigned int defaultLaunchValue, unsigned int flags);

/** @} */ /* END CUDA_GRAPH */

/**
 * \defgroup CUDA_OCCUPANCY Occupancy
 *
 * ___MANBRIEF___ occupancy calculation functions of the low-level CUDA driver
 * API (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the occupancy calculation functions of the low-level CUDA
 * driver application programming interface.
 *
 * @{
 */

/**
 * \brief Returns occupancy of a function
 *
 * Returns in \p *numBlocks the number of the maximum active blocks per
 * streaming multiprocessor.
 *
 * Note that the API can also be used with context-less kernel ::CUkernel
 * by querying the handle using ::cuLibraryGetKernel() and then passing it
 * to the API by casting to ::CUfunction. Here, the context to use for calculations
 * will be the current context.
 *
 * \param numBlocks       - Returned occupancy
 * \param func            - Kernel for which occupancy is calculated
 * \param blockSize       - Block size the kernel is intended to be launched with
 * \param dynamicSMemSize - Per-block dynamic shared memory usage intended, in bytes
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_UNKNOWN
 * \notefnerr
 *
 * \sa
 * ::cudaOccupancyMaxActiveBlocksPerMultiprocessor
 */
CUresult CUDAAPI cuOccupancyMaxActiveBlocksPerMultiprocessor(int *numBlocks, CUfunction func, int blockSize, size_t dynamicSMemSize);

/**
 * \brief Returns occupancy of a function
 *
 * Returns in \p *numBlocks the number of the maximum active blocks per
 * streaming multiprocessor.
 *
 * The \p Flags parameter controls how special cases are handled. The
 * valid flags are:
 *
 * - ::CU_OCCUPANCY_DEFAULT, which maintains the default behavior as
 *   ::cuOccupancyMaxActiveBlocksPerMultiprocessor;
 *
 * - ::CU_OCCUPANCY_DISABLE_CACHING_OVERRIDE, which suppresses the
 *   default behavior on platform where global caching affects
 *   occupancy. On such platforms, if caching is enabled, but
 *   per-block SM resource usage would result in zero occupancy, the
 *   occupancy calculator will calculate the occupancy as if caching
 *   is disabled. Setting ::CU_OCCUPANCY_DISABLE_CACHING_OVERRIDE makes
 *   the occupancy calculator to return 0 in such cases. More information
 *   can be found about this feature in the "Unified L1/Texture Cache"
 *   section of the Maxwell tuning guide.
 *
 * Note that the API can also be with launch context-less kernel ::CUkernel
 * by querying the handle using ::cuLibraryGetKernel() and then passing it
 * to the API by casting to ::CUfunction. Here, the context to use for calculations
 * will be the current context.
 *
 * \param numBlocks       - Returned occupancy
 * \param func            - Kernel for which occupancy is calculated
 * \param blockSize       - Block size the kernel is intended to be launched with
 * \param dynamicSMemSize - Per-block dynamic shared memory usage intended, in bytes
 * \param flags           - Requested behavior for the occupancy calculator
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_UNKNOWN
 * \notefnerr
 *
 * \sa
 * ::cudaOccupancyMaxActiveBlocksPerMultiprocessorWithFlags
 */
CUresult CUDAAPI cuOccupancyMaxActiveBlocksPerMultiprocessorWithFlags(int *numBlocks, CUfunction func, int blockSize, size_t dynamicSMemSize, unsigned int flags);

/**
 * \brief Suggest a launch configuration with reasonable occupancy
 *
 * Returns in \p *blockSize a reasonable block size that can achieve
 * the maximum occupancy (or, the maximum number of active warps with
 * the fewest blocks per multiprocessor), and in \p *minGridSize the
 * minimum grid size to achieve the maximum occupancy.
 *
 * If \p blockSizeLimit is 0, the configurator will use the maximum
 * block size permitted by the device / function instead.
 *
 * If per-block dynamic shared memory allocation is not needed, the
 * user should leave both \p blockSizeToDynamicSMemSize and \p
 * dynamicSMemSize as 0.
 *
 * If per-block dynamic shared memory allocation is needed, then if
 * the dynamic shared memory size is constant regardless of block
 * size, the size should be passed through \p dynamicSMemSize, and \p
 * blockSizeToDynamicSMemSize should be NULL.
 *
 * Otherwise, if the per-block dynamic shared memory size varies with
 * different block sizes, the user needs to provide a unary function
 * through \p blockSizeToDynamicSMemSize that computes the dynamic
 * shared memory needed by \p func for any given block size. \p
 * dynamicSMemSize is ignored. An example signature is:
 *
 * \code
 *    // Take block size, returns dynamic shared memory needed
 *    size_t blockToSmem(int blockSize);
 * \endcode
 *
 * Note that the API can also be used with context-less kernel ::CUkernel
 * by querying the handle using ::cuLibraryGetKernel() and then passing it
 * to the API by casting to ::CUfunction. Here, the context to use for calculations
 * will be the current context.
 *
 * \param minGridSize - Returned minimum grid size needed to achieve the maximum occupancy
 * \param blockSize   - Returned maximum block size that can achieve the maximum occupancy
 * \param func        - Kernel for which launch configuration is calculated
 * \param blockSizeToDynamicSMemSize - A function that calculates how much per-block dynamic shared memory \p func uses based on the block size
 * \param dynamicSMemSize - Dynamic shared memory usage intended, in bytes
 * \param blockSizeLimit  - The maximum block size \p func is designed to handle
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_UNKNOWN
 * \notefnerr
 *
 * \sa
 * ::cudaOccupancyMaxPotentialBlockSize
 */
CUresult CUDAAPI cuOccupancyMaxPotentialBlockSize(int *minGridSize, int *blockSize, CUfunction func, CUoccupancyB2DSize blockSizeToDynamicSMemSize, size_t dynamicSMemSize, int blockSizeLimit);

/**
 * \brief Suggest a launch configuration with reasonable occupancy
 *
 * An extended version of ::cuOccupancyMaxPotentialBlockSize. In
 * addition to arguments passed to ::cuOccupancyMaxPotentialBlockSize,
 * ::cuOccupancyMaxPotentialBlockSizeWithFlags also takes a \p Flags
 * parameter.
 *
 * The \p Flags parameter controls how special cases are handled. The
 * valid flags are:
 *
 * - ::CU_OCCUPANCY_DEFAULT, which maintains the default behavior as
 *   ::cuOccupancyMaxPotentialBlockSize;
 *
 * - ::CU_OCCUPANCY_DISABLE_CACHING_OVERRIDE, which suppresses the
 *   default behavior on platform where global caching affects
 *   occupancy. On such platforms, the launch configurations that
 *   produces maximal occupancy might not support global
 *   caching. Setting ::CU_OCCUPANCY_DISABLE_CACHING_OVERRIDE
 *   guarantees that the the produced launch configuration is global
 *   caching compatible at a potential cost of occupancy. More information
 *   can be found about this feature in the "Unified L1/Texture Cache"
 *   section of the Maxwell tuning guide.
 *
 * Note that the API can also be used with context-less kernel ::CUkernel
 * by querying the handle using ::cuLibraryGetKernel() and then passing it
 * to the API by casting to ::CUfunction. Here, the context to use for calculations
 * will be the current context.
 *
 * \param minGridSize - Returned minimum grid size needed to achieve the maximum occupancy
 * \param blockSize   - Returned maximum block size that can achieve the maximum occupancy
 * \param func        - Kernel for which launch configuration is calculated
 * \param blockSizeToDynamicSMemSize - A function that calculates how much per-block dynamic shared memory \p func uses based on the block size
 * \param dynamicSMemSize - Dynamic shared memory usage intended, in bytes
 * \param blockSizeLimit  - The maximum block size \p func is designed to handle
 * \param flags       - Options
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_UNKNOWN
 * \notefnerr
 *
 * \sa
 * ::cudaOccupancyMaxPotentialBlockSizeWithFlags
 */
CUresult CUDAAPI cuOccupancyMaxPotentialBlockSizeWithFlags(int *minGridSize, int *blockSize, CUfunction func, CUoccupancyB2DSize blockSizeToDynamicSMemSize, size_t dynamicSMemSize, int blockSizeLimit, unsigned int flags);

/**
 * \brief Returns dynamic shared memory available per block when launching \p numBlocks blocks on SM 
 *
 * Returns in \p *dynamicSmemSize the maximum size of dynamic shared memory to allow \p numBlocks blocks per SM. 
 *
 * Note that the API can also be used with context-less kernel ::CUkernel
 * by querying the handle using ::cuLibraryGetKernel() and then passing it
 * to the API by casting to ::CUfunction. Here, the context to use for calculations
 * will be the current context.
 *
 * \param dynamicSmemSize - Returned maximum dynamic shared memory 
 * \param func            - Kernel function for which occupancy is calculated
 * \param numBlocks       - Number of blocks to fit on SM 
 * \param blockSize       - Size of the blocks
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_UNKNOWN
 * \notefnerr
 */
CUresult CUDAAPI cuOccupancyAvailableDynamicSMemPerBlock(size_t *dynamicSmemSize, CUfunction func, int numBlocks, int blockSize);

/**
 * \brief Given the kernel function (\p func) and launch configuration
 * (\p config), return the maximum cluster size in \p *clusterSize.
 *
 * The cluster dimensions in \p config are ignored. If func has a required
 * cluster size set (see ::cudaFuncGetAttributes / ::cuFuncGetAttribute),\p
 * *clusterSize will reflect the required cluster size.
 *
 * By default this function will always return a value that's portable on
 * future hardware. A higher value may be returned if the kernel function
 * allows non-portable cluster sizes.
 *
 * This function will respect the compile time launch bounds.
 *
 * Note that the API can also be used with context-less kernel ::CUkernel
 * by querying the handle using ::cuLibraryGetKernel() and then passing it
 * to the API by casting to ::CUfunction. Here, the context to use for calculations
 * will either be taken from the specified stream \p config->hStream
 * or the current context in case of NULL stream.
 *
 * \param clusterSize - Returned maximum cluster size that can be launched
 *                      for the given kernel function and launch configuration
 * \param func        - Kernel function for which maximum cluster
 *                      size is calculated
 * \param config      - Launch configuration for the given kernel function
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_UNKNOWN
 * \notefnerr
 *
 * \sa
 * ::cudaFuncGetAttributes,
 * ::cuFuncGetAttribute
 */
CUresult CUDAAPI cuOccupancyMaxPotentialClusterSize(int *clusterSize, CUfunction func, const CUlaunchConfig *config);

/**
 * \brief Given the kernel function (\p func) and launch configuration
 * (\p config), return the maximum number of clusters that could co-exist
 * on the target device in \p *numClusters.
 *
 * If the function has required cluster size already set (see
 * ::cudaFuncGetAttributes / ::cuFuncGetAttribute), the cluster size
 * from config must either be unspecified or match the required size.
 * Without required sizes, the cluster size must be specified in config,
 * else the function will return an error.
 *
 * Note that various attributes of the kernel function may affect occupancy
 * calculation. Runtime environment may affect how the hardware schedules
 * the clusters, so the calculated occupancy is not guaranteed to be achievable.
 *
 * Note that the API can also be used with context-less kernel ::CUkernel
 * by querying the handle using ::cuLibraryGetKernel() and then passing it
 * to the API by casting to ::CUfunction. Here, the context to use for calculations
 * will either be taken from the specified stream \p config->hStream
 * or the current context in case of NULL stream.
 *
 * \param numClusters - Returned maximum number of clusters that
 *                      could co-exist on the target device
 * \param func        - Kernel function for which maximum number
 *                      of clusters are calculated
 * \param config      - Launch configuration for the given kernel function
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_CLUSTER_SIZE,
 * ::CUDA_ERROR_UNKNOWN
 * \notefnerr
 *
 * \sa
 * ::cudaFuncGetAttributes,
 * ::cuFuncGetAttribute
 */
CUresult CUDAAPI cuOccupancyMaxActiveClusters(int *numClusters, CUfunction func, const CUlaunchConfig *config);
/** @} */ /* END CUDA_OCCUPANCY */

/**
 * \defgroup CUDA_TEXREF_DEPRECATED Texture Reference Management [DEPRECATED]
 *
 * ___MANBRIEF___ deprecated texture reference management functions of the
 * low-level CUDA driver API (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the deprecated texture reference management
 * functions of the low-level CUDA driver application programming interface.
 *
 * @{
 */

/**
 * \brief Binds an array as a texture reference
 *
 * \deprecated
 *
 * Binds the CUDA array \p hArray to the texture reference \p hTexRef. Any
 * previous address or CUDA array state associated with the texture reference
 * is superseded by this function. \p Flags must be set to
 * ::CU_TRSA_OVERRIDE_FORMAT. Any CUDA array previously bound to \p hTexRef is
 * unbound.
 *
 * \param hTexRef - Texture reference to bind
 * \param hArray  - Array to bind
 * \param Flags   - Options (must be ::CU_TRSA_OVERRIDE_FORMAT)
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa
 * ::cuTexRefSetAddress,
 * ::cuTexRefSetAddress2D, ::cuTexRefSetAddressMode,
 * ::cuTexRefSetFilterMode, ::cuTexRefSetFlags, ::cuTexRefSetFormat,
 * ::cuTexRefGetAddress, ::cuTexRefGetAddressMode, ::cuTexRefGetArray,
 * ::cuTexRefGetFilterMode, ::cuTexRefGetFlags, ::cuTexRefGetFormat
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuTexRefSetArray(CUtexref hTexRef, CUarray hArray, unsigned int Flags);

/**
 * \brief Binds a mipmapped array to a texture reference
 *
 * \deprecated
 *
 * Binds the CUDA mipmapped array \p hMipmappedArray to the texture reference \p hTexRef.
 * Any previous address or CUDA array state associated with the texture reference
 * is superseded by this function. \p Flags must be set to ::CU_TRSA_OVERRIDE_FORMAT.
 * Any CUDA array previously bound to \p hTexRef is unbound.
 *
 * \param hTexRef         - Texture reference to bind
 * \param hMipmappedArray - Mipmapped array to bind
 * \param Flags           - Options (must be ::CU_TRSA_OVERRIDE_FORMAT)
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa
 * ::cuTexRefSetAddress,
 * ::cuTexRefSetAddress2D, ::cuTexRefSetAddressMode,
 * ::cuTexRefSetFilterMode, ::cuTexRefSetFlags, ::cuTexRefSetFormat,
 * ::cuTexRefGetAddress, ::cuTexRefGetAddressMode, ::cuTexRefGetArray,
 * ::cuTexRefGetFilterMode, ::cuTexRefGetFlags, ::cuTexRefGetFormat
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuTexRefSetMipmappedArray(CUtexref hTexRef, CUmipmappedArray hMipmappedArray, unsigned int Flags);

/**
 * \brief Binds an address as a texture reference
 *
 * \deprecated
 *
 * Binds a linear address range to the texture reference \p hTexRef. Any
 * previous address or CUDA array state associated with the texture reference
 * is superseded by this function. Any memory previously bound to \p hTexRef
 * is unbound.
 *
 * Since the hardware enforces an alignment requirement on texture base
 * addresses, ::cuTexRefSetAddress() passes back a byte offset in
 * \p *ByteOffset that must be applied to texture fetches in order to read from
 * the desired memory. This offset must be divided by the texel size and
 * passed to kernels that read from the texture so they can be applied to the
 * ::tex1Dfetch() function.
 *
 * If the device memory pointer was returned from ::cuMemAlloc(), the offset
 * is guaranteed to be 0 and NULL may be passed as the \p ByteOffset parameter.
 *
 * The total number of elements (or texels) in the linear address range
 * cannot exceed ::CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE1D_LINEAR_WIDTH.
 * The number of elements is computed as (\p bytes / bytesPerElement),
 * where bytesPerElement is determined from the data format and number of
 * components set using ::cuTexRefSetFormat().
 *
 * \param ByteOffset - Returned byte offset
 * \param hTexRef    - Texture reference to bind
 * \param dptr       - Device pointer to bind
 * \param bytes      - Size of memory to bind in bytes
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa
 * ::cuTexRefSetAddress2D, ::cuTexRefSetAddressMode, ::cuTexRefSetArray,
 * ::cuTexRefSetFilterMode, ::cuTexRefSetFlags, ::cuTexRefSetFormat,
 * ::cuTexRefGetAddress, ::cuTexRefGetAddressMode, ::cuTexRefGetArray,
 * ::cuTexRefGetFilterMode, ::cuTexRefGetFlags, ::cuTexRefGetFormat
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuTexRefSetAddress(size_t *ByteOffset, CUtexref hTexRef, CUdeviceptr dptr, size_t bytes);

/**
 * \brief Binds an address as a 2D texture reference
 *
 * \deprecated
 *
 * Binds a linear address range to the texture reference \p hTexRef. Any
 * previous address or CUDA array state associated with the texture reference
 * is superseded by this function. Any memory previously bound to \p hTexRef
 * is unbound.
 *
 * Using a ::tex2D() function inside a kernel requires a call to either
 * ::cuTexRefSetArray() to bind the corresponding texture reference to an
 * array, or ::cuTexRefSetAddress2D() to bind the texture reference to linear
 * memory.
 *
 * Function calls to ::cuTexRefSetFormat() cannot follow calls to
 * ::cuTexRefSetAddress2D() for the same texture reference.
 *
 * It is required that \p dptr be aligned to the appropriate hardware-specific
 * texture alignment. You can query this value using the device attribute
 * ::CU_DEVICE_ATTRIBUTE_TEXTURE_ALIGNMENT. If an unaligned \p dptr is
 * supplied, ::CUDA_ERROR_INVALID_VALUE is returned.
 *
 * \p Pitch has to be aligned to the hardware-specific texture pitch alignment.
 * This value can be queried using the device attribute
 * ::CU_DEVICE_ATTRIBUTE_TEXTURE_PITCH_ALIGNMENT. If an unaligned \p Pitch is
 * supplied, ::CUDA_ERROR_INVALID_VALUE is returned.
 *
 * Width and Height, which are specified in elements (or texels), cannot exceed
 * ::CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_LINEAR_WIDTH and
 * ::CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_LINEAR_HEIGHT respectively.
 * \p Pitch, which is specified in bytes, cannot exceed
 * ::CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_LINEAR_PITCH.
 *
 * \param hTexRef - Texture reference to bind
 * \param desc    - Descriptor of CUDA array
 * \param dptr    - Device pointer to bind
 * \param Pitch   - Line pitch in bytes
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa
 * ::cuTexRefSetAddress,
 * ::cuTexRefSetAddressMode, ::cuTexRefSetArray,
 * ::cuTexRefSetFilterMode, ::cuTexRefSetFlags, ::cuTexRefSetFormat,
 * ::cuTexRefGetAddress, ::cuTexRefGetAddressMode, ::cuTexRefGetArray,
 * ::cuTexRefGetFilterMode, ::cuTexRefGetFlags, ::cuTexRefGetFormat
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuTexRefSetAddress2D(CUtexref hTexRef, const CUDA_ARRAY_DESCRIPTOR *desc, CUdeviceptr dptr, size_t Pitch);

/**
 * \brief Sets the format for a texture reference
 *
 * \deprecated
 *
 * Specifies the format of the data to be read by the texture reference
 * \p hTexRef. \p fmt and \p NumPackedComponents are exactly analogous to the
 * ::Format and ::NumChannels members of the ::CUDA_ARRAY_DESCRIPTOR structure:
 * They specify the format of each component and the number of components per
 * array element.
 *
 * \param hTexRef             - Texture reference
 * \param fmt                 - Format to set
 * \param NumPackedComponents - Number of components per array element
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa
 * ::cuTexRefSetAddress,
 * ::cuTexRefSetAddress2D, ::cuTexRefSetAddressMode, ::cuTexRefSetArray,
 * ::cuTexRefSetFilterMode, ::cuTexRefSetFlags,
 * ::cuTexRefGetAddress, ::cuTexRefGetAddressMode, ::cuTexRefGetArray,
 * ::cuTexRefGetFilterMode, ::cuTexRefGetFlags, ::cuTexRefGetFormat,
 * ::cudaCreateChannelDesc
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuTexRefSetFormat(CUtexref hTexRef, CUarray_format fmt, int NumPackedComponents);

/**
 * \brief Sets the addressing mode for a texture reference
 *
 * \deprecated
 *
 * Specifies the addressing mode \p am for the given dimension \p dim of the
 * texture reference \p hTexRef. If \p dim is zero, the addressing mode is
 * applied to the first parameter of the functions used to fetch from the
 * texture; if \p dim is 1, the second, and so on. ::CUaddress_mode is defined
 * as:
 * \code
   typedef enum CUaddress_mode_enum {
      CU_TR_ADDRESS_MODE_WRAP = 0,
      CU_TR_ADDRESS_MODE_CLAMP = 1,
      CU_TR_ADDRESS_MODE_MIRROR = 2,
      CU_TR_ADDRESS_MODE_BORDER = 3
   } CUaddress_mode;
 * \endcode
 *
 * Note that this call has no effect if \p hTexRef is bound to linear memory.
 * Also, if the flag, ::CU_TRSF_NORMALIZED_COORDINATES, is not set, the only
 * supported address mode is ::CU_TR_ADDRESS_MODE_CLAMP.
 *
 * \param hTexRef - Texture reference
 * \param dim     - Dimension
 * \param am      - Addressing mode to set
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa
 * ::cuTexRefSetAddress,
 * ::cuTexRefSetAddress2D, ::cuTexRefSetArray,
 * ::cuTexRefSetFilterMode, ::cuTexRefSetFlags, ::cuTexRefSetFormat,
 * ::cuTexRefGetAddress, ::cuTexRefGetAddressMode, ::cuTexRefGetArray,
 * ::cuTexRefGetFilterMode, ::cuTexRefGetFlags, ::cuTexRefGetFormat
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuTexRefSetAddressMode(CUtexref hTexRef, int dim, CUaddress_mode am);

/**
 * \brief Sets the filtering mode for a texture reference
 *
 * \deprecated
 *
 * Specifies the filtering mode \p fm to be used when reading memory through
 * the texture reference \p hTexRef. ::CUfilter_mode_enum is defined as:
 *
 * \code
   typedef enum CUfilter_mode_enum {
      CU_TR_FILTER_MODE_POINT = 0,
      CU_TR_FILTER_MODE_LINEAR = 1
   } CUfilter_mode;
 * \endcode
 *
 * Note that this call has no effect if \p hTexRef is bound to linear memory.
 *
 * \param hTexRef - Texture reference
 * \param fm      - Filtering mode to set
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa
 * ::cuTexRefSetAddress,
 * ::cuTexRefSetAddress2D, ::cuTexRefSetAddressMode, ::cuTexRefSetArray,
 * ::cuTexRefSetFlags, ::cuTexRefSetFormat,
 * ::cuTexRefGetAddress, ::cuTexRefGetAddressMode, ::cuTexRefGetArray,
 * ::cuTexRefGetFilterMode, ::cuTexRefGetFlags, ::cuTexRefGetFormat
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuTexRefSetFilterMode(CUtexref hTexRef, CUfilter_mode fm);

/**
 * \brief Sets the mipmap filtering mode for a texture reference
 *
 * \deprecated
 *
 * Specifies the mipmap filtering mode \p fm to be used when reading memory through
 * the texture reference \p hTexRef. ::CUfilter_mode_enum is defined as:
 *
 * \code
   typedef enum CUfilter_mode_enum {
      CU_TR_FILTER_MODE_POINT = 0,
      CU_TR_FILTER_MODE_LINEAR = 1
   } CUfilter_mode;
 * \endcode
 *
 * Note that this call has no effect if \p hTexRef is not bound to a mipmapped array.
 *
 * \param hTexRef - Texture reference
 * \param fm      - Filtering mode to set
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa
 * ::cuTexRefSetAddress,
 * ::cuTexRefSetAddress2D, ::cuTexRefSetAddressMode, ::cuTexRefSetArray,
 * ::cuTexRefSetFlags, ::cuTexRefSetFormat,
 * ::cuTexRefGetAddress, ::cuTexRefGetAddressMode, ::cuTexRefGetArray,
 * ::cuTexRefGetFilterMode, ::cuTexRefGetFlags, ::cuTexRefGetFormat
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuTexRefSetMipmapFilterMode(CUtexref hTexRef, CUfilter_mode fm);

/**
 * \brief Sets the mipmap level bias for a texture reference
 *
 * \deprecated
 *
 * Specifies the mipmap level bias \p bias to be added to the specified mipmap level when
 * reading memory through the texture reference \p hTexRef.
 *
 * Note that this call has no effect if \p hTexRef is not bound to a mipmapped array.
 *
 * \param hTexRef - Texture reference
 * \param bias    - Mipmap level bias
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa
 * ::cuTexRefSetAddress,
 * ::cuTexRefSetAddress2D, ::cuTexRefSetAddressMode, ::cuTexRefSetArray,
 * ::cuTexRefSetFlags, ::cuTexRefSetFormat,
 * ::cuTexRefGetAddress, ::cuTexRefGetAddressMode, ::cuTexRefGetArray,
 * ::cuTexRefGetFilterMode, ::cuTexRefGetFlags, ::cuTexRefGetFormat
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuTexRefSetMipmapLevelBias(CUtexref hTexRef, float bias);

/**
 * \brief Sets the mipmap min/max mipmap level clamps for a texture reference
 *
 * \deprecated
 *
 * Specifies the min/max mipmap level clamps, \p minMipmapLevelClamp and \p maxMipmapLevelClamp
 * respectively, to be used when reading memory through the texture reference
 * \p hTexRef.
 *
 * Note that this call has no effect if \p hTexRef is not bound to a mipmapped array.
 *
 * \param hTexRef        - Texture reference
 * \param minMipmapLevelClamp - Mipmap min level clamp
 * \param maxMipmapLevelClamp - Mipmap max level clamp
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa
 * ::cuTexRefSetAddress,
 * ::cuTexRefSetAddress2D, ::cuTexRefSetAddressMode, ::cuTexRefSetArray,
 * ::cuTexRefSetFlags, ::cuTexRefSetFormat,
 * ::cuTexRefGetAddress, ::cuTexRefGetAddressMode, ::cuTexRefGetArray,
 * ::cuTexRefGetFilterMode, ::cuTexRefGetFlags, ::cuTexRefGetFormat
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuTexRefSetMipmapLevelClamp(CUtexref hTexRef, float minMipmapLevelClamp, float maxMipmapLevelClamp);

/**
 * \brief Sets the maximum anisotropy for a texture reference
 *
 * \deprecated
 *
 * Specifies the maximum anisotropy \p maxAniso to be used when reading memory through
 * the texture reference \p hTexRef.
 *
 * Note that this call has no effect if \p hTexRef is bound to linear memory.
 *
 * \param hTexRef  - Texture reference
 * \param maxAniso - Maximum anisotropy
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa
 * ::cuTexRefSetAddress,
 * ::cuTexRefSetAddress2D, ::cuTexRefSetAddressMode, ::cuTexRefSetArray,
 * ::cuTexRefSetFlags, ::cuTexRefSetFormat,
 * ::cuTexRefGetAddress, ::cuTexRefGetAddressMode, ::cuTexRefGetArray,
 * ::cuTexRefGetFilterMode, ::cuTexRefGetFlags, ::cuTexRefGetFormat
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuTexRefSetMaxAnisotropy(CUtexref hTexRef, unsigned int maxAniso);

/**
 * \brief Sets the border color for a texture reference
 *
 * \deprecated
 *
 * Specifies the value of the RGBA color via the \p pBorderColor to the texture reference
 * \p hTexRef. The color value supports only float type and holds color components in
 * the following sequence:
 * pBorderColor[0] holds 'R' component
 * pBorderColor[1] holds 'G' component
 * pBorderColor[2] holds 'B' component
 * pBorderColor[3] holds 'A' component
 *
 * Note that the color values can be set only when the Address mode is set to
 * CU_TR_ADDRESS_MODE_BORDER using ::cuTexRefSetAddressMode.
 * Applications using integer border color values have to "reinterpret_cast" their values to float.
 *
 * \param hTexRef       - Texture reference
 * \param pBorderColor  - RGBA color
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa
 * ::cuTexRefSetAddressMode,
 * ::cuTexRefGetAddressMode, ::cuTexRefGetBorderColor
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuTexRefSetBorderColor(CUtexref hTexRef, float *pBorderColor);

/**
 * \brief Sets the flags for a texture reference
 *
 * \deprecated
 *
 * Specifies optional flags via \p Flags to specify the behavior of data
 * returned through the texture reference \p hTexRef. The valid flags are:
 *
 * - ::CU_TRSF_READ_AS_INTEGER, which suppresses the default behavior of
 *   having the texture promote integer data to floating point data in the
 *   range [0, 1]. Note that texture with 32-bit integer format
 *   would not be promoted, regardless of whether or not this
 *   flag is specified;
 * - ::CU_TRSF_NORMALIZED_COORDINATES, which suppresses the
 *   default behavior of having the texture coordinates range
 *   from [0, Dim) where Dim is the width or height of the CUDA
 *   array. Instead, the texture coordinates [0, 1.0) reference
 *   the entire breadth of the array dimension;
 * - ::CU_TRSF_DISABLE_TRILINEAR_OPTIMIZATION, which disables any trilinear
 *   filtering optimizations. Trilinear optimizations improve texture filtering
 *   performance by allowing bilinear filtering on textures in scenarios where
 *   it can closely approximate the expected results.
 *
 * \param hTexRef - Texture reference
 * \param Flags   - Optional flags to set
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa
 * ::cuTexRefSetAddress,
 * ::cuTexRefSetAddress2D, ::cuTexRefSetAddressMode, ::cuTexRefSetArray,
 * ::cuTexRefSetFilterMode, ::cuTexRefSetFormat,
 * ::cuTexRefGetAddress, ::cuTexRefGetAddressMode, ::cuTexRefGetArray,
 * ::cuTexRefGetFilterMode, ::cuTexRefGetFlags, ::cuTexRefGetFormat
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuTexRefSetFlags(CUtexref hTexRef, unsigned int Flags);

/**
 * \brief Gets the address associated with a texture reference
 *
 * \deprecated
 *
 * Returns in \p *pdptr the base address bound to the texture reference
 * \p hTexRef, or returns ::CUDA_ERROR_INVALID_VALUE if the texture reference
 * is not bound to any device memory range.
 *
 * \param pdptr   - Returned device address
 * \param hTexRef - Texture reference
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa ::cuTexRefSetAddress,
 * ::cuTexRefSetAddress2D, ::cuTexRefSetAddressMode, ::cuTexRefSetArray,
 * ::cuTexRefSetFilterMode, ::cuTexRefSetFlags, ::cuTexRefSetFormat,
 * ::cuTexRefGetAddressMode, ::cuTexRefGetArray,
 * ::cuTexRefGetFilterMode, ::cuTexRefGetFlags, ::cuTexRefGetFormat
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuTexRefGetAddress(CUdeviceptr *pdptr, CUtexref hTexRef);

/**
 * \brief Gets the array bound to a texture reference
 *
 * \deprecated
 *
 * Returns in \p *phArray the CUDA array bound to the texture reference
 * \p hTexRef, or returns ::CUDA_ERROR_INVALID_VALUE if the texture reference
 * is not bound to any CUDA array.
 *
 * \param phArray - Returned array
 * \param hTexRef - Texture reference
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa ::cuTexRefSetAddress,
 * ::cuTexRefSetAddress2D, ::cuTexRefSetAddressMode, ::cuTexRefSetArray,
 * ::cuTexRefSetFilterMode, ::cuTexRefSetFlags, ::cuTexRefSetFormat,
 * ::cuTexRefGetAddress, ::cuTexRefGetAddressMode,
 * ::cuTexRefGetFilterMode, ::cuTexRefGetFlags, ::cuTexRefGetFormat
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuTexRefGetArray(CUarray *phArray, CUtexref hTexRef);

/**
 * \brief Gets the mipmapped array bound to a texture reference
 *
 * \deprecated
 *
 * Returns in \p *phMipmappedArray the CUDA mipmapped array bound to the texture
 * reference \p hTexRef, or returns ::CUDA_ERROR_INVALID_VALUE if the texture reference
 * is not bound to any CUDA mipmapped array.
 *
 * \param phMipmappedArray - Returned mipmapped array
 * \param hTexRef          - Texture reference
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa ::cuTexRefSetAddress,
 * ::cuTexRefSetAddress2D, ::cuTexRefSetAddressMode, ::cuTexRefSetArray,
 * ::cuTexRefSetFilterMode, ::cuTexRefSetFlags, ::cuTexRefSetFormat,
 * ::cuTexRefGetAddress, ::cuTexRefGetAddressMode,
 * ::cuTexRefGetFilterMode, ::cuTexRefGetFlags, ::cuTexRefGetFormat
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuTexRefGetMipmappedArray(CUmipmappedArray *phMipmappedArray, CUtexref hTexRef);

/**
 * \brief Gets the addressing mode used by a texture reference
 *
 * \deprecated
 *
 * Returns in \p *pam the addressing mode corresponding to the
 * dimension \p dim of the texture reference \p hTexRef. Currently, the only
 * valid value for \p dim are 0 and 1.
 *
 * \param pam     - Returned addressing mode
 * \param hTexRef - Texture reference
 * \param dim     - Dimension
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa ::cuTexRefSetAddress,
 * ::cuTexRefSetAddress2D, ::cuTexRefSetAddressMode, ::cuTexRefSetArray,
 * ::cuTexRefSetFilterMode, ::cuTexRefSetFlags, ::cuTexRefSetFormat,
 * ::cuTexRefGetAddress, ::cuTexRefGetArray,
 * ::cuTexRefGetFilterMode, ::cuTexRefGetFlags, ::cuTexRefGetFormat
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuTexRefGetAddressMode(CUaddress_mode *pam, CUtexref hTexRef, int dim);

/**
 * \brief Gets the filter-mode used by a texture reference
 *
 * \deprecated
 *
 * Returns in \p *pfm the filtering mode of the texture reference
 * \p hTexRef.
 *
 * \param pfm     - Returned filtering mode
 * \param hTexRef - Texture reference
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa ::cuTexRefSetAddress,
 * ::cuTexRefSetAddress2D, ::cuTexRefSetAddressMode, ::cuTexRefSetArray,
 * ::cuTexRefSetFilterMode, ::cuTexRefSetFlags, ::cuTexRefSetFormat,
 * ::cuTexRefGetAddress, ::cuTexRefGetAddressMode, ::cuTexRefGetArray,
 * ::cuTexRefGetFlags, ::cuTexRefGetFormat
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuTexRefGetFilterMode(CUfilter_mode *pfm, CUtexref hTexRef);

/**
 * \brief Gets the format used by a texture reference
 *
 * \deprecated
 *
 * Returns in \p *pFormat and \p *pNumChannels the format and number
 * of components of the CUDA array bound to the texture reference \p hTexRef.
 * If \p pFormat or \p pNumChannels is NULL, it will be ignored.
 *
 * \param pFormat      - Returned format
 * \param pNumChannels - Returned number of components
 * \param hTexRef      - Texture reference
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa ::cuTexRefSetAddress,
 * ::cuTexRefSetAddress2D, ::cuTexRefSetAddressMode, ::cuTexRefSetArray,
 * ::cuTexRefSetFilterMode, ::cuTexRefSetFlags, ::cuTexRefSetFormat,
 * ::cuTexRefGetAddress, ::cuTexRefGetAddressMode, ::cuTexRefGetArray,
 * ::cuTexRefGetFilterMode, ::cuTexRefGetFlags
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuTexRefGetFormat(CUarray_format *pFormat, int *pNumChannels, CUtexref hTexRef);

/**
 * \brief Gets the mipmap filtering mode for a texture reference
 *
 * \deprecated
 *
 * Returns the mipmap filtering mode in \p pfm that's used when reading memory through
 * the texture reference \p hTexRef.
 *
 * \param pfm     - Returned mipmap filtering mode
 * \param hTexRef - Texture reference
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa ::cuTexRefSetAddress,
 * ::cuTexRefSetAddress2D, ::cuTexRefSetAddressMode, ::cuTexRefSetArray,
 * ::cuTexRefSetFlags, ::cuTexRefSetFormat,
 * ::cuTexRefGetAddress, ::cuTexRefGetAddressMode, ::cuTexRefGetArray,
 * ::cuTexRefGetFilterMode, ::cuTexRefGetFlags, ::cuTexRefGetFormat
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuTexRefGetMipmapFilterMode(CUfilter_mode *pfm, CUtexref hTexRef);

/**
 * \brief Gets the mipmap level bias for a texture reference
 *
 * \deprecated
 *
 * Returns the mipmap level bias in \p pBias that's added to the specified mipmap
 * level when reading memory through the texture reference \p hTexRef.
 *
 * \param pbias   - Returned mipmap level bias
 * \param hTexRef - Texture reference
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa ::cuTexRefSetAddress,
 * ::cuTexRefSetAddress2D, ::cuTexRefSetAddressMode, ::cuTexRefSetArray,
 * ::cuTexRefSetFlags, ::cuTexRefSetFormat,
 * ::cuTexRefGetAddress, ::cuTexRefGetAddressMode, ::cuTexRefGetArray,
 * ::cuTexRefGetFilterMode, ::cuTexRefGetFlags, ::cuTexRefGetFormat
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuTexRefGetMipmapLevelBias(float *pbias, CUtexref hTexRef);

/**
 * \brief Gets the min/max mipmap level clamps for a texture reference
 *
 * \deprecated
 *
 * Returns the min/max mipmap level clamps in \p pminMipmapLevelClamp and \p pmaxMipmapLevelClamp
 * that's used when reading memory through the texture reference \p hTexRef.
 *
 * \param pminMipmapLevelClamp - Returned mipmap min level clamp
 * \param pmaxMipmapLevelClamp - Returned mipmap max level clamp
 * \param hTexRef              - Texture reference
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa ::cuTexRefSetAddress,
 * ::cuTexRefSetAddress2D, ::cuTexRefSetAddressMode, ::cuTexRefSetArray,
 * ::cuTexRefSetFlags, ::cuTexRefSetFormat,
 * ::cuTexRefGetAddress, ::cuTexRefGetAddressMode, ::cuTexRefGetArray,
 * ::cuTexRefGetFilterMode, ::cuTexRefGetFlags, ::cuTexRefGetFormat
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuTexRefGetMipmapLevelClamp(float *pminMipmapLevelClamp, float *pmaxMipmapLevelClamp, CUtexref hTexRef);

/**
 * \brief Gets the maximum anisotropy for a texture reference
 *
 * \deprecated
 *
 * Returns the maximum anisotropy in \p pmaxAniso that's used when reading memory through
 * the texture reference \p hTexRef.
 *
 * \param pmaxAniso - Returned maximum anisotropy
 * \param hTexRef   - Texture reference
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa ::cuTexRefSetAddress,
 * ::cuTexRefSetAddress2D, ::cuTexRefSetAddressMode, ::cuTexRefSetArray,
 * ::cuTexRefSetFlags, ::cuTexRefSetFormat,
 * ::cuTexRefGetAddress, ::cuTexRefGetAddressMode, ::cuTexRefGetArray,
 * ::cuTexRefGetFilterMode, ::cuTexRefGetFlags, ::cuTexRefGetFormat
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuTexRefGetMaxAnisotropy(int *pmaxAniso, CUtexref hTexRef);

/**
 * \brief Gets the border color used by a texture reference
 *
 * \deprecated
 *
 * Returns in \p pBorderColor, values of the RGBA color used by
 * the texture reference \p hTexRef.
 * The color value is of type float and holds color components in
 * the following sequence:
 * pBorderColor[0] holds 'R' component
 * pBorderColor[1] holds 'G' component
 * pBorderColor[2] holds 'B' component
 * pBorderColor[3] holds 'A' component
 *
 * \param hTexRef  - Texture reference
 * \param pBorderColor   - Returned Type and Value of RGBA color
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa ::cuTexRefSetAddressMode,
 * ::cuTexRefSetAddressMode, ::cuTexRefSetBorderColor
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuTexRefGetBorderColor(float *pBorderColor, CUtexref hTexRef);

/**
 * \brief Gets the flags used by a texture reference
 *
 * \deprecated
 *
 * Returns in \p *pFlags the flags of the texture reference \p hTexRef.
 *
 * \param pFlags  - Returned flags
 * \param hTexRef - Texture reference
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa ::cuTexRefSetAddress,
 * ::cuTexRefSetAddress2D, ::cuTexRefSetAddressMode, ::cuTexRefSetArray,
 * ::cuTexRefSetFilterMode, ::cuTexRefSetFlags, ::cuTexRefSetFormat,
 * ::cuTexRefGetAddress, ::cuTexRefGetAddressMode, ::cuTexRefGetArray,
 * ::cuTexRefGetFilterMode, ::cuTexRefGetFormat
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuTexRefGetFlags(unsigned int *pFlags, CUtexref hTexRef);

/**
 * \brief Creates a texture reference
 *
 * \deprecated
 *
 * Creates a texture reference and returns its handle in \p *pTexRef. Once
 * created, the application must call ::cuTexRefSetArray() or
 * ::cuTexRefSetAddress() to associate the reference with allocated memory.
 * Other texture reference functions are used to specify the format and
 * interpretation (addressing, filtering, etc.) to be used when the memory is
 * read through this texture reference.
 *
 * \param pTexRef - Returned texture reference
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa ::cuTexRefDestroy
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuTexRefCreate(CUtexref *pTexRef);

/**
 * \brief Destroys a texture reference
 *
 * \deprecated
 *
 * Destroys the texture reference specified by \p hTexRef.
 *
 * \param hTexRef - Texture reference to destroy
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa ::cuTexRefCreate
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuTexRefDestroy(CUtexref hTexRef);

/** @} */ /* END CUDA_TEXREF_DEPRECATED */


/**
 * \defgroup CUDA_SURFREF_DEPRECATED Surface Reference Management [DEPRECATED]
 *
 * ___MANBRIEF___ surface reference management functions of the low-level CUDA
 * driver API (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the surface reference management functions of the
 * low-level CUDA driver application programming interface.
 *
 * @{
 */

/**
 * \brief Sets the CUDA array for a surface reference.
 *
 * \deprecated
 *
 * Sets the CUDA array \p hArray to be read and written by the surface reference
 * \p hSurfRef.  Any previous CUDA array state associated with the surface
 * reference is superseded by this function.  \p Flags must be set to 0.
 * The ::CUDA_ARRAY3D_SURFACE_LDST flag must have been set for the CUDA array.
 * Any CUDA array previously bound to \p hSurfRef is unbound.

 * \param hSurfRef - Surface reference handle
 * \param hArray - CUDA array handle
 * \param Flags - set to 0
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa
 * ::cuModuleGetSurfRef,
 * ::cuSurfRefGetArray
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuSurfRefSetArray(CUsurfref hSurfRef, CUarray hArray, unsigned int Flags);

/**
 * \brief Passes back the CUDA array bound to a surface reference.
 *
 * \deprecated
 *
 * Returns in \p *phArray the CUDA array bound to the surface reference
 * \p hSurfRef, or returns ::CUDA_ERROR_INVALID_VALUE if the surface reference
 * is not bound to any CUDA array.

 * \param phArray - Surface reference handle
 * \param hSurfRef - Surface reference handle
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa ::cuModuleGetSurfRef, ::cuSurfRefSetArray
 */
__CUDA_DEPRECATED CUresult CUDAAPI cuSurfRefGetArray(CUarray *phArray, CUsurfref hSurfRef);

/** @} */ /* END CUDA_SURFREF_DEPRECATED */

/**
 * \defgroup CUDA_TEXOBJECT Texture Object Management
 *
 * ___MANBRIEF___ texture object management functions of the low-level CUDA
 * driver API (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the texture object management functions of the
 * low-level CUDA driver application programming interface. The texture
 * object API is only supported on devices of compute capability 3.0 or higher.
 *
 * @{
 */

/**
 * \brief Creates a texture object
 *
 * Creates a texture object and returns it in \p pTexObject. \p pResDesc describes
 * the data to texture from. \p pTexDesc describes how the data should be sampled.
 * \p pResViewDesc is an optional argument that specifies an alternate format for
 * the data described by \p pResDesc, and also describes the subresource region
 * to restrict access to when texturing. \p pResViewDesc can only be specified if
 * the type of resource is a CUDA array or a CUDA mipmapped array not in a block
 * compressed format.
 *
 * Texture objects are only supported on devices of compute capability 3.0 or higher.
 * Additionally, a texture object is an opaque value, and, as such, should only be
 * accessed through CUDA API calls.
 *
 * The ::CUDA_RESOURCE_DESC structure is defined as:
 * \code
        typedef struct CUDA_RESOURCE_DESC_st
        {
            CUresourcetype resType;

            union {
                struct {
                    CUarray hArray;
                } array;
                struct {
                    CUmipmappedArray hMipmappedArray;
                } mipmap;
                struct {
                    CUdeviceptr devPtr;
                    CUarray_format format;
                    unsigned int numChannels;
                    size_t sizeInBytes;
                } linear;
                struct {
                    CUdeviceptr devPtr;
                    CUarray_format format;
                    unsigned int numChannels;
                    size_t width;
                    size_t height;
                    size_t pitchInBytes;
                } pitch2D;
            } res;

            unsigned int flags;
        } CUDA_RESOURCE_DESC;

 * \endcode
 * where:
 * - ::CUDA_RESOURCE_DESC::resType specifies the type of resource to texture from.
 * CUresourceType is defined as:
 * \code
        typedef enum CUresourcetype_enum {
            CU_RESOURCE_TYPE_ARRAY           = 0x00,
            CU_RESOURCE_TYPE_MIPMAPPED_ARRAY = 0x01,
            CU_RESOURCE_TYPE_LINEAR          = 0x02,
            CU_RESOURCE_TYPE_PITCH2D         = 0x03
        } CUresourcetype;
 * \endcode
 *
 * \par
 * If ::CUDA_RESOURCE_DESC::resType is set to ::CU_RESOURCE_TYPE_ARRAY, ::CUDA_RESOURCE_DESC::res::array::hArray
 * must be set to a valid CUDA array handle.
 *
 * \par
 * If ::CUDA_RESOURCE_DESC::resType is set to ::CU_RESOURCE_TYPE_MIPMAPPED_ARRAY, ::CUDA_RESOURCE_DESC::res::mipmap::hMipmappedArray
 * must be set to a valid CUDA mipmapped array handle.
 *
 * \par
 * If ::CUDA_RESOURCE_DESC::resType is set to ::CU_RESOURCE_TYPE_LINEAR, ::CUDA_RESOURCE_DESC::res::linear::devPtr
 * must be set to a valid device pointer, that is aligned to ::CU_DEVICE_ATTRIBUTE_TEXTURE_ALIGNMENT.
 * ::CUDA_RESOURCE_DESC::res::linear::format and ::CUDA_RESOURCE_DESC::res::linear::numChannels
 * describe the format of each component and the number of components per array element. ::CUDA_RESOURCE_DESC::res::linear::sizeInBytes
 * specifies the size of the array in bytes. The total number of elements in the linear address range cannot exceed
 * ::CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE1D_LINEAR_WIDTH. The number of elements is computed as (sizeInBytes / (sizeof(format) * numChannels)).
 *
 * \par
 * If ::CUDA_RESOURCE_DESC::resType is set to ::CU_RESOURCE_TYPE_PITCH2D, ::CUDA_RESOURCE_DESC::res::pitch2D::devPtr
 * must be set to a valid device pointer, that is aligned to ::CU_DEVICE_ATTRIBUTE_TEXTURE_ALIGNMENT.
 * ::CUDA_RESOURCE_DESC::res::pitch2D::format and ::CUDA_RESOURCE_DESC::res::pitch2D::numChannels
 * describe the format of each component and the number of components per array element. ::CUDA_RESOURCE_DESC::res::pitch2D::width
 * and ::CUDA_RESOURCE_DESC::res::pitch2D::height specify the width and height of the array in elements, and cannot exceed
 * ::CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_LINEAR_WIDTH and ::CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_LINEAR_HEIGHT respectively.
 * ::CUDA_RESOURCE_DESC::res::pitch2D::pitchInBytes specifies the pitch between two rows in bytes and has to be aligned to
 * ::CU_DEVICE_ATTRIBUTE_TEXTURE_PITCH_ALIGNMENT. Pitch cannot exceed ::CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_LINEAR_PITCH.
 *
 * - ::flags must be set to zero.
 *
 *
 * The ::CUDA_TEXTURE_DESC struct is defined as
 * \code
        typedef struct CUDA_TEXTURE_DESC_st {
            CUaddress_mode addressMode[3];
            CUfilter_mode filterMode;
            unsigned int flags;
            unsigned int maxAnisotropy;
            CUfilter_mode mipmapFilterMode;
            float mipmapLevelBias;
            float minMipmapLevelClamp;
            float maxMipmapLevelClamp;
        } CUDA_TEXTURE_DESC;
 * \endcode
 * where
 * - ::CUDA_TEXTURE_DESC::addressMode specifies the addressing mode for each dimension of the texture data. ::CUaddress_mode is defined as:
 *   \code
        typedef enum CUaddress_mode_enum {
            CU_TR_ADDRESS_MODE_WRAP = 0,
            CU_TR_ADDRESS_MODE_CLAMP = 1,
            CU_TR_ADDRESS_MODE_MIRROR = 2,
            CU_TR_ADDRESS_MODE_BORDER = 3
        } CUaddress_mode;
 *   \endcode
 *   This is ignored if ::CUDA_RESOURCE_DESC::resType is ::CU_RESOURCE_TYPE_LINEAR. Also, if the flag, ::CU_TRSF_NORMALIZED_COORDINATES
 *   is not set, the only supported address mode is ::CU_TR_ADDRESS_MODE_CLAMP.
 *
 * - ::CUDA_TEXTURE_DESC::filterMode specifies the filtering mode to be used when fetching from the texture. CUfilter_mode is defined as:
 *   \code
        typedef enum CUfilter_mode_enum {
            CU_TR_FILTER_MODE_POINT = 0,
            CU_TR_FILTER_MODE_LINEAR = 1
        } CUfilter_mode;
 *   \endcode
 *   This is ignored if ::CUDA_RESOURCE_DESC::resType is ::CU_RESOURCE_TYPE_LINEAR.
 *
 * - ::CUDA_TEXTURE_DESC::flags can be any combination of the following:
 *   - ::CU_TRSF_READ_AS_INTEGER, which suppresses the default behavior of
 *   having the texture promote integer data to floating point data in the
 *   range [0, 1]. Note that texture with 32-bit integer format would not be 
 *   promoted, regardless of whether or not this flag is specified.
 *   - ::CU_TRSF_NORMALIZED_COORDINATES, which suppresses the default behavior
 *   of having the texture coordinates range from [0, Dim) where Dim is the 
 *   width or height of the CUDA array. Instead, the texture coordinates 
 *   [0, 1.0) reference the entire breadth of the array dimension; Note that
 *   for CUDA mipmapped arrays, this flag has to be set.
 *   - ::CU_TRSF_DISABLE_TRILINEAR_OPTIMIZATION, which disables any trilinear
 *   filtering optimizations. Trilinear optimizations improve texture filtering
 *   performance by allowing bilinear filtering on textures in scenarios where
 *   it can closely approximate the expected results.
 *   - ::CU_TRSF_SEAMLESS_CUBEMAP, which enables seamless cube map filtering. 
 *   This flag can only be specified if the underlying resource is a CUDA array 
 *   or a CUDA mipmapped array that was created with the flag ::CUDA_ARRAY3D_CUBEMAP.
 *   When seamless cube map filtering is enabled, texture address modes specified 
 *   by ::CUDA_TEXTURE_DESC::addressMode are ignored. Instead, if the ::CUDA_TEXTURE_DESC::filterMode 
 *   is set to ::CU_TR_FILTER_MODE_POINT the address mode ::CU_TR_ADDRESS_MODE_CLAMP 
 *   will be applied for all dimensions. If the ::CUDA_TEXTURE_DESC::filterMode is 
 *   set to ::CU_TR_FILTER_MODE_LINEAR seamless cube map filtering will be performed
 *   when sampling along the cube face borders.
 *
 * - ::CUDA_TEXTURE_DESC::maxAnisotropy specifies the maximum anisotropy ratio to be used when doing anisotropic filtering. This value will be
 *   clamped to the range [1,16].
 *
 * - ::CUDA_TEXTURE_DESC::mipmapFilterMode specifies the filter mode when the calculated mipmap level lies between two defined mipmap levels.
 *
 * - ::CUDA_TEXTURE_DESC::mipmapLevelBias specifies the offset to be applied to the calculated mipmap level.
 *
 * - ::CUDA_TEXTURE_DESC::minMipmapLevelClamp specifies the lower end of the mipmap level range to clamp access to.
 *
 * - ::CUDA_TEXTURE_DESC::maxMipmapLevelClamp specifies the upper end of the mipmap level range to clamp access to.
 *
 *
 * The ::CUDA_RESOURCE_VIEW_DESC struct is defined as
 * \code
        typedef struct CUDA_RESOURCE_VIEW_DESC_st
        {
            CUresourceViewFormat format;
            size_t width;
            size_t height;
            size_t depth;
            unsigned int firstMipmapLevel;
            unsigned int lastMipmapLevel;
            unsigned int firstLayer;
            unsigned int lastLayer;
        } CUDA_RESOURCE_VIEW_DESC;
 * \endcode
 * where:
 * - ::CUDA_RESOURCE_VIEW_DESC::format specifies how the data contained in the CUDA array or CUDA mipmapped array should
 *   be interpreted. Note that this can incur a change in size of the texture data. If the resource view format is a block
 *   compressed format, then the underlying CUDA array or CUDA mipmapped array has to have a base of format ::CU_AD_FORMAT_UNSIGNED_INT32.
 *   with 2 or 4 channels, depending on the block compressed format. For ex., BC1 and BC4 require the underlying CUDA array to have
 *   a format of ::CU_AD_FORMAT_UNSIGNED_INT32 with 2 channels. The other BC formats require the underlying resource to have the same base
 *   format but with 4 channels.
 *
 * - ::CUDA_RESOURCE_VIEW_DESC::width specifies the new width of the texture data. If the resource view format is a block
 *   compressed format, this value has to be 4 times the original width of the resource. For non block compressed formats,
 *   this value has to be equal to that of the original resource.
 *
 * - ::CUDA_RESOURCE_VIEW_DESC::height specifies the new height of the texture data. If the resource view format is a block
 *   compressed format, this value has to be 4 times the original height of the resource. For non block compressed formats,
 *   this value has to be equal to that of the original resource.
 *
 * - ::CUDA_RESOURCE_VIEW_DESC::depth specifies the new depth of the texture data. This value has to be equal to that of the
 *   original resource.
 *
 * - ::CUDA_RESOURCE_VIEW_DESC::firstMipmapLevel specifies the most detailed mipmap level. This will be the new mipmap level zero.
 *   For non-mipmapped resources, this value has to be zero.::CUDA_TEXTURE_DESC::minMipmapLevelClamp and ::CUDA_TEXTURE_DESC::maxMipmapLevelClamp
 *   will be relative to this value. For ex., if the firstMipmapLevel is set to 2, and a minMipmapLevelClamp of 1.2 is specified,
 *   then the actual minimum mipmap level clamp will be 3.2.
 *
 * - ::CUDA_RESOURCE_VIEW_DESC::lastMipmapLevel specifies the least detailed mipmap level. For non-mipmapped resources, this value
 *   has to be zero.
 *
 * - ::CUDA_RESOURCE_VIEW_DESC::firstLayer specifies the first layer index for layered textures. This will be the new layer zero.
 *   For non-layered resources, this value has to be zero.
 *
 * - ::CUDA_RESOURCE_VIEW_DESC::lastLayer specifies the last layer index for layered textures. For non-layered resources,
 *   this value has to be zero.
 *
 *
 * \param pTexObject   - Texture object to create
 * \param pResDesc     - Resource descriptor
 * \param pTexDesc     - Texture descriptor
 * \param pResViewDesc - Resource view descriptor
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa
 * ::cuTexObjectDestroy,
 * ::cudaCreateTextureObject
 */
CUresult CUDAAPI cuTexObjectCreate(CUtexObject *pTexObject, const CUDA_RESOURCE_DESC *pResDesc, const CUDA_TEXTURE_DESC *pTexDesc, const CUDA_RESOURCE_VIEW_DESC *pResViewDesc);

/**
 * \brief Destroys a texture object
 *
 * Destroys the texture object specified by \p texObject.
 *
 * \param texObject - Texture object to destroy
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa
 * ::cuTexObjectCreate,
 * ::cudaDestroyTextureObject
 */
CUresult CUDAAPI cuTexObjectDestroy(CUtexObject texObject);

/**
 * \brief Returns a texture object's resource descriptor
 *
 * Returns the resource descriptor for the texture object specified by \p texObject.
 *
 * \param pResDesc  - Resource descriptor
 * \param texObject - Texture object
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa
 * ::cuTexObjectCreate,
 * ::cudaGetTextureObjectResourceDesc,
 */
CUresult CUDAAPI cuTexObjectGetResourceDesc(CUDA_RESOURCE_DESC *pResDesc, CUtexObject texObject);

/**
 * \brief Returns a texture object's texture descriptor
 *
 * Returns the texture descriptor for the texture object specified by \p texObject.
 *
 * \param pTexDesc  - Texture descriptor
 * \param texObject - Texture object
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa
 * ::cuTexObjectCreate,
 * ::cudaGetTextureObjectTextureDesc
 */
CUresult CUDAAPI cuTexObjectGetTextureDesc(CUDA_TEXTURE_DESC *pTexDesc, CUtexObject texObject);

/**
 * \brief Returns a texture object's resource view descriptor
 *
 * Returns the resource view descriptor for the texture object specified by \p texObject.
 * If no resource view was set for \p texObject, the ::CUDA_ERROR_INVALID_VALUE is returned.
 *
 * \param pResViewDesc - Resource view descriptor
 * \param texObject    - Texture object
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa
 * ::cuTexObjectCreate,
 * ::cudaGetTextureObjectResourceViewDesc
 */
CUresult CUDAAPI cuTexObjectGetResourceViewDesc(CUDA_RESOURCE_VIEW_DESC *pResViewDesc, CUtexObject texObject);

/** @} */ /* END CUDA_TEXOBJECT */

/**
 * \defgroup CUDA_SURFOBJECT Surface Object Management
 *
 * ___MANBRIEF___ surface object management functions of the low-level CUDA
 * driver API (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the surface object management functions of the
 * low-level CUDA driver application programming interface. The surface
 * object API is only supported on devices of compute capability 3.0 or higher.
 *
 * @{
 */

/**
 * \brief Creates a surface object
 *
 * Creates a surface object and returns it in \p pSurfObject. \p pResDesc describes
 * the data to perform surface load/stores on. ::CUDA_RESOURCE_DESC::resType must be
 * ::CU_RESOURCE_TYPE_ARRAY and  ::CUDA_RESOURCE_DESC::res::array::hArray
 * must be set to a valid CUDA array handle. ::CUDA_RESOURCE_DESC::flags must be set to zero.
 *
 * Surface objects are only supported on devices of compute capability 3.0 or higher.
 * Additionally, a surface object is an opaque value, and, as such, should only be
 * accessed through CUDA API calls.
 *
 * \param pSurfObject - Surface object to create
 * \param pResDesc    - Resource descriptor
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa
 * ::cuSurfObjectDestroy,
 * ::cudaCreateSurfaceObject
 */
CUresult CUDAAPI cuSurfObjectCreate(CUsurfObject *pSurfObject, const CUDA_RESOURCE_DESC *pResDesc);

/**
 * \brief Destroys a surface object
 *
 * Destroys the surface object specified by \p surfObject.
 *
 * \param surfObject - Surface object to destroy
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa
 * ::cuSurfObjectCreate,
 * ::cudaDestroySurfaceObject
 */
CUresult CUDAAPI cuSurfObjectDestroy(CUsurfObject surfObject);

/**
 * \brief Returns a surface object's resource descriptor
 *
 * Returns the resource descriptor for the surface object specified by \p surfObject.
 *
 * \param pResDesc   - Resource descriptor
 * \param surfObject - Surface object
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa
 * ::cuSurfObjectCreate,
 * ::cudaGetSurfaceObjectResourceDesc
 */
CUresult CUDAAPI cuSurfObjectGetResourceDesc(CUDA_RESOURCE_DESC *pResDesc, CUsurfObject surfObject);

/** @} */ /* END CUDA_SURFOBJECT */

/**
 * \defgroup CUDA_TENSOR_MEMORY Tensor Map Object Managment
 *
 * ___MANBRIEF___ tensor map object management functions of the low-level CUDA
 * driver API (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the tensor map object management functions of the
 * low-level CUDA driver application programming interface. The tensor
 * core API is only supported on devices of compute capability 9.0 or higher.
 *
 * @{
 */

/**
 * \brief Create a tensor map descriptor object representing tiled memory region
 *
 * Creates a descriptor for Tensor Memory Access (TMA) object specified
 * by the parameters describing a tiled region and returns it in \p tensorMap.
 *
 * Tensor map objects are only supported on devices of compute capability 9.0 or higher.
 * Additionally, a tensor map object is an opaque value, and, as such, should only be
 * accessed through CUDA APIs and PTX.
 *
 * The parameters passed are bound to the following requirements:
 *
 * - \p tensorMap address must be aligned to 64 bytes.
 *
 * - \p tensorDataType has to be an enum from ::CUtensorMapDataType which is defined as:
 * \code
    typedef enum CUtensorMapDataType_enum {
        CU_TENSOR_MAP_DATA_TYPE_UINT8 = 0,       // 1 byte
        CU_TENSOR_MAP_DATA_TYPE_UINT16,          // 2 bytes
        CU_TENSOR_MAP_DATA_TYPE_UINT32,          // 4 bytes
        CU_TENSOR_MAP_DATA_TYPE_INT32,           // 4 bytes
        CU_TENSOR_MAP_DATA_TYPE_UINT64,          // 8 bytes
        CU_TENSOR_MAP_DATA_TYPE_INT64,           // 8 bytes
        CU_TENSOR_MAP_DATA_TYPE_FLOAT16,         // 2 bytes
        CU_TENSOR_MAP_DATA_TYPE_FLOAT32,         // 4 bytes
        CU_TENSOR_MAP_DATA_TYPE_FLOAT64,         // 8 bytes
        CU_TENSOR_MAP_DATA_TYPE_BFLOAT16,        // 2 bytes
        CU_TENSOR_MAP_DATA_TYPE_FLOAT32_FTZ,     // 4 bytes
        CU_TENSOR_MAP_DATA_TYPE_TFLOAT32,        // 4 bytes
        CU_TENSOR_MAP_DATA_TYPE_TFLOAT32_FTZ,    // 4 bytes
        CU_TENSOR_MAP_DATA_TYPE_16U4_ALIGN8B,    // 4 bits
        CU_TENSOR_MAP_DATA_TYPE_16U4_ALIGN16B,   // 4 bits
        CU_TENSOR_MAP_DATA_TYPE_16U6_ALIGN16B    // 6 bits
    } CUtensorMapDataType;
 * \endcode
 *  ::CU_TENSOR_MAP_DATA_TYPE_16U4_ALIGN8B copies '16 x U4' packed values to memory aligned as 8 bytes. There are no gaps between packed values.
 *  ::CU_TENSOR_MAP_DATA_TYPE_16U4_ALIGN16B copies '16 x U4' packed values to memory aligned as 16 bytes. There are 8 byte gaps between every 8 byte chunk of packed values.
 *  ::CU_TENSOR_MAP_DATA_TYPE_16U6_ALIGN16B copies '16 x U6' packed values to memory aligned as 16 bytes. There are 4 byte gaps between every 12 byte chunk of packed values.
 *
 * - \p tensorRank must be non-zero and less than or equal to the maximum supported dimensionality of 5. If \p interleave is not
 * ::CU_TENSOR_MAP_INTERLEAVE_NONE, then \p tensorRank must additionally be greater than or equal to 3.
 *
 * - \p globalAddress, which specifies the starting address of the memory region described, must be 16 byte aligned. The following requirements need to also be met:
 *    - When \p interleave is ::CU_TENSOR_MAP_INTERLEAVE_32B, \p globalAddress must be 32 byte aligned.
 *    - When \p tensorDataType is ::CU_TENSOR_MAP_DATA_TYPE_16U6_ALIGN16B or ::CU_TENSOR_MAP_DATA_TYPE_16U4_ALIGN16B, \p globalAddress must be 32 byte aligned.
 *
  * - \p globalDim array, which specifies tensor size of each of the \p tensorRank dimensions, must be non-zero and less than or
 * equal to 2^32. Additionally, the following requirements need to be met for the packed data types:
 *    - When \p tensorDataType is ::CU_TENSOR_MAP_DATA_TYPE_16U6_ALIGN16B or ::CU_TENSOR_MAP_DATA_TYPE_16U4_ALIGN16B, globalDim[0] must be a multiple of 128.
 *    - When \p tensorDataType is ::CU_TENSOR_MAP_DATA_TYPE_16U4_ALIGN8B, \p globalDim[0] must be a multiple of 2.
 *    - Dimension for the packed data types must reflect the number of individual U# values.
 *
 * - \p globalStrides array, which specifies tensor stride of each of the lower \p tensorRank - 1 dimensions in bytes, must be a
 * multiple of 16 and less than 2^40. Additionally, the following requirements need to be met:
 *    - When \p interleave is ::CU_TENSOR_MAP_INTERLEAVE_32B, the strides must be a multiple of 32.
 *    - When \p tensorDataType is ::CU_TENSOR_MAP_DATA_TYPE_16U6_ALIGN16B or ::CU_TENSOR_MAP_DATA_TYPE_16U4_ALIGN16B, the strides must be a multiple of 32.
 * Each following dimension specified includes previous dimension stride:
 * \code
    globalStrides[0] = globalDim[0] * elementSizeInBytes(tensorDataType) + padding[0];
    for (i = 1; i < tensorRank - 1; i++)
        globalStrides[i] = globalStrides[i – 1] * (globalDim[i] + padding[i]);
        assert(globalStrides[i] >= globalDim[i]);
 * \endcode
 *
 * - \p boxDim array, which specifies number of elements to be traversed along each of the \p tensorRank dimensions, must be non-zero
 * and less than or equal to 256. Additionally, the following requirements need to be met:
 *    - When \p interleave is ::CU_TENSOR_MAP_INTERLEAVE_NONE, { \p boxDim[0] * elementSizeInBytes( \p tensorDataType ) } must be a multiple of 16 bytes.
 *    - When \p tensorDataType is ::CU_TENSOR_MAP_DATA_TYPE_16U6_ALIGN16B or ::CU_TENSOR_MAP_DATA_TYPE_16U4_ALIGN16B, boxDim[0] must be 128.
 *
 * - \p elementStrides array, which specifies the iteration step along each of the \p tensorRank dimensions, must be non-zero and less
 * than or equal to 8. Note that when \p interleave is ::CU_TENSOR_MAP_INTERLEAVE_NONE, the first element of this array is ignored since
 * TMA doesn’t support the stride for dimension zero.
 * When all elements of \p elementStrides array is one, \p boxDim specifies the number of elements to load. However, if the \p elementStrides[i]
 * is not equal to one, then TMA loads ceil( \p boxDim[i] / \p elementStrides[i]) number of elements along i-th dimension. To load N elements along
 * i-th dimension, \p boxDim[i] must be set to N * \p elementStrides[i].
 *
 * - \p interleave specifies the interleaved layout of type ::CUtensorMapInterleave, which is defined as:
 * \code
    typedef enum CUtensorMapInterleave_enum {
        CU_TENSOR_MAP_INTERLEAVE_NONE = 0,
        CU_TENSOR_MAP_INTERLEAVE_16B,
        CU_TENSOR_MAP_INTERLEAVE_32B
    } CUtensorMapInterleave;
 * \endcode
 * TMA supports interleaved layouts like NC/8HWC8 where C8 utilizes 16 bytes in memory assuming 2 byte per channel or NC/16HWC16 where C16
 * uses 32 bytes.
 * When \p interleave is ::CU_TENSOR_MAP_INTERLEAVE_NONE and \p swizzle is not ::CU_TENSOR_MAP_SWIZZLE_NONE, the bounding box inner dimension
 * (computed as \p boxDim[0] multiplied by element size derived from \p tensorDataType) must be less than or equal to the swizzle size.
 *    - CU_TENSOR_MAP_SWIZZLE_32B requires the bounding box inner dimension to be <= 32.
 *    - CU_TENSOR_MAP_SWIZZLE_64B requires the bounding box inner dimension to be <= 64.
 *    - CU_TENSOR_MAP_SWIZZLE_128B* require the bounding box inner dimension to be <= 128.
 * Additionally, \p tensorDataType of ::CU_TENSOR_MAP_DATA_TYPE_16U6_ALIGN16B requires \p interleave to be ::CU_TENSOR_MAP_INTERLEAVE_NONE.
 *
 * - \p swizzle, which specifies the shared memory bank swizzling pattern, has to be of type ::CUtensorMapSwizzle which is defined as:
 * \code
    typedef enum CUtensorMapSwizzle_enum {
        CU_TENSOR_MAP_SWIZZLE_NONE = 0,
        CU_TENSOR_MAP_SWIZZLE_32B,                   // Swizzle 16B chunks within 32B  span
        CU_TENSOR_MAP_SWIZZLE_64B,                   // Swizzle 16B chunks within 64B  span
        CU_TENSOR_MAP_SWIZZLE_128B,                  // Swizzle 16B chunks within 128B span
        CU_TENSOR_MAP_SWIZZLE_128B_ATOM_32B,         // Swizzle 32B chunks within 128B span
        CU_TENSOR_MAP_SWIZZLE_128B_ATOM_32B_FLIP_8B, // Swizzle 32B chunks within 128B span, additionally swap lower 8B with upper 8B within each 16B for every alternate row
        CU_TENSOR_MAP_SWIZZLE_128B_ATOM_64B          // Swizzle 64B chunks within 128B span
    } CUtensorMapSwizzle;
 * \endcode
 * Data are organized in a specific order in global memory; however, this may not match the order in which the application accesses data
 * in shared memory. This difference in data organization may cause bank conflicts when shared memory is accessed. In order to avoid this
 * problem, data can be loaded to shared memory with shuffling across shared memory banks.
 * When \p interleave is ::CU_TENSOR_MAP_INTERLEAVE_32B, \p swizzle must be ::CU_TENSOR_MAP_SWIZZLE_32B.
 * Other interleave modes can have any swizzling pattern.
 * When the \p tensorDataType is ::CU_TENSOR_MAP_DATA_TYPE_16U6_ALIGN16B, only the following swizzle modes are supported:
 *    - CU_TENSOR_MAP_SWIZZLE_NONE (Load & Store)
 *    - CU_TENSOR_MAP_SWIZZLE_128B (Load & Store)
 *    - CU_TENSOR_MAP_SWIZZLE_128B_ATOM_32B (Load & Store)
 *    - CU_TENSOR_MAP_SWIZZLE_128B_ATOM_64B (Store only)
 * When the \p tensorDataType is ::CU_TENSOR_MAP_DATA_TYPE_16U4_ALIGN16B, only the following swizzle modes are supported:
 *    - CU_TENSOR_MAP_SWIZZLE_NONE (Load only)
 *    - CU_TENSOR_MAP_SWIZZLE_128B (Load only)
 *    - CU_TENSOR_MAP_SWIZZLE_128B_ATOM_32B (Load only)
 *
 * - \p l2Promotion specifies L2 fetch size which indicates the byte granurality at which L2 requests is filled from DRAM. It must be of
 * type ::CUtensorMapL2promotion, which is defined as:
 * \code
    typedef enum CUtensorMapL2promotion_enum {
        CU_TENSOR_MAP_L2_PROMOTION_NONE = 0,
        CU_TENSOR_MAP_L2_PROMOTION_L2_64B,
        CU_TENSOR_MAP_L2_PROMOTION_L2_128B,
        CU_TENSOR_MAP_L2_PROMOTION_L2_256B
    } CUtensorMapL2promotion;
 * \endcode
 *
 * - \p oobFill, which indicates whether zero or a special NaN constant should be used to fill out-of-bound elements, must be of type
 * ::CUtensorMapFloatOOBfill which is defined as:
 * \code
    typedef enum CUtensorMapFloatOOBfill_enum {
        CU_TENSOR_MAP_FLOAT_OOB_FILL_NONE = 0,
        CU_TENSOR_MAP_FLOAT_OOB_FILL_NAN_REQUEST_ZERO_FMA
    } CUtensorMapFloatOOBfill;
 * \endcode
 * Note that ::CU_TENSOR_MAP_FLOAT_OOB_FILL_NAN_REQUEST_ZERO_FMA can only be used when \p tensorDataType represents a floating-point data type,
 * and when \p tensorDataType is not ::CU_TENSOR_MAP_DATA_TYPE_16U4_ALIGN8B, ::CU_TENSOR_MAP_DATA_TYPE_16U4_ALIGN16B, and ::CU_TENSOR_MAP_DATA_TYPE_16U6_ALIGN16B.
 *
 * \param tensorMap         - Tensor map object to create
 * \param tensorDataType    - Tensor data type
 * \param tensorRank        - Dimensionality of tensor
 * \param globalAddress     - Starting address of memory region described by tensor
 * \param globalDim         - Array containing tensor size (number of elements) along each of the \p tensorRank dimensions
 * \param globalStrides     - Array containing stride size (in bytes) along each of the \p tensorRank - 1 dimensions
 * \param boxDim            - Array containing traversal box size (number of elments) along each of the \p tensorRank dimensions. Specifies how many elements to be traversed along each tensor dimension.
 * \param elementStrides    - Array containing traversal stride in each of the \p tensorRank dimensions
 * \param interleave        - Type of interleaved layout the tensor addresses
 * \param swizzle           - Bank swizzling pattern inside shared memory
 * \param l2Promotion       - L2 promotion size
 * \param oobFill           - Indicate whether zero or special NaN constant must be used to fill out-of-bound elements
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa
 * ::cuTensorMapEncodeIm2col,
 * ::cuTensorMapEncodeIm2colWide,
 * ::cuTensorMapReplaceAddress
 */
CUresult CUDAAPI cuTensorMapEncodeTiled(CUtensorMap *tensorMap, CUtensorMapDataType tensorDataType, cuuint32_t tensorRank, void *globalAddress, const cuuint64_t *globalDim, const cuuint64_t *globalStrides, const cuuint32_t *boxDim, const cuuint32_t *elementStrides, CUtensorMapInterleave interleave, CUtensorMapSwizzle swizzle, CUtensorMapL2promotion l2Promotion, CUtensorMapFloatOOBfill oobFill);

/**
 * \brief Create a tensor map descriptor object representing im2col memory region
 *
 * Creates a descriptor for Tensor Memory Access (TMA) object specified
 * by the parameters describing a im2col memory layout and returns it in \p tensorMap.
 *
 * Tensor map objects are only supported on devices of compute capability 9.0 or higher.
 * Additionally, a tensor map object is an opaque value, and, as such, should only be
 * accessed through CUDA APIs and PTX.
 *
 * The parameters passed are bound to the following requirements:
 *
 * - \p tensorMap address must be aligned to 64 bytes.
 *
 * - \p tensorDataType has to be an enum from ::CUtensorMapDataType which is defined as:
 * \code
    typedef enum CUtensorMapDataType_enum {
        CU_TENSOR_MAP_DATA_TYPE_UINT8 = 0,       // 1 byte
        CU_TENSOR_MAP_DATA_TYPE_UINT16,          // 2 bytes
        CU_TENSOR_MAP_DATA_TYPE_UINT32,          // 4 bytes
        CU_TENSOR_MAP_DATA_TYPE_INT32,           // 4 bytes
        CU_TENSOR_MAP_DATA_TYPE_UINT64,          // 8 bytes
        CU_TENSOR_MAP_DATA_TYPE_INT64,           // 8 bytes
        CU_TENSOR_MAP_DATA_TYPE_FLOAT16,         // 2 bytes
        CU_TENSOR_MAP_DATA_TYPE_FLOAT32,         // 4 bytes
        CU_TENSOR_MAP_DATA_TYPE_FLOAT64,         // 8 bytes
        CU_TENSOR_MAP_DATA_TYPE_BFLOAT16,        // 2 bytes
        CU_TENSOR_MAP_DATA_TYPE_FLOAT32_FTZ,     // 4 bytes
        CU_TENSOR_MAP_DATA_TYPE_TFLOAT32,        // 4 bytes
        CU_TENSOR_MAP_DATA_TYPE_TFLOAT32_FTZ     // 4 bytes
        CU_TENSOR_MAP_DATA_TYPE_16U4_ALIGN8B,    // 4 bits
        CU_TENSOR_MAP_DATA_TYPE_16U4_ALIGN16B,   // 4 bits
        CU_TENSOR_MAP_DATA_TYPE_16U6_ALIGN16B    // 6 bits
    } CUtensorMapDataType;
 * \endcode
 *  ::CU_TENSOR_MAP_DATA_TYPE_16U4_ALIGN8B copies '16 x U4' packed values to memory aligned as 8 bytes. There are no gaps between packed values.
 *  ::CU_TENSOR_MAP_DATA_TYPE_16U4_ALIGN16B copies '16 x U4' packed values to memory aligned as 16 bytes. There are 8 byte gaps between every 8 byte chunk of packed values.
 *  ::CU_TENSOR_MAP_DATA_TYPE_16U6_ALIGN16B copies '16 x U6' packed values to memory aligned as 16 bytes. There are 4 byte gaps between every 12 byte chunk of packed values.
 *
 * - \p tensorRank, which specifies the number of tensor dimensions, must be 3, 4, or 5.
 *
 * - \p globalAddress, which specifies the starting address of the memory region described, must be 16 byte aligned. The following requirements need to also be met:
 *    - When \p interleave is ::CU_TENSOR_MAP_INTERLEAVE_32B, \p globalAddress must be 32 byte aligned.
 *    - When \p tensorDataType is ::CU_TENSOR_MAP_DATA_TYPE_16U6_ALIGN16B or ::CU_TENSOR_MAP_DATA_TYPE_16U4_ALIGN16B, \p globalAddress must be 32 byte aligned.
 *
 * - \p globalDim array, which specifies tensor size of each of the \p tensorRank dimensions, must be non-zero and less than or
 * equal to 2^32. Additionally, the following requirements need to be met for the packed data types:
 *    - When \p tensorDataType is ::CU_TENSOR_MAP_DATA_TYPE_16U6_ALIGN16B or ::CU_TENSOR_MAP_DATA_TYPE_16U4_ALIGN16B, globalDim[0] must be a multiple of 128.
 *    - When \p tensorDataType is ::CU_TENSOR_MAP_DATA_TYPE_16U4_ALIGN8B, \p globalDim[0] must be a multiple of 2.
 *    - Dimension for the packed data types must reflect the number of individual U# values.
 *
 * - \p globalStrides array, which specifies tensor stride of each of the lower \p tensorRank - 1 dimensions in bytes, must be a
 * multiple of 16 and less than 2^40. Additionally, the following requirements need to be met:
 *    - When \p interleave is ::CU_TENSOR_MAP_INTERLEAVE_32B, the strides must be a multiple of 32.
 *    - When \p tensorDataType is ::CU_TENSOR_MAP_DATA_TYPE_16U6_ALIGN16B or ::CU_TENSOR_MAP_DATA_TYPE_16U4_ALIGN16B, the strides must be a multiple of 32.
 * Each following dimension specified includes previous dimension stride:
 * \code
    globalStrides[0] = globalDim[0] * elementSizeInBytes(tensorDataType) + padding[0];
    for (i = 1; i < tensorRank - 1; i++)
        globalStrides[i] = globalStrides[i – 1] * (globalDim[i] + padding[i]);
        assert(globalStrides[i] >= globalDim[i]);
 * \endcode
 *
 * - \p pixelBoxLowerCorner array specifies the coordinate offsets {D, H, W} of the bounding box from top/left/front corner. The number of
 * offsets and their precision depend on the tensor dimensionality:
 *    - When \p tensorRank is 3, one signed offset within range [-32768, 32767] is supported.
 *    - When \p tensorRank is 4, two signed offsets each within range [-128, 127] are supported.
 *    - When \p tensorRank is 5, three offsets each within range [-16, 15] are supported.
 *
 * - \p pixelBoxUpperCorner array specifies the coordinate offsets {D, H, W} of the bounding box from bottom/right/back corner. The number of
 * offsets and their precision depend on the tensor dimensionality:
 *    - When \p tensorRank is 3, one signed offset within range [-32768, 32767] is supported.
 *    - When \p tensorRank is 4, two signed offsets each within range [-128, 127] are supported.
 *    - When \p tensorRank is 5, three offsets each within range [-16, 15] are supported.
 * The bounding box specified by \p pixelBoxLowerCorner and \p pixelBoxUpperCorner must have non-zero area.
 *
 * - \p channelsPerPixel, which specifies the number of elements which must be accessed along C dimension, must be less than or equal to 256.
 * Additionally, when \p tensorDataType is ::CU_TENSOR_MAP_DATA_TYPE_16U6_ALIGN16B or ::CU_TENSOR_MAP_DATA_TYPE_16U4_ALIGN16B, \p channelsPerPixel must be 128.
 *
 * - \p pixelsPerColumn, which specifies the number of elements that must be accessed along the {N, D, H, W} dimensions, must be less than or
 * equal to 1024.
 *
 * - \p elementStrides array, which specifies the iteration step along each of the \p tensorRank dimensions, must be non-zero and less
 * than or equal to 8. Note that when \p interleave is ::CU_TENSOR_MAP_INTERLEAVE_NONE, the first element of this array is ignored since
 * TMA doesn’t support the stride for dimension zero.
 * When all elements of the \p elementStrides array are one, \p boxDim specifies the number of elements to load. However, if \p elementStrides[i]
 * is not equal to one for some \p i, then TMA loads ceil( \p boxDim[i] / \p elementStrides[i]) number of elements along i-th dimension.
 * To load N elements along i-th dimension, \p boxDim[i] must be set to N * \p elementStrides[i].
 *
 * - \p interleave specifies the interleaved layout of type ::CUtensorMapInterleave, which is defined as:
 * \code
    typedef enum CUtensorMapInterleave_enum {
        CU_TENSOR_MAP_INTERLEAVE_NONE = 0,
        CU_TENSOR_MAP_INTERLEAVE_16B,
        CU_TENSOR_MAP_INTERLEAVE_32B
    } CUtensorMapInterleave;
 * \endcode
 * TMA supports interleaved layouts like NC/8HWC8 where C8 utilizes 16 bytes in memory assuming 2 byte per channel or NC/16HWC16 where C16
 * uses 32 bytes.
 * When \p interleave is ::CU_TENSOR_MAP_INTERLEAVE_NONE and \p swizzle is not ::CU_TENSOR_MAP_SWIZZLE_NONE, the bounding box inner dimension
 * (computed as \p channelsPerPixel multiplied by element size in bytes derived from \p tensorDataType) must be less than or equal to the swizzle size.
 *    - CU_TENSOR_MAP_SWIZZLE_32B requires the bounding box inner dimension to be <= 32.
 *    - CU_TENSOR_MAP_SWIZZLE_64B requires the bounding box inner dimension to be <= 64.
 *    - CU_TENSOR_MAP_SWIZZLE_128B* require the bounding box inner dimension to be <= 128.
 * Additionally, \p tensorDataType of ::CU_TENSOR_MAP_DATA_TYPE_16U6_ALIGN16B requires \p interleave to be ::CU_TENSOR_MAP_INTERLEAVE_NONE.
 *
 * - \p swizzle, which specifies the shared memory bank swizzling pattern, has to be of type ::CUtensorMapSwizzle which is defined as:
 * \code
    typedef enum CUtensorMapSwizzle_enum {
        CU_TENSOR_MAP_SWIZZLE_NONE = 0,
        CU_TENSOR_MAP_SWIZZLE_32B,                   // Swizzle 16B chunks within 32B  span
        CU_TENSOR_MAP_SWIZZLE_64B,                   // Swizzle 16B chunks within 64B  span
        CU_TENSOR_MAP_SWIZZLE_128B,                  // Swizzle 16B chunks within 128B span
        CU_TENSOR_MAP_SWIZZLE_128B_ATOM_32B,         // Swizzle 32B chunks within 128B span
        CU_TENSOR_MAP_SWIZZLE_128B_ATOM_32B_FLIP_8B, // Swizzle 32B chunks within 128B span, additionally swap lower 8B with upper 8B within each 16B for every alternate row
        CU_TENSOR_MAP_SWIZZLE_128B_ATOM_64B          // Swizzle 64B chunks within 128B span
    } CUtensorMapSwizzle;
 * \endcode
 * Data are organized in a specific order in global memory; however, this may not match the order in which the application accesses data
 * in shared memory. This difference in data organization may cause bank conflicts when shared memory is accessed. In order to avoid this
 * problem, data can be loaded to shared memory with shuffling across shared memory banks.
 * When \p interleave is ::CU_TENSOR_MAP_INTERLEAVE_32B, \p swizzle must be ::CU_TENSOR_MAP_SWIZZLE_32B.
 * Other interleave modes can have any swizzling pattern.
 * When the \p tensorDataType is ::CU_TENSOR_MAP_DATA_TYPE_16U6_ALIGN16B, only the following swizzle modes are supported:
 *    - CU_TENSOR_MAP_SWIZZLE_NONE (Load & Store)
 *    - CU_TENSOR_MAP_SWIZZLE_128B (Load & Store)
 *    - CU_TENSOR_MAP_SWIZZLE_128B_ATOM_32B (Load & Store)
 *    - CU_TENSOR_MAP_SWIZZLE_128B_ATOM_64B (Store only)
 * When the \p tensorDataType is ::CU_TENSOR_MAP_DATA_TYPE_16U4_ALIGN16B, only the following swizzle modes are supported:
 *    - CU_TENSOR_MAP_SWIZZLE_NONE (Load only)
 *    - CU_TENSOR_MAP_SWIZZLE_128B (Load only)
 *    - CU_TENSOR_MAP_SWIZZLE_128B_ATOM_32B (Load only)
 *
 * - \p l2Promotion specifies L2 fetch size which indicates the byte granularity at which L2 requests are filled from DRAM. It must be of
 * type ::CUtensorMapL2promotion, which is defined as:
 * \code
    typedef enum CUtensorMapL2promotion_enum {
        CU_TENSOR_MAP_L2_PROMOTION_NONE = 0,
        CU_TENSOR_MAP_L2_PROMOTION_L2_64B,
        CU_TENSOR_MAP_L2_PROMOTION_L2_128B,
        CU_TENSOR_MAP_L2_PROMOTION_L2_256B
    } CUtensorMapL2promotion;
 * \endcode
 *
 * - \p oobFill, which indicates whether zero or a special NaN constant should be used to fill out-of-bound elements, must be of type
 * ::CUtensorMapFloatOOBfill which is defined as:
 * \code
    typedef enum CUtensorMapFloatOOBfill_enum {
        CU_TENSOR_MAP_FLOAT_OOB_FILL_NONE = 0,
        CU_TENSOR_MAP_FLOAT_OOB_FILL_NAN_REQUEST_ZERO_FMA
    } CUtensorMapFloatOOBfill;
 * \endcode
 * Note that ::CU_TENSOR_MAP_FLOAT_OOB_FILL_NAN_REQUEST_ZERO_FMA can only be used when \p tensorDataType represents a floating-point data type,
 * and when \p tensorDataType is not ::CU_TENSOR_MAP_DATA_TYPE_16U4_ALIGN8B, ::CU_TENSOR_MAP_DATA_TYPE_16U4_ALIGN16B, and ::CU_TENSOR_MAP_DATA_TYPE_16U6_ALIGN16B.
 *
 * \param tensorMap             - Tensor map object to create
 * \param tensorDataType        - Tensor data type
 * \param tensorRank            - Dimensionality of tensor; must be at least 3
 * \param globalAddress         - Starting address of memory region described by tensor
 * \param globalDim             - Array containing tensor size (number of elements) along each of the \p tensorRank dimensions
 * \param globalStrides         - Array containing stride size (in bytes) along each of the \p tensorRank - 1 dimensions
 * \param pixelBoxLowerCorner   - Array containing DHW dimensions of lower box corner
 * \param pixelBoxUpperCorner   - Array containing DHW dimensions of upper box corner
 * \param channelsPerPixel      - Number of channels per pixel
 * \param pixelsPerColumn       - Number of pixels per column
 * \param elementStrides        - Array containing traversal stride in each of the \p tensorRank dimensions
 * \param interleave            - Type of interleaved layout the tensor addresses
 * \param swizzle               - Bank swizzling pattern inside shared memory
 * \param l2Promotion           - L2 promotion size
 * \param oobFill               - Indicate whether zero or special NaN constant will be used to fill out-of-bound elements
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa
 * ::cuTensorMapEncodeTiled,
 * ::cuTensorMapEncodeIm2colWide,
 * ::cuTensorMapReplaceAddress
 */
CUresult CUDAAPI cuTensorMapEncodeIm2col(CUtensorMap *tensorMap, CUtensorMapDataType tensorDataType, cuuint32_t tensorRank, void *globalAddress, const cuuint64_t *globalDim, const cuuint64_t *globalStrides, const int *pixelBoxLowerCorner, const int *pixelBoxUpperCorner, cuuint32_t channelsPerPixel, cuuint32_t pixelsPerColumn, const cuuint32_t *elementStrides, CUtensorMapInterleave interleave, CUtensorMapSwizzle swizzle, CUtensorMapL2promotion l2Promotion, CUtensorMapFloatOOBfill oobFill);

/**
 * \brief Create a tensor map descriptor object representing im2col memory region, but where
 * the elements are exclusively loaded along the W dimension.
 *
 * Creates a descriptor for Tensor Memory Access (TMA) object specified by the parameters
 * describing a im2col memory layout and where the row is always loaded along the W dimensuin
 * and returns it in \p tensorMap. This assumes the tensor layout in memory is either NDHWC,
 * NHWC, or NWC.
 *
 * This API is only supported on devices of compute capability 10.0 or higher.
 * Additionally, a tensor map object is an opaque value, and, as such, should only be
 * accessed through CUDA APIs and PTX.
 *
 * The parameters passed are bound to the following requirements:
 *
 * - \p tensorMap address must be aligned to 64 bytes.
 *
 * - \p tensorDataType has to be an enum from ::CUtensorMapDataType which is defined as:
 * \code
    typedef enum CUtensorMapDataType_enum {
        CU_TENSOR_MAP_DATA_TYPE_UINT8 = 0,       // 1 byte
        CU_TENSOR_MAP_DATA_TYPE_UINT16,          // 2 bytes
        CU_TENSOR_MAP_DATA_TYPE_UINT32,          // 4 bytes
        CU_TENSOR_MAP_DATA_TYPE_INT32,           // 4 bytes
        CU_TENSOR_MAP_DATA_TYPE_UINT64,          // 8 bytes
        CU_TENSOR_MAP_DATA_TYPE_INT64,           // 8 bytes
        CU_TENSOR_MAP_DATA_TYPE_FLOAT16,         // 2 bytes
        CU_TENSOR_MAP_DATA_TYPE_FLOAT32,         // 4 bytes
        CU_TENSOR_MAP_DATA_TYPE_FLOAT64,         // 8 bytes
        CU_TENSOR_MAP_DATA_TYPE_BFLOAT16,        // 2 bytes
        CU_TENSOR_MAP_DATA_TYPE_FLOAT32_FTZ,     // 4 bytes
        CU_TENSOR_MAP_DATA_TYPE_TFLOAT32,        // 4 bytes
        CU_TENSOR_MAP_DATA_TYPE_TFLOAT32_FTZ     // 4 bytes
        CU_TENSOR_MAP_DATA_TYPE_16U4_ALIGN8B,    // 4 bits
        CU_TENSOR_MAP_DATA_TYPE_16U4_ALIGN16B,   // 4 bits
        CU_TENSOR_MAP_DATA_TYPE_16U6_ALIGN16B    // 6 bits
    } CUtensorMapDataType;
 * \endcode
 *  ::CU_TENSOR_MAP_DATA_TYPE_16U4_ALIGN8B copies '16 x U4' packed values to memory aligned as 8 bytes. There are no gaps between packed values.
 *  ::CU_TENSOR_MAP_DATA_TYPE_16U4_ALIGN16B copies '16 x U4' packed values to memory aligned as 16 bytes. There are 8 byte gaps between every 8 byte chunk of packed values.
 *  ::CU_TENSOR_MAP_DATA_TYPE_16U6_ALIGN16B copies '16 x U6' packed values to memory aligned as 16 bytes. There are 4 byte gaps between every 12 byte chunk of packed values.
 *
 * - \p tensorRank, which specifies the number of tensor dimensions, must be 3, 4, or 5.
 *
 * - \p globalAddress, which specifies the starting address of the memory region described, must be 16 byte aligned. The following requirements need to also be met:
 *    - When \p interleave is ::CU_TENSOR_MAP_INTERLEAVE_32B, \p globalAddress must be 32 byte aligned.
 *    - When \p tensorDataType is ::CU_TENSOR_MAP_DATA_TYPE_16U6_ALIGN16B or ::CU_TENSOR_MAP_DATA_TYPE_16U4_ALIGN16B, \p globalAddress must be 32 byte aligned.
 *
  * - \p globalDim array, which specifies tensor size of each of the \p tensorRank dimensions, must be non-zero and less than or
 * equal to 2^32. Additionally, the following requirements need to be met for the packed data types:
 *    - When \p tensorDataType is ::CU_TENSOR_MAP_DATA_TYPE_16U6_ALIGN16B or ::CU_TENSOR_MAP_DATA_TYPE_16U4_ALIGN16B, globalDim[0] must be a multiple of 128.
 *    - When \p tensorDataType is ::CU_TENSOR_MAP_DATA_TYPE_16U4_ALIGN8B, \p globalDim[0] must be a multiple of 2.
 *    - Dimension for the packed data types must reflect the number of individual U# values.
 *
 * - \p globalStrides array, which specifies tensor stride of each of the lower \p tensorRank - 1 dimensions in bytes, must be a
 * multiple of 16 and less than 2^40. Additionally, the following requirements need to be met:
 *    - When \p interleave is ::CU_TENSOR_MAP_INTERLEAVE_32B, the strides must be a multiple of 32.
 *    - When \p tensorDataType is ::CU_TENSOR_MAP_DATA_TYPE_16U6_ALIGN16B or ::CU_TENSOR_MAP_DATA_TYPE_16U4_ALIGN16B, the strides must be a multiple of 32.
 * Each following dimension specified includes previous dimension stride:
 * \code
    globalStrides[0] = globalDim[0] * elementSizeInBytes(tensorDataType) + padding[0];
    for (i = 1; i < tensorRank - 1; i++)
        globalStrides[i] = globalStrides[i – 1] * (globalDim[i] + padding[i]);
        assert(globalStrides[i] >= globalDim[i]);
 * \endcode
 *
 * - \p pixelBoxLowerCornerWidth specifies the coordinate offset W of the bounding box from left corner. The offset must be
 * within range [-32768, 32767].
 *
 * - \p pixelBoxUpperCornerWidth specifies the coordinate offset W of the bounding box from right corner. The offset must be
 * within range [-32768, 32767].
 *
 * The bounding box specified by \p pixelBoxLowerCornerWidth and \p pixelBoxUpperCornerWidth must have non-zero area. Note
 * that the size of the box along D and H dimensions is always equal to one.
 *
 * - \p channelsPerPixel, which specifies the number of elements which must be accessed along C dimension, must be less than or equal to 256.
 * Additionally, when \p tensorDataType is ::CU_TENSOR_MAP_DATA_TYPE_16U6_ALIGN16B or ::CU_TENSOR_MAP_DATA_TYPE_16U4_ALIGN16B, \p channelsPerPixel must be 128.
 *
 * - \p pixelsPerColumn, which specifies the number of elements that must be accessed along the W dimension, must be less than or
 * equal to 1024. This field is ignored when \p mode is ::CU_TENSOR_MAP_IM2COL_WIDE_MODE_W128.
 *
 * - \p elementStrides array, which specifies the iteration step along each of the \p tensorRank dimensions, must be non-zero and less
 * than or equal to 8. Note that when \p interleave is ::CU_TENSOR_MAP_INTERLEAVE_NONE, the first element of this array is ignored since
 * TMA doesn’t support the stride for dimension zero.
 * When all elements of the \p elementStrides array are one, \p boxDim specifies the number of elements to load. However, if \p elementStrides[i]
 * is not equal to one for some \p i, then TMA loads ceil( \p boxDim[i] / \p elementStrides[i]) number of elements along i-th dimension.
 * To load N elements along i-th dimension, \p boxDim[i] must be set to N * \p elementStrides[i].
 *
 * - \p interleave specifies the interleaved layout of type ::CUtensorMapInterleave, which is defined as:
 * \code
    typedef enum CUtensorMapInterleave_enum {
        CU_TENSOR_MAP_INTERLEAVE_NONE = 0,
        CU_TENSOR_MAP_INTERLEAVE_16B,
        CU_TENSOR_MAP_INTERLEAVE_32B
    } CUtensorMapInterleave;
 * \endcode
 * TMA supports interleaved layouts like NC/8HWC8 where C8 utilizes 16 bytes in memory assuming 2 byte per channel or NC/16HWC16 where C16
 * uses 32 bytes.
 * When \p interleave is ::CU_TENSOR_MAP_INTERLEAVE_NONE, the bounding box inner dimension (computed as \p channelsPerPixel multiplied by
 * element size in bytes derived from \p tensorDataType) must be less than or equal to the swizzle size.
 *    - CU_TENSOR_MAP_SWIZZLE_64B requires the bounding box inner dimension to be <= 64.
 *    - CU_TENSOR_MAP_SWIZZLE_128B* require the bounding box inner dimension to be <= 128.
 * Additionally, \p tensorDataType of ::CU_TENSOR_MAP_DATA_TYPE_16U6_ALIGN16B requires \p interleave to be ::CU_TENSOR_MAP_INTERLEAVE_NONE.
 *
 * - \p mode, which describes loading of elements loaded along the W dimension, has to be one of the following ::CUtensorMapIm2ColWideMode types:
 * \code
 *          CU_TENSOR_MAP_IM2COL_WIDE_MODE_W,
 *          CU_TENSOR_MAP_IM2COL_WIDE_MODE_W128
 * \endcode
 * ::CU_TENSOR_MAP_IM2COL_WIDE_MODE_W allows the number of elements loaded along the W dimension to be specified
 * via the \p pixelsPerColumn field.
 *
 * - \p swizzle, which specifies the shared memory bank swizzling pattern, must be one of the following
 * ::CUtensorMapSwizzle modes (other swizzle modes are not supported):
 * \code
    typedef enum CUtensorMapSwizzle_enum {
        CU_TENSOR_MAP_SWIZZLE_64B,                   // Swizzle 16B chunks within 64B  span
        CU_TENSOR_MAP_SWIZZLE_128B,                  // Swizzle 16B chunks within 128B span
        CU_TENSOR_MAP_SWIZZLE_128B_ATOM_32B,         // Swizzle 32B chunks within 128B span
    } CUtensorMapSwizzle;
 * \endcode
 * Data are organized in a specific order in global memory; however, this may not match the order in which the application accesses data
 * in shared memory. This difference in data organization may cause bank conflicts when shared memory is accessed. In order to avoid this
 * problem, data can be loaded to shared memory with shuffling across shared memory banks.
 * When the \p tensorDataType is ::CU_TENSOR_MAP_DATA_TYPE_16U6_ALIGN16B, only the following swizzle modes are supported:
 *    - CU_TENSOR_MAP_SWIZZLE_128B (Load & Store)
 *    - CU_TENSOR_MAP_SWIZZLE_128B_ATOM_32B (Load & Store)
 * When the \p tensorDataType is ::CU_TENSOR_MAP_DATA_TYPE_16U4_ALIGN16B, only the following swizzle modes are supported:
 *    - CU_TENSOR_MAP_SWIZZLE_128B (Load only)
 *    - CU_TENSOR_MAP_SWIZZLE_128B_ATOM_32B (Load only)
 *
 * - \p l2Promotion specifies L2 fetch size which indicates the byte granularity at which L2 requests are filled from DRAM. It must be of
 * type ::CUtensorMapL2promotion, which is defined as:
 * \code
    typedef enum CUtensorMapL2promotion_enum {
        CU_TENSOR_MAP_L2_PROMOTION_NONE = 0,
        CU_TENSOR_MAP_L2_PROMOTION_L2_64B,
        CU_TENSOR_MAP_L2_PROMOTION_L2_128B,
        CU_TENSOR_MAP_L2_PROMOTION_L2_256B
    } CUtensorMapL2promotion;
 * \endcode
 *
 * - \p oobFill, which indicates whether zero or a special NaN constant should be used to fill out-of-bound elements, must be of type
 * ::CUtensorMapFloatOOBfill which is defined as:
 * \code
    typedef enum CUtensorMapFloatOOBfill_enum {
        CU_TENSOR_MAP_FLOAT_OOB_FILL_NONE = 0,
        CU_TENSOR_MAP_FLOAT_OOB_FILL_NAN_REQUEST_ZERO_FMA
    } CUtensorMapFloatOOBfill;
 * \endcode
 * Note that ::CU_TENSOR_MAP_FLOAT_OOB_FILL_NAN_REQUEST_ZERO_FMA can only be used when \p tensorDataType represents a floating-point data type,
 * and when \p tensorDataType is not ::CU_TENSOR_MAP_DATA_TYPE_16U4_ALIGN8B, ::CU_TENSOR_MAP_DATA_TYPE_16U4_ALIGN16B, and ::CU_TENSOR_MAP_DATA_TYPE_16U6_ALIGN16B.
 *
 * \param tensorMap                - Tensor map object to create
 * \param tensorDataType           - Tensor data type
 * \param tensorRank               - Dimensionality of tensor; must be at least 3
 * \param globalAddress            - Starting address of memory region described by tensor
 * \param globalDim                - Array containing tensor size (number of elements) along each of the \p tensorRank dimensions
 * \param globalStrides            - Array containing stride size (in bytes) along each of the \p tensorRank - 1 dimensions
 * \param pixelBoxLowerCornerWidth - Width offset of left box corner
 * \param pixelBoxUpperCornerWidth - Width offset of right box corner
 * \param channelsPerPixel         - Number of channels per pixel
 * \param pixelsPerColumn          - Number of pixels per column
 * \param elementStrides           - Array containing traversal stride in each of the \p tensorRank dimensions
 * \param interleave               - Type of interleaved layout the tensor addresses
 * \param mode                     - W or W128 mode
 * \param swizzle                  - Bank swizzling pattern inside shared memory
 * \param l2Promotion              - L2 promotion size
 * \param oobFill                  - Indicate whether zero or special NaN constant will be used to fill out-of-bound elements
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa
 * ::cuTensorMapEncodeTiled,
 * ::cuTensorMapEncodeIm2col,
 * ::cuTensorMapReplaceAddress
 */
CUresult CUDAAPI cuTensorMapEncodeIm2colWide(CUtensorMap *tensorMap, CUtensorMapDataType tensorDataType, cuuint32_t tensorRank, void *globalAddress, const cuuint64_t *globalDim, const cuuint64_t *globalStrides, int pixelBoxLowerCornerWidth, int pixelBoxUpperCornerWidth, cuuint32_t channelsPerPixel, cuuint32_t pixelsPerColumn, const cuuint32_t *elementStrides, CUtensorMapInterleave interleave, CUtensorMapIm2ColWideMode mode, CUtensorMapSwizzle swizzle, CUtensorMapL2promotion l2Promotion, CUtensorMapFloatOOBfill oobFill);

/**
 * \brief Modify an existing tensor map descriptor with an updated global address
 *
 * Modifies the descriptor for Tensor Memory Access (TMA) object passed in \p tensorMap with
 * an updated \p globalAddress.
 *
 * Tensor map objects are only supported on devices of compute capability 9.0 or higher.
 * Additionally, a tensor map object is an opaque value, and, as such, should only be
 * accessed through CUDA API calls.
 *
 * \param tensorMap             - Tensor map object to modify
 * \param globalAddress         - Starting address of memory region described by tensor, must follow previous alignment requirements
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa
 * ::cuTensorMapEncodeTiled,
 * ::cuTensorMapEncodeIm2col
 * ::cuTensorMapEncodeIm2colWide
 */
CUresult CUDAAPI cuTensorMapReplaceAddress(CUtensorMap *tensorMap, void *globalAddress);

/** @} */
/* END CUDA_TENSOR_MEMORY */

/**
 * \defgroup CUDA_PEER_ACCESS Peer Context Memory Access
 *
 * ___MANBRIEF___ direct peer context memory access functions of the low-level
 * CUDA driver API (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the direct peer context memory access functions
 * of the low-level CUDA driver application programming interface.
 *
 * @{
 */

/**
 * \brief Queries if a device may directly access a peer device's memory.
 *
 * Returns in \p *canAccessPeer a value of 1 if contexts on \p dev are capable of
 * directly accessing memory from contexts on \p peerDev and 0 otherwise.
 * If direct access of \p peerDev from \p dev is possible, then access may be
 * enabled on two specific contexts by calling ::cuCtxEnablePeerAccess().
 *
 * \param canAccessPeer - Returned access capability
 * \param dev           - Device from which allocations on \p peerDev are to
 *                        be directly accessed.
 * \param peerDev       - Device on which the allocations to be directly accessed
 *                        by \p dev reside.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_DEVICE
 * \notefnerr
 *
 * \sa
 * ::cuCtxEnablePeerAccess,
 * ::cuCtxDisablePeerAccess,
 * ::cudaDeviceCanAccessPeer
 */
CUresult CUDAAPI cuDeviceCanAccessPeer(int *canAccessPeer, CUdevice dev, CUdevice peerDev);

/**
 * \brief Enables direct access to memory allocations in a peer context.
 *
 * If both the current context and \p peerContext are on devices which support unified
 * addressing (as may be queried using ::CU_DEVICE_ATTRIBUTE_UNIFIED_ADDRESSING) and same
 * major compute capability, then on success all allocations from \p peerContext will
 * immediately be accessible by the current context.  See \ref CUDA_UNIFIED for additional
 * details.
 *
 * Note that access granted by this call is unidirectional and that in order to access
 * memory from the current context in \p peerContext, a separate symmetric call
 * to ::cuCtxEnablePeerAccess() is required.
 *
 * Note that there are both device-wide and system-wide limitations per system
 * configuration, as noted in the CUDA Programming Guide under the section
 * "Peer-to-Peer Memory Access".
 *
 * Returns ::CUDA_ERROR_PEER_ACCESS_UNSUPPORTED if ::cuDeviceCanAccessPeer() indicates
 * that the ::CUdevice of the current context cannot directly access memory
 * from the ::CUdevice of \p peerContext.
 *
 * Returns ::CUDA_ERROR_PEER_ACCESS_ALREADY_ENABLED if direct access of
 * \p peerContext from the current context has already been enabled.
 *
 * Returns ::CUDA_ERROR_TOO_MANY_PEERS if direct peer access is not possible
 * because hardware resources required for peer access have been exhausted.
 *
 * Returns ::CUDA_ERROR_INVALID_CONTEXT if there is no current context, \p peerContext
 * is not a valid context, or if the current context is \p peerContext.
 *
 * Returns ::CUDA_ERROR_INVALID_VALUE if \p Flags is not 0.
 *
 * \param peerContext - Peer context to enable direct access to from the current context
 * \param Flags       - Reserved for future use and must be set to 0
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_PEER_ACCESS_ALREADY_ENABLED,
 * ::CUDA_ERROR_TOO_MANY_PEERS,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_PEER_ACCESS_UNSUPPORTED,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 *
 * \sa
 * ::cuDeviceCanAccessPeer,
 * ::cuCtxDisablePeerAccess,
 * ::cudaDeviceEnablePeerAccess
 */
CUresult CUDAAPI cuCtxEnablePeerAccess(CUcontext peerContext, unsigned int Flags);

/**
 * \brief Disables direct access to memory allocations in a peer context and
 * unregisters any registered allocations.
 *
  Returns ::CUDA_ERROR_PEER_ACCESS_NOT_ENABLED if direct peer access has
 * not yet been enabled from \p peerContext to the current context.
 *
 * Returns ::CUDA_ERROR_INVALID_CONTEXT if there is no current context, or if
 * \p peerContext is not a valid context.
 *
 * \param peerContext - Peer context to disable direct access to
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_PEER_ACCESS_NOT_ENABLED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * \notefnerr
 *
 * \sa
 * ::cuDeviceCanAccessPeer,
 * ::cuCtxEnablePeerAccess,
 * ::cudaDeviceDisablePeerAccess
 */
CUresult CUDAAPI cuCtxDisablePeerAccess(CUcontext peerContext);

/**
 * \brief Queries attributes of the link between two devices.
 *
 * Returns in \p *value the value of the requested attribute \p attrib of the
 * link between \p srcDevice and \p dstDevice. The supported attributes are:
 * - ::CU_DEVICE_P2P_ATTRIBUTE_PERFORMANCE_RANK: A relative value indicating the
 *   performance of the link between two devices.
 * - ::CU_DEVICE_P2P_ATTRIBUTE_ACCESS_SUPPORTED P2P: 1 if P2P Access is enable.
 * - ::CU_DEVICE_P2P_ATTRIBUTE_NATIVE_ATOMIC_SUPPORTED: 1 if Atomic operations over
 *   the link are supported.
 * - ::CU_DEVICE_P2P_ATTRIBUTE_CUDA_ARRAY_ACCESS_SUPPORTED: 1 if cudaArray can
 *   be accessed over the link.
 *
 * Returns ::CUDA_ERROR_INVALID_DEVICE if \p srcDevice or \p dstDevice are not valid
 * or if they represent the same device.
 *
 * Returns ::CUDA_ERROR_INVALID_VALUE if \p attrib is not valid or if \p value is
 * a null pointer.
 *
 * \param value         - Returned value of the requested attribute
 * \param attrib        - The requested attribute of the link between \p srcDevice and \p dstDevice.
 * \param srcDevice     - The source device of the target link.
 * \param dstDevice     - The destination device of the target link.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_DEVICE,
 * ::CUDA_ERROR_INVALID_VALUE
 * \notefnerr
 *
 * \sa
 * ::cuCtxEnablePeerAccess,
 * ::cuCtxDisablePeerAccess,
 * ::cuDeviceCanAccessPeer,
 * ::cudaDeviceGetP2PAttribute
 */
CUresult CUDAAPI cuDeviceGetP2PAttribute(int* value, CUdevice_P2PAttribute attrib, CUdevice srcDevice, CUdevice dstDevice);

/** @} */ /* END CUDA_PEER_ACCESS */

/**
 * \defgroup CUDA_GRAPHICS Graphics Interoperability
 *
 * ___MANBRIEF___ graphics interoperability functions of the low-level CUDA
 * driver API (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the graphics interoperability functions of the
 * low-level CUDA driver application programming interface.
 *
 * @{
 */

/**
 * \brief Unregisters a graphics resource for access by CUDA
 *
 * Unregisters the graphics resource \p resource so it is not accessible by
 * CUDA unless registered again.
 *
 * If \p resource is invalid then ::CUDA_ERROR_INVALID_HANDLE is
 * returned.
 *
 * \param resource - Resource to unregister
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_UNKNOWN
 * \notefnerr
 *
 * \sa
 * ::cuGraphicsD3D9RegisterResource,
 * ::cuGraphicsD3D10RegisterResource,
 * ::cuGraphicsD3D11RegisterResource,
 * ::cuGraphicsGLRegisterBuffer,
 * ::cuGraphicsGLRegisterImage,
 * ::cudaGraphicsUnregisterResource
 */
CUresult CUDAAPI cuGraphicsUnregisterResource(CUgraphicsResource resource);

/**
 * \brief Get an array through which to access a subresource of a mapped graphics resource.
 *
 * Returns in \p *pArray an array through which the subresource of the mapped
 * graphics resource \p resource which corresponds to array index \p arrayIndex
 * and mipmap level \p mipLevel may be accessed.  The value set in \p *pArray may
 * change every time that \p resource is mapped.
 *
 * If \p resource is not a texture then it cannot be accessed via an array and
 * ::CUDA_ERROR_NOT_MAPPED_AS_ARRAY is returned.
 * If \p arrayIndex is not a valid array index for \p resource then
 * ::CUDA_ERROR_INVALID_VALUE is returned.
 * If \p mipLevel is not a valid mipmap level for \p resource then
 * ::CUDA_ERROR_INVALID_VALUE is returned.
 * If \p resource is not mapped then ::CUDA_ERROR_NOT_MAPPED is returned.
 *
 * \param pArray      - Returned array through which a subresource of \p resource may be accessed
 * \param resource    - Mapped resource to access
 * \param arrayIndex  - Array index for array textures or cubemap face
 *                      index as defined by ::CUarray_cubemap_face for
 *                      cubemap textures for the subresource to access
 * \param mipLevel    - Mipmap level for the subresource to access
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_NOT_MAPPED,
 * ::CUDA_ERROR_NOT_MAPPED_AS_ARRAY
 * \notefnerr
 *
 * \sa
 * ::cuGraphicsResourceGetMappedPointer,
 * ::cudaGraphicsSubResourceGetMappedArray
 */
CUresult CUDAAPI cuGraphicsSubResourceGetMappedArray(CUarray *pArray, CUgraphicsResource resource, unsigned int arrayIndex, unsigned int mipLevel);

/**
 * \brief Get a mipmapped array through which to access a mapped graphics resource.
 *
 * Returns in \p *pMipmappedArray a mipmapped array through which the mapped graphics
 * resource \p resource. The value set in \p *pMipmappedArray may change every time
 * that \p resource is mapped.
 *
 * If \p resource is not a texture then it cannot be accessed via a mipmapped array and
 * ::CUDA_ERROR_NOT_MAPPED_AS_ARRAY is returned.
 * If \p resource is not mapped then ::CUDA_ERROR_NOT_MAPPED is returned.
 *
 * \param pMipmappedArray - Returned mipmapped array through which \p resource may be accessed
 * \param resource        - Mapped resource to access
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_NOT_MAPPED,
 * ::CUDA_ERROR_NOT_MAPPED_AS_ARRAY
 * \notefnerr
 *
 * \sa
 * ::cuGraphicsResourceGetMappedPointer,
 * ::cudaGraphicsResourceGetMappedMipmappedArray
 */
CUresult CUDAAPI cuGraphicsResourceGetMappedMipmappedArray(CUmipmappedArray *pMipmappedArray, CUgraphicsResource resource);

/**
 * \brief Get a device pointer through which to access a mapped graphics resource.
 *
 * Returns in \p *pDevPtr a pointer through which the mapped graphics resource
 * \p resource may be accessed.
 * Returns in \p pSize the size of the memory in bytes which may be accessed from that pointer.
 * The value set in \p pPointer may change every time that \p resource is mapped.
 *
 * If \p resource is not a buffer then it cannot be accessed via a pointer and
 * ::CUDA_ERROR_NOT_MAPPED_AS_POINTER is returned.
 * If \p resource is not mapped then ::CUDA_ERROR_NOT_MAPPED is returned.
 * *
 * \param pDevPtr    - Returned pointer through which \p resource may be accessed
 * \param pSize      - Returned size of the buffer accessible starting at \p *pPointer
 * \param resource   - Mapped resource to access
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_NOT_MAPPED,
 * ::CUDA_ERROR_NOT_MAPPED_AS_POINTER
 * \notefnerr
 *
 * \sa
 * ::cuGraphicsMapResources,
 * ::cuGraphicsSubResourceGetMappedArray,
 * ::cudaGraphicsResourceGetMappedPointer
 */
CUresult CUDAAPI cuGraphicsResourceGetMappedPointer(CUdeviceptr *pDevPtr, size_t *pSize, CUgraphicsResource resource);

/**
 * \brief Set usage flags for mapping a graphics resource
 *
 * Set \p flags for mapping the graphics resource \p resource.
 *
 * Changes to \p flags will take effect the next time \p resource is mapped.
 * The \p flags argument may be any of the following:

 * - ::CU_GRAPHICS_MAP_RESOURCE_FLAGS_NONE: Specifies no hints about how this
 *   resource will be used. It is therefore assumed that this resource will be
 *   read from and written to by CUDA kernels.  This is the default value.
 * - ::CU_GRAPHICS_MAP_RESOURCE_FLAGS_READONLY: Specifies that CUDA kernels which
 *   access this resource will not write to this resource.
 * - ::CU_GRAPHICS_MAP_RESOURCE_FLAGS_WRITEDISCARD: Specifies that CUDA kernels
 *   which access this resource will not read from this resource and will
 *   write over the entire contents of the resource, so none of the data
 *   previously stored in the resource will be preserved.
 *
 * If \p resource is presently mapped for access by CUDA then
 * ::CUDA_ERROR_ALREADY_MAPPED is returned.
 * If \p flags is not one of the above values then ::CUDA_ERROR_INVALID_VALUE is returned.
 *
 * \param resource - Registered resource to set flags for
 * \param flags    - Parameters for resource mapping
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_ALREADY_MAPPED
 * \notefnerr
 *
 * \sa
 * ::cuGraphicsMapResources,
 * ::cudaGraphicsResourceSetMapFlags
 */
CUresult CUDAAPI cuGraphicsResourceSetMapFlags(CUgraphicsResource resource, unsigned int flags);

/**
 * \brief Map graphics resources for access by CUDA
 *
 * Maps the \p count graphics resources in \p resources for access by CUDA.
 *
 * The resources in \p resources may be accessed by CUDA until they
 * are unmapped. The graphics API from which \p resources were registered
 * should not access any resources while they are mapped by CUDA. If an
 * application does so, the results are undefined.
 *
 * This function provides the synchronization guarantee that any graphics calls
 * issued before ::cuGraphicsMapResources() will complete before any subsequent CUDA
 * work issued in \p stream begins.
 *
 * If \p resources includes any duplicate entries then ::CUDA_ERROR_INVALID_HANDLE is returned.
 * If any of \p resources are presently mapped for access by CUDA then ::CUDA_ERROR_ALREADY_MAPPED is returned.
 *
 * \param count      - Number of resources to map
 * \param resources  - Resources to map for CUDA usage
 * \param hStream    - Stream with which to synchronize
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_ALREADY_MAPPED,
 * ::CUDA_ERROR_UNKNOWN
 * \note_null_stream
 * \notefnerr
 *
 * \sa
 * ::cuGraphicsResourceGetMappedPointer,
 * ::cuGraphicsSubResourceGetMappedArray,
 * ::cuGraphicsUnmapResources,
 * ::cudaGraphicsMapResources
 */
CUresult CUDAAPI cuGraphicsMapResources(unsigned int count, CUgraphicsResource *resources, CUstream hStream);

/**
 * \brief Unmap graphics resources.
 *
 * Unmaps the \p count graphics resources in \p resources.
 *
 * Once unmapped, the resources in \p resources may not be accessed by CUDA
 * until they are mapped again.
 *
 * This function provides the synchronization guarantee that any CUDA work issued
 * in \p stream before ::cuGraphicsUnmapResources() will complete before any
 * subsequently issued graphics work begins.
 *
 *
 * If \p resources includes any duplicate entries then ::CUDA_ERROR_INVALID_HANDLE is returned.
 * If any of \p resources are not presently mapped for access by CUDA then ::CUDA_ERROR_NOT_MAPPED is returned.
 *
 * \param count      - Number of resources to unmap
 * \param resources  - Resources to unmap
 * \param hStream    - Stream with which to synchronize
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_NOT_MAPPED,
 * ::CUDA_ERROR_UNKNOWN
 * \note_null_stream
 * \notefnerr
 *
 * \sa
 * ::cuGraphicsMapResources,
 * ::cudaGraphicsUnmapResources
 */
CUresult CUDAAPI cuGraphicsUnmapResources(unsigned int count, CUgraphicsResource *resources, CUstream hStream);

/** @} */ /* END CUDA_GRAPHICS */

/**
 * \defgroup CUDA_DRIVER_ENTRY_POINT Driver Entry Point Access 
 *
 * ___MANBRIEF___ driver entry point access functions of the low-level CUDA driver API
 * (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the driver entry point access functions of the low-level CUDA
 * driver application programming interface.
 *
 * @{
 */

/**
 * \brief Returns the requested driver API function pointer
 *
 * Returns in \p **pfn the address of the CUDA driver function for the requested
 * CUDA version and flags.
 *
 * The CUDA version is specified as (1000 * major + 10 * minor), so CUDA 11.2
 * should be specified as 11020. For a requested driver symbol, if the specified
 * CUDA version is greater than or equal to the CUDA version in which the driver symbol
 * was introduced, this API will return the function pointer to the corresponding
 * versioned function.
 *
 * The pointer returned by the API should be cast to a function pointer matching the
 * requested driver function's definition in the API header file. The function pointer
 * typedef can be picked up from the corresponding typedefs header file. For example,
 * cudaTypedefs.h consists of function pointer typedefs for driver APIs defined in cuda.h.
 *
 * The API will return ::CUDA_SUCCESS and set the returned \p pfn to NULL if the 
 * requested driver function is not supported on the platform, no ABI 
 * compatible driver function exists for the specified \p cudaVersion or if the 
 * driver symbol is invalid.
 *
 * It will also set the optional \p symbolStatus to one of the values in
 * ::CUdriverProcAddressQueryResult with the following meanings:
 * - ::CU_GET_PROC_ADDRESS_SUCCESS - The requested symbol was succesfully found based
 *   on input arguments and \p pfn is valid
 * - ::CU_GET_PROC_ADDRESS_SYMBOL_NOT_FOUND - The requested symbol was not found
 * - ::CU_GET_PROC_ADDRESS_VERSION_NOT_SUFFICIENT - The requested symbol was found but is
 *   not supported by cudaVersion specified
 *
 * The requested flags can be:
 * - ::CU_GET_PROC_ADDRESS_DEFAULT: This is the default mode. This is equivalent to
 *   ::CU_GET_PROC_ADDRESS_PER_THREAD_DEFAULT_STREAM if the code is compiled with
 *   --default-stream per-thread compilation flag or the macro CUDA_API_PER_THREAD_DEFAULT_STREAM
 *   is defined; ::CU_GET_PROC_ADDRESS_LEGACY_STREAM otherwise.
 * - ::CU_GET_PROC_ADDRESS_LEGACY_STREAM: This will enable the search for all driver symbols
 *   that match the requested driver symbol name except the corresponding per-thread versions.
 * - ::CU_GET_PROC_ADDRESS_PER_THREAD_DEFAULT_STREAM: This will enable the search for all
 *   driver symbols that match the requested driver symbol name including the per-thread
 *   versions. If a per-thread version is not found, the API will return the legacy version
 *   of the driver function.
 *
 * \param symbol - The base name of the driver API function to look for. As an example,
 *                 for the driver API ::cuMemAlloc_v2, \p symbol would be cuMemAlloc and
 *                 \p cudaVersion would be the ABI compatible CUDA version for the _v2 variant. 
 * \param pfn - Location to return the function pointer to the requested driver function
 * \param cudaVersion - The CUDA version to look for the requested driver symbol 
 * \param flags -  Flags to specify search options.
 * \param symbolStatus - Optional location to store the status of the search for
 *                       \p symbol based on \p cudaVersion. See ::CUdriverProcAddressQueryResult
 *                       for possible values.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_NOT_SUPPORTED
 * \note_version_mixing
 *
 * \sa
 * ::cudaGetDriverEntryPoint
 */
CUresult CUDAAPI cuGetProcAddress(const char *symbol, void **pfn, int cudaVersion, cuuint64_t flags, CUdriverProcAddressQueryResult *symbolStatus);

/** @} */ /* END CUDA_DRIVER_ENTRY_POINT */

/**
 * \defgroup CUDA_COREDUMP Coredump Attributes Control API
 *
 * ___MANBRIEF___ coredump attribute control functions for the low-level CUDA API
 * (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the coredump attribute control functions of the low-level CUDA
 * driver application programming interface.
 *
 * @{
 */

/**
 * Flags for choosing a coredump attribute to get/set
 */
typedef enum CUcoredumpSettings_enum {
    CU_COREDUMP_ENABLE_ON_EXCEPTION = 1,
    CU_COREDUMP_TRIGGER_HOST,
    CU_COREDUMP_LIGHTWEIGHT,
    CU_COREDUMP_ENABLE_USER_TRIGGER,
    CU_COREDUMP_FILE,
    CU_COREDUMP_PIPE,
    CU_COREDUMP_GENERATION_FLAGS,
    CU_COREDUMP_MAX
} CUcoredumpSettings;

/**
 * Flags for controlling coredump contents
 */
typedef enum CUCoredumpGenerationFlags {
    CU_COREDUMP_DEFAULT_FLAGS                = 0,
    CU_COREDUMP_SKIP_NONRELOCATED_ELF_IMAGES = (1 << 0),
    CU_COREDUMP_SKIP_GLOBAL_MEMORY           = (1 << 1),
    CU_COREDUMP_SKIP_SHARED_MEMORY           = (1 << 2),
    CU_COREDUMP_SKIP_LOCAL_MEMORY            = (1 << 3),
    CU_COREDUMP_SKIP_ABORT                   = (1 << 4),
    CU_COREDUMP_SKIP_CONSTBANK_MEMORY        = (1 << 5),

    CU_COREDUMP_LIGHTWEIGHT_FLAGS = CU_COREDUMP_SKIP_NONRELOCATED_ELF_IMAGES
                                     | CU_COREDUMP_SKIP_GLOBAL_MEMORY
                                     | CU_COREDUMP_SKIP_SHARED_MEMORY
                                     | CU_COREDUMP_SKIP_LOCAL_MEMORY
                                     | CU_COREDUMP_SKIP_CONSTBANK_MEMORY
} CUCoredumpGenerationFlags;

/**
 * \brief Allows caller to fetch a coredump attribute value for the current context
 *
 * Returns in \p *value the requested value specified by \p attrib. It is up to the caller
 * to ensure that the data type and size of \p *value matches the request.
 *
 * If the caller calls this function with \p *value equal to NULL, the size of the memory
 * region (in bytes) expected for \p attrib will be placed in \p size.
 *
 * The supported attributes are:
 * - ::CU_COREDUMP_ENABLE_ON_EXCEPTION: Bool where ::true means that GPU exceptions from
 *      this context will create a coredump at the location specified by ::CU_COREDUMP_FILE.
 *      The default value is ::false unless set to ::true globally or locally, or the
 *      CU_CTX_USER_COREDUMP_ENABLE flag was set during context creation.
 * - ::CU_COREDUMP_TRIGGER_HOST: Bool where ::true means that the host CPU will
 *      also create a coredump. The default value is ::true unless set to ::false globally or
 *      or locally. This value is deprecated as of CUDA 12.5 - raise the ::CU_COREDUMP_SKIP_ABORT
 *      flag to disable host device abort() if needed.
 * - ::CU_COREDUMP_LIGHTWEIGHT: Bool where ::true means that any resulting coredumps
 *      will not have a dump of GPU memory or non-reloc ELF images. The default value is
 *      ::false unless set to ::true globally or locally. This attribute is deprecated as
 *      of CUDA 12.5, please use ::CU_COREDUMP_GENERATION_FLAGS instead.
 * - ::CU_COREDUMP_ENABLE_USER_TRIGGER: Bool where ::true means that a coredump can be
 *      created by writing to the system pipe specified by ::CU_COREDUMP_PIPE. The default
 *      value is ::false unless set to ::true globally or locally.
 * - ::CU_COREDUMP_FILE: String of up to 1023 characters that defines the location where
 *      any coredumps generated by this context will be written. The default value is
 *      ::core.cuda.HOSTNAME.PID where ::HOSTNAME is the host name of the machine running
 *      the CUDA applications and ::PID is the process ID of the CUDA application.
 * - ::CU_COREDUMP_PIPE: String of up to 1023 characters that defines the name of the pipe
 *      that will be monitored if user-triggered coredumps are enabled. The default value is
 *      ::corepipe.cuda.HOSTNAME.PID where ::HOSTNAME is the host name of the machine running
 *      the CUDA application and ::PID is the process ID of the CUDA application.
 * - ::CU_COREDUMP_GENERATION_FLAGS: An integer with values to allow granular control the data
 *      contained in a coredump specified as a bitwise OR combination of the following values:
 *      + ::CU_COREDUMP_DEFAULT_FLAGS - if set by itself, coredump generation returns to its
 *          default settings of including all memory regions that it is able to access
 *      + ::CU_COREDUMP_SKIP_NONRELOCATED_ELF_IMAGES - Coredump will not include the data from
 *          CUDA source modules that are not relocated at runtime.
 *      + ::CU_COREDUMP_SKIP_GLOBAL_MEMORY - Coredump will not include device-side global data
 *          that does not belong to any context.
 *      + ::CU_COREDUMP_SKIP_SHARED_MEMORY - Coredump will not include grid-scale shared memory
 *          for the warp that the dumped kernel belonged to.
 *      + ::CU_COREDUMP_SKIP_LOCAL_MEMORY - Coredump will not include local memory from the kernel.
 *      + ::CU_COREDUMP_LIGHTWEIGHT_FLAGS - Enables all of the above options. Equiavlent to setting
 *          the ::CU_COREDUMP_LIGHTWEIGHT attribute to ::true.
 *      + ::CU_COREDUMP_SKIP_ABORT - If set, GPU exceptions will not raise an abort() in the host CPU
 *          process. Same functional goal as ::CU_COREDUMP_TRIGGER_HOST but better reflects the default
 *          behavior.
 *
 * \param attrib - The enum defining which value to fetch.
 * \param value - void* containing the requested data.
 * \param size - The size of the memory region \p value points to.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_NOT_PERMITTED,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_CONTEXT_IS_DESTROYED
 *
 * \sa
 * ::cuCoredumpGetAttributeGlobal,
 * ::cuCoredumpSetAttribute,
 * ::cuCoredumpSetAttributeGlobal
 */
CUresult CUDAAPI cuCoredumpGetAttribute(CUcoredumpSettings attrib, void* value, size_t *size);

/**
 * \brief Allows caller to fetch a coredump attribute value for the entire application
 *
 * Returns in \p *value the requested value specified by \p attrib. It is up to the caller
 * to ensure that the data type and size of \p *value matches the request.
 *
 * If the caller calls this function with \p *value equal to NULL, the size of the memory
 * region (in bytes) expected for \p attrib will be placed in \p size.
 *
 * The supported attributes are:
 * - ::CU_COREDUMP_ENABLE_ON_EXCEPTION: Bool where ::true means that GPU exceptions from
 *      this context will create a coredump at the location specified by ::CU_COREDUMP_FILE.
 *      The default value is ::false.
 * - ::CU_COREDUMP_TRIGGER_HOST: Bool where ::true means that the host CPU will
 *      also create a coredump. The default value is ::true unless set to ::false globally or
 *      or locally. This value is deprecated as of CUDA 12.5 - raise the ::CU_COREDUMP_SKIP_ABORT
 *      flag to disable host device abort() if needed.
 * - ::CU_COREDUMP_LIGHTWEIGHT: Bool where ::true means that any resulting coredumps
 *      will not have a dump of GPU memory or non-reloc ELF images. The default value is
 *      ::false. This attribute is deprecated as of CUDA 12.5, please use ::CU_COREDUMP_GENERATION_FLAGS
 *      instead.
 * - ::CU_COREDUMP_ENABLE_USER_TRIGGER: Bool where ::true means that a coredump can be
 *      created by writing to the system pipe specified by ::CU_COREDUMP_PIPE. The default
 *      value is ::false.
 * - ::CU_COREDUMP_FILE: String of up to 1023 characters that defines the location where
 *      any coredumps generated by this context will be written. The default value is
 *      ::core.cuda.HOSTNAME.PID where ::HOSTNAME is the host name of the machine running
 *      the CUDA applications and ::PID is the process ID of the CUDA application.
 * - ::CU_COREDUMP_PIPE: String of up to 1023 characters that defines the name of the pipe
 *      that will be monitored if user-triggered coredumps are enabled. The default value is
 *      ::corepipe.cuda.HOSTNAME.PID where ::HOSTNAME is the host name of the machine running
 *      the CUDA application and ::PID is the process ID of the CUDA application.
 * - ::CU_COREDUMP_GENERATION_FLAGS: An integer with values to allow granular control the data
 *      contained in a coredump specified as a bitwise OR combination of the following values:
 *      + ::CU_COREDUMP_DEFAULT_FLAGS - if set by itself, coredump generation returns to its
 *          default settings of including all memory regions that it is able to access
 *      + ::CU_COREDUMP_SKIP_NONRELOCATED_ELF_IMAGES - Coredump will not include the data from
 *          CUDA source modules that are not relocated at runtime.
 *      + ::CU_COREDUMP_SKIP_GLOBAL_MEMORY - Coredump will not include device-side global data
 *          that does not belong to any context.
 *      + ::CU_COREDUMP_SKIP_SHARED_MEMORY - Coredump will not include grid-scale shared memory
 *          for the warp that the dumped kernel belonged to.
 *      + ::CU_COREDUMP_SKIP_LOCAL_MEMORY - Coredump will not include local memory from the kernel.
 *      + ::CU_COREDUMP_LIGHTWEIGHT_FLAGS - Enables all of the above options. Equiavlent to setting
 *          the ::CU_COREDUMP_LIGHTWEIGHT attribute to ::true.
 *      + ::CU_COREDUMP_SKIP_ABORT - If set, GPU exceptions will not raise an abort() in the host CPU
 *          process. Same functional goal as ::CU_COREDUMP_TRIGGER_HOST but better reflects the default
 *          behavior.
 *
 * \param attrib - The enum defining which value to fetch.
 * \param value - void* containing the requested data.
 * \param size - The size of the memory region \p value points to.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa
 * ::cuCoredumpGetAttribute,
 * ::cuCoredumpSetAttribute,
 * ::cuCoredumpSetAttributeGlobal
 */
CUresult CUDAAPI cuCoredumpGetAttributeGlobal(CUcoredumpSettings attrib, void *value, size_t *size);

/**
 * \brief Allows caller to set a coredump attribute value for the current context
 *
 * This function should be considered an alternate interface to the CUDA-GDB environment
 * variables defined in this document: https://docs.nvidia.com/cuda/cuda-gdb/index.html#gpu-coredump
 *
 * An important design decision to note is that any coredump environment variable values
 * set before CUDA initializes will take permanent precedence over any values set with this
 * function. This decision was made to ensure no change in behavior for any users that
 * may be currently using these variables to get coredumps.
 *
 * \p *value shall contain the requested value specified by \p set. It is up to the caller
 * to ensure that the data type and size of \p *value matches the request.
 *
 * If the caller calls this function with \p *value equal to NULL, the size of the memory
 * region (in bytes) expected for \p set will be placed in \p size.
 *
 * /note This function will return ::CUDA_ERROR_NOT_SUPPORTED if the caller attempts to set
 * ::CU_COREDUMP_ENABLE_ON_EXCEPTION on a GPU of with Compute Capability < 6.0. ::cuCoredumpSetAttributeGlobal
 * works on those platforms as an alternative.
 *
 * /note ::CU_COREDUMP_ENABLE_USER_TRIGGER and ::CU_COREDUMP_PIPE cannot be set on a per-context basis.
 *
 * The supported attributes are:
 * - ::CU_COREDUMP_ENABLE_ON_EXCEPTION: Bool where ::true means that GPU exceptions from
 *      this context will create a coredump at the location specified by ::CU_COREDUMP_FILE.
 *      The default value is ::false.
 * - ::CU_COREDUMP_TRIGGER_HOST: Bool where ::true means that the host CPU will
 *      also create a coredump. The default value is ::true unless set to ::false globally or
 *      or locally. This value is deprecated as of CUDA 12.5 - raise the ::CU_COREDUMP_SKIP_ABORT
 *      flag to disable host device abort() if needed.
 * - ::CU_COREDUMP_LIGHTWEIGHT: Bool where ::true means that any resulting coredumps
 *      will not have a dump of GPU memory or non-reloc ELF images. The default value is
 *      ::false. This attribute is deprecated as of CUDA 12.5, please use ::CU_COREDUMP_GENERATION_FLAGS
 *      instead.
 * - ::CU_COREDUMP_FILE: String of up to 1023 characters that defines the location where
 *      any coredumps generated by this context will be written. The default value is
 *      ::core.cuda.HOSTNAME.PID where ::HOSTNAME is the host name of the machine running
 *      the CUDA applications and ::PID is the process ID of the CUDA application.
 * - ::CU_COREDUMP_GENERATION_FLAGS: An integer with values to allow granular control the data
 *      contained in a coredump specified as a bitwise OR combination of the following values:
 *      + ::CU_COREDUMP_DEFAULT_FLAGS - if set by itself, coredump generation returns to its
 *          default settings of including all memory regions that it is able to access
 *      + ::CU_COREDUMP_SKIP_NONRELOCATED_ELF_IMAGES - Coredump will not include the data from
 *          CUDA source modules that are not relocated at runtime.
 *      + ::CU_COREDUMP_SKIP_GLOBAL_MEMORY - Coredump will not include device-side global data
 *          that does not belong to any context.
 *      + ::CU_COREDUMP_SKIP_SHARED_MEMORY - Coredump will not include grid-scale shared memory
 *          for the warp that the dumped kernel belonged to.
 *      + ::CU_COREDUMP_SKIP_LOCAL_MEMORY - Coredump will not include local memory from the kernel.
 *      + ::CU_COREDUMP_LIGHTWEIGHT_FLAGS - Enables all of the above options. Equiavlent to setting
 *          the ::CU_COREDUMP_LIGHTWEIGHT attribute to ::true.
 *      + ::CU_COREDUMP_SKIP_ABORT - If set, GPU exceptions will not raise an abort() in the host CPU
 *          process. Same functional goal as ::CU_COREDUMP_TRIGGER_HOST but better reflects the default
 *          behavior.
 *
 * \param attrib - The enum defining which value to set.
 * \param value - void* containing the requested data.
 * \param size - The size of the memory region \p value points to.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_NOT_PERMITTED,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_CONTEXT_IS_DESTROYED,
 * ::CUDA_ERROR_NOT_SUPPORTED
 *
 * \sa
 * ::cuCoredumpGetAttributeGlobal,
 * ::cuCoredumpGetAttribute,
 * ::cuCoredumpSetAttributeGlobal
 */
CUresult CUDAAPI cuCoredumpSetAttribute(CUcoredumpSettings attrib, void* value, size_t *size);

/**
 * \brief Allows caller to set a coredump attribute value globally
 *
 * This function should be considered an alternate interface to the CUDA-GDB environment
 * variables defined in this document: https://docs.nvidia.com/cuda/cuda-gdb/index.html#gpu-coredump
 *
 * An important design decision to note is that any coredump environment variable values
 * set before CUDA initializes will take permanent precedence over any values set with this
 * function. This decision was made to ensure no change in behavior for any users that
 * may be currently using these variables to get coredumps.
 *
 * \p *value shall contain the requested value specified by \p set. It is up to the caller
 * to ensure that the data type and size of \p *value matches the request.
 *
 * If the caller calls this function with \p *value equal to NULL, the size of the memory
 * region (in bytes) expected for \p set will be placed in \p size.
 *
 * The supported attributes are:
 * - ::CU_COREDUMP_ENABLE_ON_EXCEPTION: Bool where ::true means that GPU exceptions from
 *      this context will create a coredump at the location specified by ::CU_COREDUMP_FILE.
 *      The default value is ::false.
 * - ::CU_COREDUMP_TRIGGER_HOST: Bool where ::true means that the host CPU will
 *      also create a coredump. The default value is ::true unless set to ::false globally or
 *      or locally. This value is deprecated as of CUDA 12.5 - raise the ::CU_COREDUMP_SKIP_ABORT
 *      flag to disable host device abort() if needed.
 * - ::CU_COREDUMP_LIGHTWEIGHT: Bool where ::true means that any resulting coredumps
 *      will not have a dump of GPU memory or non-reloc ELF images. The default value is
 *      ::false. This attribute is deprecated as of CUDA 12.5, please use ::CU_COREDUMP_GENERATION_FLAGS
 *      instead.
 * - ::CU_COREDUMP_ENABLE_USER_TRIGGER: Bool where ::true means that a coredump can be
 *      created by writing to the system pipe specified by ::CU_COREDUMP_PIPE. The default
 *      value is ::false.
 * - ::CU_COREDUMP_FILE: String of up to 1023 characters that defines the location where
 *      any coredumps generated by this context will be written. The default value is
 *      ::core.cuda.HOSTNAME.PID where ::HOSTNAME is the host name of the machine running
 *      the CUDA applications and ::PID is the process ID of the CUDA application.
 * - ::CU_COREDUMP_PIPE: String of up to 1023 characters that defines the name of the pipe
 *      that will be monitored if user-triggered coredumps are enabled. This value may not be
 *      changed after ::CU_COREDUMP_ENABLE_USER_TRIGGER is set to ::true. The default
 *      value is ::corepipe.cuda.HOSTNAME.PID where ::HOSTNAME is the host name of the machine
 *      running the CUDA application and ::PID is the process ID of the CUDA application.
 * - ::CU_COREDUMP_GENERATION_FLAGS: An integer with values to allow granular control the data
 *      contained in a coredump specified as a bitwise OR combination of the following values:
 *      + ::CU_COREDUMP_DEFAULT_FLAGS - if set by itself, coredump generation returns to its
 *          default settings of including all memory regions that it is able to access
 *      + ::CU_COREDUMP_SKIP_NONRELOCATED_ELF_IMAGES - Coredump will not include the data from
 *          CUDA source modules that are not relocated at runtime.
 *      + ::CU_COREDUMP_SKIP_GLOBAL_MEMORY - Coredump will not include device-side global data
 *          that does not belong to any context.
 *      + ::CU_COREDUMP_SKIP_SHARED_MEMORY - Coredump will not include grid-scale shared memory
 *          for the warp that the dumped kernel belonged to.
 *      + ::CU_COREDUMP_SKIP_LOCAL_MEMORY - Coredump will not include local memory from the kernel.
 *      + ::CU_COREDUMP_LIGHTWEIGHT_FLAGS - Enables all of the above options. Equiavlent to setting
 *          the ::CU_COREDUMP_LIGHTWEIGHT attribute to ::true.
 *      + ::CU_COREDUMP_SKIP_ABORT - If set, GPU exceptions will not raise an abort() in the host CPU
 *          process. Same functional goal as ::CU_COREDUMP_TRIGGER_HOST but better reflects the default
 *          behavior.
 *
 * \param attrib - The enum defining which value to set.
 * \param value - void* containing the requested data.
 * \param size - The size of the memory region \p value points to.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_NOT_PERMITTED
 *
 * \sa
 * ::cuCoredumpGetAttribute,
 * ::cuCoredumpGetAttributeGlobal,
 * ::cuCoredumpSetAttribute
 */
CUresult CUDAAPI cuCoredumpSetAttributeGlobal(CUcoredumpSettings attrib, void *value, size_t *size);

/** @} */ /* END CUDA_COREDUMP */

CUresult CUDAAPI cuGetExportTable(const void **ppExportTable, const CUuuid *pExportTableId);

/*
** ******************* GREEN CONTEXTS **********************
*/

/**
 * \defgroup CUDA_GREEN_CONTEXTS Green Contexts
 *
 * ___MANBRIEF___ Driver level API for creation and manipulation of green contexts
 * (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This section describes the APIs for creation and manipulation of green contexts in the CUDA
 * driver. Green contexts are a lightweight alternative to traditional contexts, with the ability
 * to pass in a set of resources that they should be initialized with. This allows the developer to
 * represent distinct spatial partitions of the GPU, provision resources for them, and target them
 * via the same programming model that CUDA exposes (streams, kernel launches, etc.).
 *
 * There are 4 main steps to using these new set of APIs.
 * - (1) Start with an initial set of resources, for example via ::cuDeviceGetDevResource. Only SM type is supported today.
 * - (2) Partition this set of resources by providing them as input to a partition API, for example: ::cuDevSmResourceSplitByCount.
 * - (3) Finalize the specification of resources by creating a descriptor via ::cuDevResourceGenerateDesc.
 * - (4) Provision the resources and create a green context via ::cuGreenCtxCreate.
 *
 * For \p CU_DEV_RESOURCE_TYPE_SM, the partitions created have minimum SM count requirements, often rounding up and aligning the
 * minCount provided to ::cuDevSmResourceSplitByCount. The following is a guideline for each architecture
 * and may be subject to change:
 * - On Compute Architecture 6.X: The minimum count is 1 SM.
 * - On Compute Architecture 7.X: The minimum count is 2 SMs and must be a multiple of 2.
 * - On Compute Architecture 8.X: The minimum count is 4 SMs and must be a multiple of 2.
 * - On Compute Architecture 9.0+: The minimum count is 8 SMs and must be a multiple of 8.
 *
 * In the future, flags can be provided to tradeoff functional and performance characteristics versus finer grained SM partitions.
 *
 * Even if the green contexts have disjoint SM partitions, it is not guaranteed that the kernels launched
 * in them will run concurrently or have forward progress guarantees. This is due to other resources (like HW connections,
 * see ::CUDA_DEVICE_MAX_CONNECTIONS) that could cause a dependency. Additionally, in certain scenarios,
 * it is possible for the workload to run on more SMs than was provisioned (but never less).
 * The following are two scenarios which can exhibit this behavior:
 * - On Volta+ MPS: When \p CUDA_MPS_ACTIVE_THREAD_PERCENTAGE is used,
 * the set of SMs that are used for running kernels can be scaled up to the value of SMs used for the MPS client.
 * - On Compute Architecture 9.x: When a module with dynamic parallelism (CDP) is loaded, all future
 * kernels running under green contexts may use and share an additional set of 2 SMs.
 *
 * @{
 */

/*!
 * \typedef struct CUdevResourceDesc_st* CUdevResourceDesc;
 * An opaque descriptor handle. The descriptor encapsulates multiple created and configured resources.
 * Created via ::cuDevResourceGenerateDesc
 */
typedef struct CUdevResourceDesc_st *CUdevResourceDesc;

typedef enum {
    CU_GREEN_CTX_DEFAULT_STREAM = 0x1, /**< Required. Creates a default stream to use inside the green context */
} CUgreenCtxCreate_flags;

typedef enum {
    CU_DEV_SM_RESOURCE_SPLIT_IGNORE_SM_COSCHEDULING = 0x1,
    CU_DEV_SM_RESOURCE_SPLIT_MAX_POTENTIAL_CLUSTER_SIZE = 0x2,
} CUdevSmResourceSplit_flags;

#define RESOURCE_ABI_VERSION 1
#define RESOURCE_ABI_EXTERNAL_BYTES 48

#define _CONCAT_INNER(x, y) x ## y
#define _CONCAT_OUTER(x, y) _CONCAT_INNER(x, y)

/*!
 * \typedef enum CUdevResourceType
 * Type of resource
 */
typedef enum {
    CU_DEV_RESOURCE_TYPE_INVALID = 0,
    CU_DEV_RESOURCE_TYPE_SM = 1, /**< Streaming multiprocessors related information */
#if defined(__CUDA_API_VERSION_INTERNAL) && !defined(__CUDA_API_VERSION_INTERNAL_ODR)
    CU_DEV_RESOURCE_TYPE_MAX,
#endif
} CUdevResourceType;

/*!
 * \struct CUdevSmResource
 * Data for SM-related resources
 */
typedef struct CUdevSmResource_st {
    unsigned int smCount; /**< The amount of streaming multiprocessors available in this resource. This is an output parameter only, do not write to this field. */
} CUdevSmResource;

/*!
 * \struct CUdevResource
 * A tagged union describing different resources identified by the type field. This structure should not be directly modified outside of the API that created it.
 * \code
 * struct {
 *     CUdevResourceType type;
 *     union {
 *         CUdevSmResource sm;
 *     };
 * };
 * \endcode
 * - If \p type is \p CU_DEV_RESOURCE_TYPE_INVALID, this resoure is not valid and cannot be further accessed.
 * - If \p type is \p CU_DEV_RESOURCE_TYPE_SM, the ::CUdevSmResource structure \p sm is filled in. For example,
 * \p sm.smCount will reflect the amount of streaming multiprocessors available in this resource.
 */
typedef struct CUdevResource_st {
    CUdevResourceType type; /**< Type of resource, dictates which union field was last set */
    unsigned char _internal_padding[92];
    union {
        CUdevSmResource sm; /**< Resource corresponding to CU_DEV_RESOURCE_TYPE_SM \p. type. */
        unsigned char _oversize[RESOURCE_ABI_EXTERNAL_BYTES];
    };
} _CONCAT_OUTER(CUdevResource_v, RESOURCE_ABI_VERSION);
typedef _CONCAT_OUTER(CUdevResource_v, RESOURCE_ABI_VERSION) CUdevResource;

#undef _CONCAT_INNER
#undef _CONCAT_OUTER

#undef ABI_PER_RESOURCE_EXTERNAL_BYTES
#undef ABI_RESOURCE_VERSION

/**
 * \brief Creates a green context with a specified set of resources.
 *
 * This API creates a green context with the resources specified in the descriptor \p desc and
 * returns it in the handle represented by \p phCtx. This API will retain the primary context on device \p dev,
 * which will is released when the green context is destroyed. It is advised to have the primary context active
 * before calling this API to avoid the heavy cost of triggering primary context initialization and
 * deinitialization multiple times.
 *
 * The API does not set the green context current. In order to set it current, you need to explicitly set it current
 * by first converting the green context to a CUcontext using ::cuCtxFromGreenCtx and subsequently calling
 * ::cuCtxSetCurrent / ::cuCtxPushCurrent. It should be noted that a green context can be current to only one
 * thread at a time. There is no internal synchronization to make API calls accessing the same green context
 * from multiple threads work.
 *
 * Note: The API is not supported on 32-bit platforms.
 *
 * \param phCtx - Pointer for the output handle to the green context
 * \param desc - Descriptor generated via ::cuDevResourceGenerateDesc which contains the set of resources to be used
 * \param dev - Device on which to create the green context.
 * \param flags - One of the supported green context creation flags. \p CU_GREEN_CTX_DEFAULT_STREAM is required.
 *
 * The supported flags are:
 * - \p CU_GREEN_CTX_DEFAULT_STREAM : Creates a default stream to use inside the green context. Required.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_DEVICE,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_NOT_SUPPORTED,
 * ::CUDA_ERROR_OUT_OF_MEMORY
 *
 * \sa
 * ::cuGreenCtxDestroy,
 * ::cuCtxFromGreenCtx,
 * ::cuCtxSetCurrent,
 * ::cuCtxPushCurrent,
 * ::cuDevResourceGenerateDesc,
 * ::cuDevicePrimaryCtxRetain,
 * ::cuCtxCreate,
 * ::cuCtxCreate_v3
 */
CUresult CUDAAPI cuGreenCtxCreate(CUgreenCtx* phCtx, CUdevResourceDesc desc, CUdevice dev, unsigned int flags);

/**
 * \brief Destroys a green context
 *
 * Destroys the green context, releasing the primary context of the device that this green context was created for.
 * Any resources provisioned for this green context (that were initially available via the resource descriptor)
 * are released as well.
 * \param hCtx - Green context to be destroyed
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_CONTEXT_IS_DESTROYED
 *
 * \sa
 * ::cuGreenCtxCreate,
 * ::cuCtxDestroy
 */
CUresult CUDAAPI cuGreenCtxDestroy(CUgreenCtx hCtx);

/**
 * \brief Converts a green context into the primary context
 *
 * The API converts a green context into the primary context returned in \p pContext. It is important
 * to note that the converted context \p pContext is a normal primary context but with
 * the resources of the specified green context \p hCtx. Once converted, it can then
 * be used to set the context current with ::cuCtxSetCurrent or with any of the CUDA APIs
 * that accept a CUcontext parameter.
 *
 * Users are expected to call this API before calling any CUDA APIs that accept a
 * CUcontext. Failing to do so will result in the APIs returning ::CUDA_ERROR_INVALID_CONTEXT.
 *
 * \param pContext Returned primary context with green context resources
 * \param hCtx Green context to convert
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa
 * ::cuGreenCtxCreate
 */
CUresult CUDAAPI cuCtxFromGreenCtx(CUcontext *pContext, CUgreenCtx hCtx);

/**
 * \brief Get device resources
 *
 * Get the \p type resources available to the \p device.
 * This may often be the starting point for further partitioning or configuring of resources.
 *
 * Note: The API is not supported on 32-bit platforms.
 *
 * \param device - Device to get resource for
 * \param resource - Output pointer to a CUdevResource structure
 * \param type - Type of resource to retrieve
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_RESOURCE_TYPE,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_DEVICE
 *
 * \sa
 * ::cuDevResourceGenerateDesc
 */
CUresult CUDAAPI cuDeviceGetDevResource(CUdevice device, CUdevResource* resource, CUdevResourceType type);

/**
 * \brief Get context resources
 *
 * Get the \p type resources available to the context represented by \p hCtx
 * \param hCtx - Context to get resource for
 *
 * Note: The API is not supported on 32-bit platforms.
 *
 * \param resource - Output pointer to a CUdevResource structure
 * \param type - Type of resource to retrieve
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_RESOURCE_TYPE,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_CONTEXT
 *
 * \sa
 * ::cuDevResourceGenerateDesc
 */
CUresult CUDAAPI cuCtxGetDevResource(CUcontext hCtx, CUdevResource* resource, CUdevResourceType type);

/**
 * \brief Get green context resources
 *
 * Get the \p type resources available to the green context represented by \p hCtx
 * \param hCtx - Green context to get resource for
 * \param resource - Output pointer to a CUdevResource structure
 * \param type - Type of resource to retrieve
 *
 * \return
 * ::CUDA_SUCCESS
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_RESOURCE_TYPE,
 * ::CUDA_ERROR_INVALID_VALUE
 *
 * \sa
 * ::cuDevResourceGenerateDesc
 */
CUresult CUDAAPI cuGreenCtxGetDevResource(CUgreenCtx hCtx, CUdevResource* resource, CUdevResourceType type);

/**
 * \brief Splits \p CU_DEV_RESOURCE_TYPE_SM resources.
 *
 * Splits \p CU_DEV_RESOURCE_TYPE_SM resources into \p nbGroups, adhering to the minimum SM count specified in \p minCount
 * and the usage flags in \p useFlags. If \p result is NULL, the API simulates a split and provides the amount of groups that
 * would be created in \p nbGroups. Otherwise, \p nbGroups must point to the amount of elements in \p result and on return,
 * the API will overwrite \p nbGroups with the amount actually created. The groups are written to the array in \p result.
 * \p nbGroups can be less than the total amount if a smaller number of groups is needed.
 *
 * This API is used to spatially partition the input resource. The input resource needs to come from one of
 * ::cuDeviceGetDevResource, ::cuCtxGetDevResource, or ::cuGreenCtxGetDevResource.
 * A limitation of the API is that the output results cannot be split again without
 * first creating a descriptor and a green context with that descriptor.
 *
 * When creating the groups, the API will take into account the performance and functional characteristics of the
 * input resource, and guarantee a split that will create a disjoint set of symmetrical partitions. This may lead to fewer groups created
 * than purely dividing the total SM count by the \p minCount due to cluster requirements or
 * alignment and granularity requirements for the minCount.
 *
 * The \p remainder set does not have the same functional or performance guarantees as the groups in \p result.
 * Its use should be carefully planned and future partitions of the \p remainder set are discouraged.
 *
 * The following flags are supported:
 * - \p CU_DEV_SM_RESOURCE_SPLIT_IGNORE_SM_COSCHEDULING : Lower the minimum SM count and alignment, and treat each SM independent of its hierarchy.
 *  This allows more fine grained partitions but at the cost of advanced features (such as large clusters on compute capability 9.0+).
 * - \p CU_DEV_SM_RESOURCE_SPLIT_MAX_POTENTIAL_CLUSTER_SIZE : Compute Capability 9.0+ only. Attempt to create groups that may allow
 *  for maximally sized thread clusters. This can be queried post green context creation using ::cuOccupancyMaxPotentialClusterSize.
 *
 * A successful API call must either have:
 * - A valid array of \p result pointers of size passed in \p nbGroups, with \p input of type \p CU_DEV_RESOURCE_TYPE_SM.
 * Value of \p minCount must be between 0 and the SM count specified in \p input. \p remaining may be NULL.
 * - NULL passed in for \p result, with a valid integer pointer in \p nbGroups and \p input of type \p CU_DEV_RESOURCE_TYPE_SM.
 * Value of \p minCount must be between 0 and the SM count specified in \p input. \p remaining may be NULL.
 * This queries the number of groups that would be created by the API.
 *
 * Note: The API is not supported on 32-bit platforms.
 *
 * \param result - Output array of \p CUdevResource resources. Can be NULL to query the number of groups.
 * \param nbGroups - This is a pointer, specifying the number of groups that would be or should be created as described below.
 * \param input - Input SM resource to be split. Must be a valid \p CU_DEV_RESOURCE_TYPE_SM resource.
 * \param remaining - If the input resource cannot be cleanly split among \p nbGroups, the remaining is placed in here.
 * Can be ommitted (NULL) if the user does not need the remaining set.
 * \param useFlags - Flags specifying how these partitions are used or which constraints to abide by when splitting the input. Zero is valid for default behavior.
 * \param minCount - Minimum number of SMs required
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_DEVICE,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_RESOURCE_TYPE,
 * ::CUDA_ERROR_INVALID_RESOURCE_CONFIGURATION
 *
 * \sa
 * ::cuGreenCtxGetDevResource,
 * ::cuCtxGetDevResource,
 * ::cuDeviceGetDevResource
 */
CUresult CUDAAPI cuDevSmResourceSplitByCount(
    CUdevResource* result, unsigned int* nbGroups, const CUdevResource* input, CUdevResource* remaining, unsigned int useFlags, unsigned int minCount);

/**
 * \brief Generate a resource descriptor
 *
 * Generates a single resource descriptor with the set of resources specified in \p resources.
 * The generated resource descriptor is necessary for the creation of green contexts via the ::cuGreenCtxCreate API.
 * Resources of the same type can be passed in, provided they meet the requirements as noted below.
 *
 * A successful API call must have:
 * - A valid output pointer for the \p phDesc descriptor as well as a valid array of \p resources pointers,
 * with the array size passed in \p nbResources.
 * If multiple resources are provided in \p resources, the device they came from must be the same,
 * otherwise CUDA_ERROR_INVALID_RESOURCE_CONFIGURATION is returned.
 * If multiple resources are provided in \p resources and they are of type ::CU_DEV_RESOURCE_TYPE_SM,
 * they must be outputs (whether \p result or \p remaining) from the same split API instance,
 * otherwise CUDA_ERROR_INVALID_RESOURCE_CONFIGURATION is returned.
 *
 * Note: The API is not supported on 32-bit platforms.
 *
 * \param phDesc - Output descriptor
 * \param resources - Array of resources to be included in the descriptor
 * \param nbResources - Number of resources passed in \p resources
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_INVALID_RESOURCE_TYPE,
 * ::CUDA_ERROR_INVALID_RESOURCE_CONFIGURATION
 *
 * \sa
 * ::cuDevSmResourceSplitByCount
 */
CUresult CUDAAPI cuDevResourceGenerateDesc(CUdevResourceDesc *phDesc, CUdevResource *resources, unsigned int nbResources);

/**
 * \brief Records an event.
 *
 * Captures in \p hEvent all the activities of the green context of \p hCtx
 * at the time of this call. \p hEvent and \p hCtx must be from the same
 * primary context otherwise ::CUDA_ERROR_INVALID_HANDLE is returned.
 * Calls such as ::cuEventQuery() or ::cuGreenCtxWaitEvent() will
 * then examine or wait for completion of the work that was captured. Uses of
 * \p hCtx after this call do not modify \p hEvent.
 *
 * \note The API will return ::CUDA_ERROR_STREAM_CAPTURE_UNSUPPORTED if the
 * specified green context \p hCtx has a stream in the capture mode. In such
 * a case, the call will invalidate all the conflicting captures.
 *
 * \param hCtx - Green context to record event for
 * \param hEvent  - Event to record
 *
 * \return
 * ::CUDA_SUCCESS
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_STREAM_CAPTURE_UNSUPPORTED
 *
 * \sa
 * ::cuGreenCtxWaitEvent,
 * ::cuEventRecord,
 * ::cuCtxRecordEvent,
 * ::cuCtxWaitEvent
 */
CUresult CUDAAPI cuGreenCtxRecordEvent(CUgreenCtx hCtx, CUevent hEvent);

/**
 * \brief Make a green context wait on an event
 *
 * Makes all future work submitted to green context \p hCtx wait for all work
 * captured in \p hEvent. The synchronization will be performed on the device
 * and will not block the calling CPU thread. See ::cuGreenCtxRecordEvent()
 * or ::cuEventRecord(), for details on what is captured by an event.
 *
 * \note \p hEvent may be from a different context or device than \p hCtx.
 *
 * \note The API will return ::CUDA_ERROR_STREAM_CAPTURE_UNSUPPORTED and
 * invalidate the capture if the specified event \p hEvent is part of an
 * ongoing capture sequence or if the specified green context \p hCtx has
 * a stream in the capture mode.
 *
 * \param hCtx    - Green context to wait
 * \param hEvent  - Event to wait on
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * ::CUDA_ERROR_STREAM_CAPTURE_UNSUPPORTED
 *
 * \sa
 * ::cuGreenCtxRecordEvent,
 * ::cuStreamWaitEvent
 * ::cuCtxRecordEvent,
 * ::cuCtxWaitEvent
*/
CUresult CUDAAPI cuGreenCtxWaitEvent(CUgreenCtx hCtx, CUevent hEvent);

/**
 * \brief Query the green context associated with a stream
 *
 * Returns the CUDA green context that the stream is associated with, or NULL if the stream
 * is not associated with any green context.
 *
 * The stream handle \p hStream can refer to any of the following:
 * <ul>
 *   <li>
 *   a stream created via any of the CUDA driver APIs such as ::cuStreamCreate, ::cuStreamCreateWithPriority
 *   and ::cuGreenCtxStreamCreate, or their runtime API equivalents such as
 *   ::cudaStreamCreate, ::cudaStreamCreateWithFlags and ::cudaStreamCreateWithPriority.
 *   If during stream creation the context that was active in the calling thread was obtained
 *   with cuCtxFromGreenCtx, that green context is returned in \p phCtx.
 *   Otherwise, \p *phCtx is set to NULL instead.
 *   </li>
 *   <li>
 *   special stream such as the NULL stream or ::CU_STREAM_LEGACY.
 *   In that case if context that is active in the calling thread was obtained
 *   with cuCtxFromGreenCtx, that green context is returned.
 *   Otherwise, \p *phCtx is set to NULL instead.
 *   </li>
 * </ul>
 * Passing an invalid handle will result in undefined behavior.
 *
 * \param hStream - Handle to the stream to be queried
 * \param phCtx   - Returned green context associated with the stream
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_HANDLE,
 * \notefnerr
 *
 * \sa ::cuStreamDestroy,
 * ::cuStreamCreate,
 * ::cuStreamCreateWithPriority,
 * ::cuStreamGetCtx_v2,
 * ::cuGreenCtxStreamCreate,
 * ::cuStreamGetPriority,
 * ::cuStreamGetFlags,
 * ::cuStreamGetDevice
 * ::cuStreamWaitEvent,
 * ::cuStreamQuery,
 * ::cuStreamSynchronize,
 * ::cuStreamAddCallback,
 * ::cudaStreamCreate,
 * ::cudaStreamCreateWithFlags
 */
CUresult CUDAAPI cuStreamGetGreenCtx(CUstream hStream, CUgreenCtx *phCtx);

/**
 * \brief Create a stream for use in the green context
 *
 * Creates a stream for use in the specified green context \p greenCtx and returns a handle in \p phStream.
 * The stream can be destroyed by calling ::cuStreamDestroy(). Note that the API ignores the context that
 * is current to the calling thread and creates a stream in the specified green context \p greenCtx.
 *
 * The supported values for \p flags are:
 * - ::CU_STREAM_NON_BLOCKING: This must be specified. It indicates that work running in the created
 *   stream may run concurrently with work in the default stream, and that
 *   the created stream should perform no implicit synchronization with the default stream.
 *
 * Specifying \p priority affects the scheduling priority of work in the stream. Priorities provide a
 * hint to preferentially run work with higher priority when possible, but do not preempt
 * already-running work or provide any other functional guarantee on execution order.
 * \p priority follows a convention where lower numbers represent higher priorities.
 * '0' represents default priority. The range of meaningful numerical priorities can
 * be queried using ::cuCtxGetStreamPriorityRange. If the specified priority is
 * outside the numerical range returned by ::cuCtxGetStreamPriorityRange,
 * it will automatically be clamped to the lowest or the highest number in the range.
 *
 * \param phStream - Returned newly created stream
 * \param greenCtx - Green context for which to create the stream for
 * \param flags    - Flags for stream creation. \p CU_STREAM_NON_BLOCKING must be specified.
 * \param priority - Stream priority. Lower numbers represent higher priorities.
 *                   See ::cuCtxGetStreamPriorityRange for more information about
 *                   meaningful stream priorities that can be passed.
 *
 * \return
 * ::CUDA_SUCCESS,
 * ::CUDA_ERROR_DEINITIALIZED,
 * ::CUDA_ERROR_NOT_INITIALIZED,
 * ::CUDA_ERROR_INVALID_CONTEXT,
 * ::CUDA_ERROR_INVALID_VALUE,
 * ::CUDA_ERROR_OUT_OF_MEMORY
 * \notefnerr
 *
 * \note In the current implementation, only compute kernels launched in
 * priority streams are affected by the stream's priority. Stream priorities have
 * no effect on host-to-device and device-to-host memory operations.
 *
 * \sa ::cuStreamDestroy,
 * ::cuGreenCtxCreate
 * ::cuStreamCreate,
 * ::cuStreamGetPriority,
 * ::cuCtxGetStreamPriorityRange,
 * ::cuStreamGetFlags,
 * ::cuStreamGetDevice
 * ::cuStreamWaitEvent,
 * ::cuStreamQuery,
 * ::cuStreamSynchronize,
 * ::cuStreamAddCallback,
 * ::cudaStreamCreateWithPriority
 */
CUresult CUDAAPI cuGreenCtxStreamCreate(CUstream* phStream, CUgreenCtx greenCtx, unsigned int flags, int priority);

/** @} */

/*
** *************** END CUDA_GREEN_CONTEXTS *****************
*/

/**
 * CUDA API versioning support
 */
#if defined(__CUDA_API_VERSION_INTERNAL)
    #undef cuMemHostRegister
    #undef cuGraphicsResourceSetMapFlags
    #undef cuLinkCreate
    #undef cuLinkAddData
    #undef cuLinkAddFile
    #undef cuDeviceTotalMem
    #undef cuCtxCreate
    #undef cuModuleGetGlobal
    #undef cuMemGetInfo
    #undef cuMemAlloc
    #undef cuMemAllocPitch
    #undef cuMemFree
    #undef cuMemGetAddressRange
    #undef cuMemAllocHost
    #undef cuMemHostGetDevicePointer
    #undef cuMemcpyHtoD
    #undef cuMemcpyDtoH
    #undef cuMemcpyDtoD
    #undef cuMemcpyDtoA
    #undef cuMemcpyAtoD
    #undef cuMemcpyHtoA
    #undef cuMemcpyAtoH
    #undef cuMemcpyAtoA
    #undef cuMemcpyHtoAAsync
    #undef cuMemcpyAtoHAsync
    #undef cuMemcpy2D
    #undef cuMemcpy2DUnaligned
    #undef cuMemcpy3D
    #undef cuMemcpyHtoDAsync
    #undef cuMemcpyDtoHAsync
    #undef cuMemcpyDtoDAsync
    #undef cuMemcpy2DAsync
    #undef cuMemcpy3DAsync
    #undef cuMemcpyBatchAsync
    #undef cuMemcpy3DBatchAsync
    #undef cuMemsetD8
    #undef cuMemsetD16
    #undef cuMemsetD32
    #undef cuMemsetD2D8
    #undef cuMemsetD2D16
    #undef cuMemsetD2D32
    #undef cuArrayCreate
    #undef cuArrayGetDescriptor
    #undef cuArray3DCreate
    #undef cuArray3DGetDescriptor
    #undef cuTexRefSetAddress
    #undef cuTexRefSetAddress2D
    #undef cuTexRefGetAddress
    #undef cuGraphicsResourceGetMappedPointer
    #undef cuCtxDestroy
    #undef cuCtxPopCurrent
    #undef cuCtxPushCurrent
    #undef cuStreamDestroy
    #undef cuEventDestroy
    #undef cuMemcpy
    #undef cuMemcpyAsync
    #undef cuMemcpyPeer
    #undef cuMemcpyPeerAsync
    #undef cuMemcpy3DPeer
    #undef cuMemcpy3DPeerAsync
    #undef cuMemsetD8Async
    #undef cuMemsetD16Async
    #undef cuMemsetD32Async
    #undef cuMemsetD2D8Async
    #undef cuMemsetD2D16Async
    #undef cuMemsetD2D32Async
    #undef cuStreamGetPriority
    #undef cuStreamGetId
    #undef cuStreamGetFlags
    #undef cuStreamGetDevice
    #undef cuStreamGetCtx
    #undef cuStreamWaitEvent
    #undef cuStreamAddCallback
    #undef cuStreamAttachMemAsync
    #undef cuStreamQuery
    #undef cuStreamSynchronize
    #undef cuEventRecord
    #undef cuEventRecordWithFlags
    #undef cuLaunchKernel
    #undef cuLaunchKernelEx
    #undef cuLaunchHostFunc
    #undef cuGraphicsMapResources
    #undef cuGraphicsUnmapResources
    #undef cuStreamWriteValue32
    #undef cuStreamWaitValue32
    #undef cuStreamWriteValue64
    #undef cuStreamWaitValue64
    #undef cuStreamBatchMemOp
    #undef cuStreamWriteValue32_v2
    #undef cuStreamWaitValue32_v2
    #undef cuStreamWriteValue64_v2
    #undef cuStreamWaitValue64_v2
    #undef cuStreamBatchMemOp_v2
    #undef cuMemPrefetchAsync
    #undef cuMemPrefetchAsync_v2
    #undef cuLaunchCooperativeKernel
    #undef cuSignalExternalSemaphoresAsync
    #undef cuWaitExternalSemaphoresAsync
    #undef cuStreamBeginCapture
    #undef cuStreamBeginCaptureToGraph
    #undef cuStreamEndCapture
    #undef cuStreamIsCapturing
    #undef cuStreamGetCaptureInfo
    #undef cuStreamGetCaptureInfo_v2
    #undef cuStreamGetCaptureInfo_v3
    #undef cuGraphInstantiateWithParams
    #undef cuGraphExecUpdate
    #undef cuGraphUpload
    #undef cuGraphLaunch
    #undef cuDevicePrimaryCtxRelease
    #undef cuDevicePrimaryCtxReset
    #undef cuDevicePrimaryCtxSetFlags
    #undef cuIpcOpenMemHandle
    #undef cuStreamCopyAttributes
    #undef cuStreamSetAttribute
    #undef cuStreamGetAttribute
    #undef cuGraphInstantiate
    #undef cuGraphAddKernelNode
    #undef cuGraphKernelNodeGetParams
    #undef cuGraphKernelNodeSetParams
    #undef cuGraphExecKernelNodeSetParams
    #undef cuMemMapArrayAsync
    #undef cuMemFreeAsync 
    #undef cuMemAllocAsync 
    #undef cuMemAllocFromPoolAsync 
    #undef cuStreamUpdateCaptureDependencies
    #undef cuStreamUpdateCaptureDependencies_v2
    #undef cuGetProcAddress
    #undef cuStreamGetCtx_v2
    #undef cuMemBatchDecompressAsync

    CUresult CUDAAPI cuMemHostRegister(void *p, size_t bytesize, unsigned int Flags);
    CUresult CUDAAPI cuGraphicsResourceSetMapFlags(CUgraphicsResource resource, unsigned int flags);
    CUresult CUDAAPI cuLinkCreate(unsigned int numOptions, CUjit_option *options, void **optionValues, CUlinkState *stateOut);
    CUresult CUDAAPI cuLinkAddData(CUlinkState state, CUjitInputType type, void *data, size_t size, const char *name,
        unsigned int numOptions, CUjit_option *options, void **optionValues);
    CUresult CUDAAPI cuLinkAddFile(CUlinkState state, CUjitInputType type, const char *path,
        unsigned int numOptions, CUjit_option *options, void **optionValues);
    CUresult CUDAAPI cuTexRefSetAddress2D_v2(CUtexref hTexRef, const CUDA_ARRAY_DESCRIPTOR *desc, CUdeviceptr dptr, size_t Pitch);

    typedef unsigned int CUdeviceptr_v1;

    typedef struct CUDA_MEMCPY2D_v1_st
    {
        unsigned int srcXInBytes;   /**< Source X in bytes */
        unsigned int srcY;          /**< Source Y */
        CUmemorytype srcMemoryType; /**< Source memory type (host, device, array) */
        const void *srcHost;        /**< Source host pointer */
        CUdeviceptr_v1 srcDevice;   /**< Source device pointer */
        CUarray srcArray;           /**< Source array reference */
        unsigned int srcPitch;      /**< Source pitch (ignored when src is array) */

        unsigned int dstXInBytes;   /**< Destination X in bytes */
        unsigned int dstY;          /**< Destination Y */
        CUmemorytype dstMemoryType; /**< Destination memory type (host, device, array) */
        void *dstHost;              /**< Destination host pointer */
        CUdeviceptr_v1 dstDevice;   /**< Destination device pointer */
        CUarray dstArray;           /**< Destination array reference */
        unsigned int dstPitch;      /**< Destination pitch (ignored when dst is array) */

        unsigned int WidthInBytes;  /**< Width of 2D memory copy in bytes */
        unsigned int Height;        /**< Height of 2D memory copy */
    } CUDA_MEMCPY2D_v1;

    typedef struct CUDA_MEMCPY3D_v1_st
    {
        unsigned int srcXInBytes;   /**< Source X in bytes */
        unsigned int srcY;          /**< Source Y */
        unsigned int srcZ;          /**< Source Z */
        unsigned int srcLOD;        /**< Source LOD */
        CUmemorytype srcMemoryType; /**< Source memory type (host, device, array) */
        const void *srcHost;        /**< Source host pointer */
        CUdeviceptr_v1 srcDevice;   /**< Source device pointer */
        CUarray srcArray;           /**< Source array reference */
        void *reserved0;            /**< Must be NULL */
        unsigned int srcPitch;      /**< Source pitch (ignored when src is array) */
        unsigned int srcHeight;     /**< Source height (ignored when src is array; may be 0 if Depth==1) */

        unsigned int dstXInBytes;   /**< Destination X in bytes */
        unsigned int dstY;          /**< Destination Y */
        unsigned int dstZ;          /**< Destination Z */
        unsigned int dstLOD;        /**< Destination LOD */
        CUmemorytype dstMemoryType; /**< Destination memory type (host, device, array) */
        void *dstHost;              /**< Destination host pointer */
        CUdeviceptr_v1 dstDevice;   /**< Destination device pointer */
        CUarray dstArray;           /**< Destination array reference */
        void *reserved1;            /**< Must be NULL */
        unsigned int dstPitch;      /**< Destination pitch (ignored when dst is array) */
        unsigned int dstHeight;     /**< Destination height (ignored when dst is array; may be 0 if Depth==1) */

        unsigned int WidthInBytes;  /**< Width of 3D memory copy in bytes */
        unsigned int Height;        /**< Height of 3D memory copy */
        unsigned int Depth;         /**< Depth of 3D memory copy */
    } CUDA_MEMCPY3D_v1;

    typedef struct CUDA_ARRAY_DESCRIPTOR_v1_st
    {
        unsigned int Width;         /**< Width of array */
        unsigned int Height;        /**< Height of array */

        CUarray_format Format;      /**< Array format */
        unsigned int NumChannels;   /**< Channels per array element */
    } CUDA_ARRAY_DESCRIPTOR_v1;

    typedef struct CUDA_ARRAY3D_DESCRIPTOR_v1_st
    {
        unsigned int Width;         /**< Width of 3D array */
        unsigned int Height;        /**< Height of 3D array */
        unsigned int Depth;         /**< Depth of 3D array */

        CUarray_format Format;      /**< Array format */
        unsigned int NumChannels;   /**< Channels per array element */
        unsigned int Flags;         /**< Flags */
    } CUDA_ARRAY3D_DESCRIPTOR_v1;

    CUresult CUDAAPI cuDeviceTotalMem(unsigned int *bytes, CUdevice dev);
    CUresult CUDAAPI cuCtxCreate(CUcontext *pctx, unsigned int flags, CUdevice dev);
    CUresult CUDAAPI cuModuleGetGlobal(CUdeviceptr_v1 *dptr, unsigned int *bytes, CUmodule hmod, const char *name);
    CUresult CUDAAPI cuMemGetInfo(unsigned int *free, unsigned int *total);
    CUresult CUDAAPI cuMemAlloc(CUdeviceptr_v1 *dptr, unsigned int bytesize);
    CUresult CUDAAPI cuMemAllocPitch(CUdeviceptr_v1 *dptr, unsigned int *pPitch, unsigned int WidthInBytes, unsigned int Height, unsigned int ElementSizeBytes);
    CUresult CUDAAPI cuMemFree(CUdeviceptr_v1 dptr);
    CUresult CUDAAPI cuMemGetAddressRange(CUdeviceptr_v1 *pbase, unsigned int *psize, CUdeviceptr_v1 dptr);
    CUresult CUDAAPI cuMemAllocHost(void **pp, unsigned int bytesize);
    CUresult CUDAAPI cuMemHostGetDevicePointer(CUdeviceptr_v1 *pdptr, void *p, unsigned int Flags);
    CUresult CUDAAPI cuMemcpyHtoD(CUdeviceptr_v1 dstDevice, const void *srcHost, unsigned int ByteCount);
    CUresult CUDAAPI cuMemcpyDtoH(void *dstHost, CUdeviceptr_v1 srcDevice, unsigned int ByteCount);
    CUresult CUDAAPI cuMemcpyDtoD(CUdeviceptr_v1 dstDevice, CUdeviceptr_v1 srcDevice, unsigned int ByteCount);
    CUresult CUDAAPI cuMemcpyDtoA(CUarray dstArray, unsigned int dstOffset, CUdeviceptr_v1 srcDevice, unsigned int ByteCount);
    CUresult CUDAAPI cuMemcpyAtoD(CUdeviceptr_v1 dstDevice, CUarray srcArray, unsigned int srcOffset, unsigned int ByteCount);
    CUresult CUDAAPI cuMemcpyHtoA(CUarray dstArray, unsigned int dstOffset, const void *srcHost, unsigned int ByteCount);
    CUresult CUDAAPI cuMemcpyAtoH(void *dstHost, CUarray srcArray, unsigned int srcOffset, unsigned int ByteCount);
    CUresult CUDAAPI cuMemcpyAtoA(CUarray dstArray, unsigned int dstOffset, CUarray srcArray, unsigned int srcOffset, unsigned int ByteCount);
    CUresult CUDAAPI cuMemcpyHtoAAsync(CUarray dstArray, unsigned int dstOffset, const void *srcHost, unsigned int ByteCount, CUstream hStream);
    CUresult CUDAAPI cuMemcpyAtoHAsync(void *dstHost, CUarray srcArray, unsigned int srcOffset, unsigned int ByteCount, CUstream hStream);
    CUresult CUDAAPI cuMemcpy2D(const CUDA_MEMCPY2D_v1 *pCopy);
    CUresult CUDAAPI cuMemcpy2DUnaligned(const CUDA_MEMCPY2D_v1 *pCopy);
    CUresult CUDAAPI cuMemcpy3D(const CUDA_MEMCPY3D_v1 *pCopy);
    CUresult CUDAAPI cuMemcpyHtoDAsync(CUdeviceptr_v1 dstDevice, const void *srcHost, unsigned int ByteCount, CUstream hStream);
    CUresult CUDAAPI cuMemcpyDtoHAsync(void *dstHost, CUdeviceptr_v1 srcDevice, unsigned int ByteCount, CUstream hStream);
    CUresult CUDAAPI cuMemcpyDtoDAsync(CUdeviceptr_v1 dstDevice, CUdeviceptr_v1 srcDevice, unsigned int ByteCount, CUstream hStream);
    CUresult CUDAAPI cuMemcpy2DAsync(const CUDA_MEMCPY2D_v1 *pCopy, CUstream hStream);
    CUresult CUDAAPI cuMemcpy3DAsync(const CUDA_MEMCPY3D_v1 *pCopy, CUstream hStream);
    CUresult CUDAAPI cuMemsetD8(CUdeviceptr_v1 dstDevice, unsigned char uc, unsigned int N);
    CUresult CUDAAPI cuMemsetD16(CUdeviceptr_v1 dstDevice, unsigned short us, unsigned int N);
    CUresult CUDAAPI cuMemsetD32(CUdeviceptr_v1 dstDevice, unsigned int ui, unsigned int N);
    CUresult CUDAAPI cuMemsetD2D8(CUdeviceptr_v1 dstDevice, unsigned int dstPitch, unsigned char uc, unsigned int Width, unsigned int Height);
    CUresult CUDAAPI cuMemsetD2D16(CUdeviceptr_v1 dstDevice, unsigned int dstPitch, unsigned short us, unsigned int Width, unsigned int Height);
    CUresult CUDAAPI cuMemsetD2D32(CUdeviceptr_v1 dstDevice, unsigned int dstPitch, unsigned int ui, unsigned int Width, unsigned int Height);
    CUresult CUDAAPI cuArrayCreate(CUarray *pHandle, const CUDA_ARRAY_DESCRIPTOR_v1 *pAllocateArray);
    CUresult CUDAAPI cuArrayGetDescriptor(CUDA_ARRAY_DESCRIPTOR_v1 *pArrayDescriptor, CUarray hArray);
    CUresult CUDAAPI cuArray3DCreate(CUarray *pHandle, const CUDA_ARRAY3D_DESCRIPTOR_v1 *pAllocateArray);
    CUresult CUDAAPI cuArray3DGetDescriptor(CUDA_ARRAY3D_DESCRIPTOR_v1 *pArrayDescriptor, CUarray hArray);
    CUresult CUDAAPI cuTexRefSetAddress(unsigned int *ByteOffset, CUtexref hTexRef, CUdeviceptr_v1 dptr, unsigned int bytes);
    CUresult CUDAAPI cuTexRefSetAddress2D(CUtexref hTexRef, const CUDA_ARRAY_DESCRIPTOR_v1 *desc, CUdeviceptr_v1 dptr, unsigned int Pitch);
    CUresult CUDAAPI cuTexRefGetAddress(CUdeviceptr_v1 *pdptr, CUtexref hTexRef);
    CUresult CUDAAPI cuGraphicsResourceGetMappedPointer(CUdeviceptr_v1 *pDevPtr, unsigned int *pSize, CUgraphicsResource resource);

    CUresult CUDAAPI cuCtxDestroy(CUcontext ctx);
    CUresult CUDAAPI cuCtxPopCurrent(CUcontext *pctx);
    CUresult CUDAAPI cuCtxPushCurrent(CUcontext ctx);
    CUresult CUDAAPI cuStreamDestroy(CUstream hStream);
    CUresult CUDAAPI cuEventDestroy(CUevent hEvent);
    CUresult CUDAAPI cuDevicePrimaryCtxRelease(CUdevice dev);
    CUresult CUDAAPI cuDevicePrimaryCtxReset(CUdevice dev);
    CUresult CUDAAPI cuDevicePrimaryCtxSetFlags(CUdevice dev, unsigned int flags);

    CUresult CUDAAPI cuMemcpyHtoD_v2(CUdeviceptr dstDevice, const void *srcHost, size_t ByteCount);
    CUresult CUDAAPI cuMemcpyDtoH_v2(void *dstHost, CUdeviceptr srcDevice, size_t ByteCount);
    CUresult CUDAAPI cuMemcpyDtoD_v2(CUdeviceptr dstDevice, CUdeviceptr srcDevice, size_t ByteCount);
    CUresult CUDAAPI cuMemcpyDtoA_v2(CUarray dstArray, size_t dstOffset, CUdeviceptr srcDevice, size_t ByteCount);
    CUresult CUDAAPI cuMemcpyAtoD_v2(CUdeviceptr dstDevice, CUarray srcArray, size_t srcOffset, size_t ByteCount);
    CUresult CUDAAPI cuMemcpyHtoA_v2(CUarray dstArray, size_t dstOffset, const void *srcHost, size_t ByteCount);
    CUresult CUDAAPI cuMemcpyAtoH_v2(void *dstHost, CUarray srcArray, size_t srcOffset, size_t ByteCount);
    CUresult CUDAAPI cuMemcpyAtoA_v2(CUarray dstArray, size_t dstOffset, CUarray srcArray, size_t srcOffset, size_t ByteCount);
    CUresult CUDAAPI cuMemcpyHtoAAsync_v2(CUarray dstArray, size_t dstOffset, const void *srcHost, size_t ByteCount, CUstream hStream);
    CUresult CUDAAPI cuMemcpyAtoHAsync_v2(void *dstHost, CUarray srcArray, size_t srcOffset, size_t ByteCount, CUstream hStream);
    CUresult CUDAAPI cuMemcpy2D_v2(const CUDA_MEMCPY2D *pCopy);
    CUresult CUDAAPI cuMemcpy2DUnaligned_v2(const CUDA_MEMCPY2D *pCopy);
    CUresult CUDAAPI cuMemcpy3D_v2(const CUDA_MEMCPY3D *pCopy);
    CUresult CUDAAPI cuMemcpyHtoDAsync_v2(CUdeviceptr dstDevice, const void *srcHost, size_t ByteCount, CUstream hStream);
    CUresult CUDAAPI cuMemcpyDtoHAsync_v2(void *dstHost, CUdeviceptr srcDevice, size_t ByteCount, CUstream hStream);
    CUresult CUDAAPI cuMemcpyDtoDAsync_v2(CUdeviceptr dstDevice, CUdeviceptr srcDevice, size_t ByteCount, CUstream hStream);
    CUresult CUDAAPI cuMemcpy2DAsync_v2(const CUDA_MEMCPY2D *pCopy, CUstream hStream);
    CUresult CUDAAPI cuMemcpy3DAsync_v2(const CUDA_MEMCPY3D *pCopy, CUstream hStream);
    CUresult CUDAAPI cuMemsetD8_v2(CUdeviceptr dstDevice, unsigned char uc, size_t N);
    CUresult CUDAAPI cuMemsetD16_v2(CUdeviceptr dstDevice, unsigned short us, size_t N);
    CUresult CUDAAPI cuMemsetD32_v2(CUdeviceptr dstDevice, unsigned int ui, size_t N);
    CUresult CUDAAPI cuMemsetD2D8_v2(CUdeviceptr dstDevice, size_t dstPitch, unsigned char uc, size_t Width, size_t Height);
    CUresult CUDAAPI cuMemsetD2D16_v2(CUdeviceptr dstDevice, size_t dstPitch, unsigned short us, size_t Width, size_t Height);
    CUresult CUDAAPI cuMemsetD2D32_v2(CUdeviceptr dstDevice, size_t dstPitch, unsigned int ui, size_t Width, size_t Height);
    CUresult CUDAAPI cuMemcpy(CUdeviceptr dst, CUdeviceptr src, size_t ByteCount);
    CUresult CUDAAPI cuMemcpyAsync(CUdeviceptr dst, CUdeviceptr src, size_t ByteCount, CUstream hStream);
    CUresult CUDAAPI cuMemcpyPeer(CUdeviceptr dstDevice, CUcontext dstContext, CUdeviceptr srcDevice, CUcontext srcContext, size_t ByteCount);
    CUresult CUDAAPI cuMemcpyPeerAsync(CUdeviceptr dstDevice, CUcontext dstContext, CUdeviceptr srcDevice, CUcontext srcContext, size_t ByteCount, CUstream hStream);
    CUresult CUDAAPI cuMemcpy3DPeer(const CUDA_MEMCPY3D_PEER *pCopy);
    CUresult CUDAAPI cuMemcpy3DPeerAsync(const CUDA_MEMCPY3D_PEER *pCopy, CUstream hStream);
    CUresult CUDAAPI cuMemcpyBatchAsync(CUdeviceptr *dsts, CUdeviceptr *srcs, size_t *sizes, size_t count,
                                        CUmemcpyAttributes *attrs, size_t *attrsIdxs, size_t numAttrs,
                                        size_t *failIdx, CUstream hStream);
    CUresult CUDAAPI cuMemcpy3DBatchAsync(size_t numOps, CUDA_MEMCPY3D_BATCH_OP *opList,
                                          size_t *failIdx, unsigned long long flags, CUstream hStream);
    CUresult CUDAAPI cuMemsetD8Async(CUdeviceptr dstDevice, unsigned char uc, size_t N, CUstream hStream);
    CUresult CUDAAPI cuMemsetD16Async(CUdeviceptr dstDevice, unsigned short us, size_t N, CUstream hStream);
    CUresult CUDAAPI cuMemsetD32Async(CUdeviceptr dstDevice, unsigned int ui, size_t N, CUstream hStream);
    CUresult CUDAAPI cuMemsetD2D8Async(CUdeviceptr dstDevice, size_t dstPitch, unsigned char uc, size_t Width, size_t Height, CUstream hStream);
    CUresult CUDAAPI cuMemsetD2D16Async(CUdeviceptr dstDevice, size_t dstPitch, unsigned short us, size_t Width, size_t Height, CUstream hStream);
    CUresult CUDAAPI cuMemsetD2D32Async(CUdeviceptr dstDevice, size_t dstPitch, unsigned int ui, size_t Width, size_t Height, CUstream hStream);

    CUresult CUDAAPI cuStreamGetPriority(CUstream hStream, int *priority);
    CUresult CUDAAPI cuStreamGetId(CUstream hStream, unsigned long long *streamId);
    CUresult CUDAAPI cuStreamGetFlags(CUstream hStream, unsigned int *flags);
    CUresult CUDAAPI cuStreamGetDevice(CUstream hStream, CUdevice *device);
    CUresult CUDAAPI cuStreamGetCtx(CUstream hStream, CUcontext *pctx);
    CUresult CUDAAPI cuStreamGetCtx_v2(CUstream hStream, CUcontext *pCtx, CUgreenCtx *pGreenCtx);
    CUresult CUDAAPI cuStreamWaitEvent(CUstream hStream, CUevent hEvent, unsigned int Flags);
    CUresult CUDAAPI cuStreamAddCallback(CUstream hStream, CUstreamCallback callback, void *userData, unsigned int flags);
    CUresult CUDAAPI cuStreamAttachMemAsync(CUstream hStream, CUdeviceptr dptr, size_t length, unsigned int flags);
    CUresult CUDAAPI cuStreamQuery(CUstream hStream);
    CUresult CUDAAPI cuStreamSynchronize(CUstream hStream);
    CUresult CUDAAPI cuEventRecord(CUevent hEvent, CUstream hStream);
    CUresult CUDAAPI cuEventRecordWithFlags(CUevent hEvent, CUstream hStream, unsigned int flags);
    CUresult CUDAAPI cuLaunchKernel(CUfunction f, unsigned int gridDimX, unsigned int gridDimY, unsigned int gridDimZ, unsigned int blockDimX, unsigned int blockDimY, unsigned int blockDimZ, unsigned int sharedMemBytes, CUstream hStream, void **kernelParams, void **extra);
    CUresult CUDAAPI cuLaunchKernelEx(const CUlaunchConfig *config, CUfunction f, void **kernelParams, void **extra);
    CUresult CUDAAPI cuLaunchHostFunc(CUstream hStream, CUhostFn fn, void *userData);
    CUresult CUDAAPI cuGraphicsMapResources(unsigned int count, CUgraphicsResource *resources, CUstream hStream);
    CUresult CUDAAPI cuGraphicsUnmapResources(unsigned int count, CUgraphicsResource *resources, CUstream hStream);
    CUresult CUDAAPI cuStreamWriteValue32(CUstream stream, CUdeviceptr addr, cuuint32_t value, unsigned int flags);
    CUresult CUDAAPI cuStreamWaitValue32(CUstream stream, CUdeviceptr addr, cuuint32_t value, unsigned int flags);
    CUresult CUDAAPI cuStreamWriteValue64(CUstream stream, CUdeviceptr addr, cuuint64_t value, unsigned int flags);
    CUresult CUDAAPI cuStreamWaitValue64(CUstream stream, CUdeviceptr addr, cuuint64_t value, unsigned int flags);
    CUresult CUDAAPI cuStreamBatchMemOp(CUstream stream, unsigned int count, CUstreamBatchMemOpParams *paramArray, unsigned int flags);

    CUresult CUDAAPI cuStreamWriteValue32_ptsz(CUstream stream, CUdeviceptr addr, cuuint32_t value, unsigned int flags);
    CUresult CUDAAPI cuStreamWaitValue32_ptsz(CUstream stream, CUdeviceptr addr, cuuint32_t value, unsigned int flags);
    CUresult CUDAAPI cuStreamWriteValue64_ptsz(CUstream stream, CUdeviceptr addr, cuuint64_t value, unsigned int flags);
    CUresult CUDAAPI cuStreamWaitValue64_ptsz(CUstream stream, CUdeviceptr addr, cuuint64_t value, unsigned int flags);
    CUresult CUDAAPI cuStreamBatchMemOp_ptsz(CUstream stream, unsigned int count, CUstreamBatchMemOpParams *paramArray, unsigned int flags);

    CUresult CUDAAPI cuStreamWriteValue32_v2(CUstream stream, CUdeviceptr addr, cuuint32_t value, unsigned int flags);
    CUresult CUDAAPI cuStreamWaitValue32_v2(CUstream stream, CUdeviceptr addr, cuuint32_t value, unsigned int flags);
    CUresult CUDAAPI cuStreamWriteValue64_v2(CUstream stream, CUdeviceptr addr, cuuint64_t value, unsigned int flags);
    CUresult CUDAAPI cuStreamWaitValue64_v2(CUstream stream, CUdeviceptr addr, cuuint64_t value, unsigned int flags);
    CUresult CUDAAPI cuStreamBatchMemOp_v2(CUstream stream, unsigned int count, CUstreamBatchMemOpParams *paramArray, unsigned int flags);
    CUresult CUDAAPI cuMemPrefetchAsync(CUdeviceptr devPtr, size_t count, CUdevice dstDevice, CUstream hStream);
    CUresult CUDAAPI cuMemPrefetchAsync_v2(CUdeviceptr devPtr, size_t count, CUmemLocation location, unsigned int flags, CUstream hStream);
    CUresult CUDAAPI cuLaunchCooperativeKernel(CUfunction f, unsigned int gridDimX, unsigned int gridDimY, unsigned int gridDimZ, unsigned int blockDimX, unsigned int blockDimY, unsigned int blockDimZ, unsigned int sharedMemBytes, CUstream hStream, void **kernelParams);
    CUresult CUDAAPI cuSignalExternalSemaphoresAsync(const CUexternalSemaphore *extSemArray, const CUDA_EXTERNAL_SEMAPHORE_SIGNAL_PARAMS *paramsArray, unsigned int numExtSems, CUstream stream);
    CUresult CUDAAPI cuWaitExternalSemaphoresAsync(const CUexternalSemaphore *extSemArray, const CUDA_EXTERNAL_SEMAPHORE_WAIT_PARAMS *paramsArray, unsigned int numExtSems, CUstream stream);
    CUresult CUDAAPI cuStreamBeginCapture(CUstream hStream);
    CUresult CUDAAPI cuStreamBeginCapture_ptsz(CUstream hStream);
    CUresult CUDAAPI cuStreamBeginCapture_v2(CUstream hStream, CUstreamCaptureMode mode);
    CUresult CUDAAPI cuStreamBeginCaptureToGraph(CUstream hStream, CUgraph hGraph, const CUgraphNode *dependencies, const CUgraphEdgeData *dependencyData, size_t numDependencies, CUstreamCaptureMode mode);
    CUresult CUDAAPI cuStreamEndCapture(CUstream hStream, CUgraph *phGraph);
    CUresult CUDAAPI cuStreamIsCapturing(CUstream hStream, CUstreamCaptureStatus *captureStatus);
    CUresult CUDAAPI cuStreamGetCaptureInfo(CUstream hStream, CUstreamCaptureStatus *captureStatus_out, cuuint64_t *id_out);
    CUresult CUDAAPI cuStreamGetCaptureInfo_ptsz(CUstream hStream, CUstreamCaptureStatus *captureStatus_out, cuuint64_t *id_out);
    CUresult CUDAAPI cuStreamGetCaptureInfo_v2(CUstream hStream, CUstreamCaptureStatus *captureStatus_out, cuuint64_t *id_out, CUgraph *graph_out, const CUgraphNode **dependencies_out, size_t *numDependencies_out);
    CUresult CUDAAPI cuStreamGetCaptureInfo_v3(CUstream hStream, CUstreamCaptureStatus *captureStatus_out, cuuint64_t *id_out, CUgraph *graph_out, const CUgraphNode **dependencies_out, const CUgraphEdgeData **edgeData_out, size_t *numDependencies_out);
    CUresult CUDAAPI cuGraphAddKernelNode(CUgraphNode *phGraphNode, CUgraph hGraph, const CUgraphNode *dependencies, size_t numDependencies, const CUDA_KERNEL_NODE_PARAMS_v1 *nodeParams);
    CUresult CUDAAPI cuGraphKernelNodeGetParams(CUgraphNode hNode, CUDA_KERNEL_NODE_PARAMS_v1 *nodeParams);
    CUresult CUDAAPI cuGraphKernelNodeSetParams(CUgraphNode hNode, const CUDA_KERNEL_NODE_PARAMS_v1 *nodeParams);
    CUresult CUDAAPI cuGraphExecKernelNodeSetParams(CUgraphExec hGraphExec, CUgraphNode hNode, const CUDA_KERNEL_NODE_PARAMS_v1 *nodeParams);
    CUresult CUDAAPI cuGraphInstantiateWithParams(CUgraphExec *phGraphExec, CUgraph hGraph, CUDA_GRAPH_INSTANTIATE_PARAMS *instantiateParams);
    CUresult CUDAAPI cuGraphExecUpdate(CUgraphExec hGraphExec, CUgraph hGraph, CUgraphNode *hErrorNode_out, CUgraphExecUpdateResult *updateResult_out);
    CUresult CUDAAPI cuGraphUpload(CUgraphExec hGraph, CUstream hStream);
    CUresult CUDAAPI cuGraphLaunch(CUgraphExec hGraph, CUstream hStream);
    CUresult CUDAAPI cuStreamCopyAttributes(CUstream dstStream, CUstream srcStream);
    CUresult CUDAAPI cuStreamGetAttribute(CUstream hStream, CUstreamAttrID attr, CUstreamAttrValue *value);
    CUresult CUDAAPI cuStreamSetAttribute(CUstream hStream, CUstreamAttrID attr, const CUstreamAttrValue *param);

    CUresult CUDAAPI cuIpcOpenMemHandle(CUdeviceptr *pdptr, CUipcMemHandle handle, unsigned int Flags);
    CUresult CUDAAPI cuGraphInstantiate(CUgraphExec *phGraphExec, CUgraph hGraph, CUgraphNode *phErrorNode, char *logBuffer, size_t bufferSize);
    CUresult CUDAAPI cuGraphInstantiate_v2(CUgraphExec *phGraphExec, CUgraph hGraph, CUgraphNode *phErrorNode, char *logBuffer, size_t bufferSize);

    CUresult CUDAAPI cuMemMapArrayAsync(CUarrayMapInfo *mapInfoList, unsigned int count, CUstream hStream);

    CUresult CUDAAPI cuMemFreeAsync(CUdeviceptr dptr, CUstream hStream);
    CUresult CUDAAPI cuMemAllocAsync(CUdeviceptr *dptr, size_t bytesize, CUstream hStream);
    CUresult CUDAAPI cuMemAllocFromPoolAsync(CUdeviceptr *dptr, size_t bytesize, CUmemoryPool pool, CUstream hStream);

    CUresult CUDAAPI cuStreamUpdateCaptureDependencies(CUstream hStream, CUgraphNode *dependencies, size_t numDependencies, unsigned int flags);
    CUresult CUDAAPI cuStreamUpdateCaptureDependencies_v2(CUstream hStream, CUgraphNode *dependencies, const CUgraphEdgeData *dependencyData, size_t numDependencies, unsigned int flags);

    CUresult CUDAAPI cuMemBatchDecompressAsync(
        CUmemDecompressParams *paramsArray,
        size_t count,
        unsigned int flags,
        size_t *errorIndex,
        CUstream stream
    );

    CUresult CUDAAPI cuGetProcAddress(const char *symbol, void **pfn, int cudaVersion, cuuint64_t flags);

#elif defined(__CUDA_API_PER_THREAD_DEFAULT_STREAM)
static inline CUresult cuGetProcAddress_v2_ptsz(const char *symbol, void **funcPtr, int driverVersion, cuuint64_t flags, CUdriverProcAddressQueryResult *symbolStatus) {
    const int procAddressMask = (CU_GET_PROC_ADDRESS_LEGACY_STREAM|
                                 CU_GET_PROC_ADDRESS_PER_THREAD_DEFAULT_STREAM);
    if ((flags & procAddressMask) == 0) {
        flags |= CU_GET_PROC_ADDRESS_PER_THREAD_DEFAULT_STREAM;
    }
    return cuGetProcAddress_v2(symbol, funcPtr, driverVersion, flags, symbolStatus); 
}
#define cuGetProcAddress_v2 cuGetProcAddress_v2_ptsz
#endif

/**
 * \defgroup CUDA_CHECKPOINT CUDA Checkpointing
 *
 * ___MANBRIEF___ CUDA checkpoint and restore functionality of the low-level
 * CUDA driver API (___CURRENT_FILE___) ___ENDMANBRIEF___
 *
 * This sections describes the checkpoint and restore functions of the low-level
 * CUDA driver application programming interface.
 *
 * The CUDA checkpoint and restore API's provide a way to save and restore GPU
 * state for full process checkpoints when used with CPU side process
 * checkpointing solutions. They can also be used to pause GPU work and suspend
 * a CUDA process to allow other applications to make use of GPU resources.
 *
 * Checkpoint and restore capabilities are currently restricted to Linux.
 *
 * @{
 */

/**
 * \brief Returns the restore thread ID for a CUDA process
 *
 * Returns in \p *tid the thread ID of the CUDA restore thread for the process
 * specified by \p pid.
 *
 * \param pid - The process ID of the CUDA process
 * \param tid - Returned restore thread ID
 *
 * \return
 * ::CUDA_SUCCESS
 * ::CUDA_ERROR_INVALID_VALUE
 * ::CUDA_ERROR_NOT_INITIALIZED
 * ::CUDA_ERROR_NOT_SUPPORTED
 */
CUresult CUDAAPI cuCheckpointProcessGetRestoreThreadId(int pid, int *tid);

/**
 * \brief Returns the process state of a CUDA process
 *
 * Returns in \p *state the current state of the CUDA process specified by \p pid.
 *
 * \param pid - The process ID of the CUDA process
 * \param state - Returned CUDA process state
 *
 * \return
 * ::CUDA_SUCCESS
 * ::CUDA_ERROR_INVALID_VALUE
 * ::CUDA_ERROR_NOT_INITIALIZED
 * ::CUDA_ERROR_NOT_SUPPORTED
 */
CUresult CUDAAPI cuCheckpointProcessGetState(int pid, CUprocessState *state);

/**
 * \brief Lock a running CUDA process
 *
 * Lock the CUDA process specified by \p pid which will block further CUDA API
 * calls. Process must be in the RUNNING state in order to lock.
 *
 * Upon successful return the process will be in the LOCKED state.
 *
 * If timeoutMs is specified and the timeout is reached the process will be left
 * in the RUNNING state upon return.
 *
 * \param pid - The process ID of the CUDA process
 * \param args - Optional lock operation arguments
 *
 * \return
 * ::CUDA_SUCCESS
 * ::CUDA_ERROR_INVALID_VALUE
 * ::CUDA_ERROR_NOT_INITIALIZED
 * ::CUDA_ERROR_ILLEGAL_STATE
 * ::CUDA_ERROR_NOT_SUPPORTED
 * ::CUDA_ERROR_NOT_READY
 */
CUresult CUDAAPI cuCheckpointProcessLock(int pid, CUcheckpointLockArgs *args);

/**
 * \brief Checkpoint a CUDA process's GPU memory contents
 *
 * Checkpoints a CUDA process specified by \p pid that is in the LOCKED
 * state. The GPU memory contents will be brought into host memory and all
 * underlying references will be released. Process must be in the LOCKED state
 * to checkpoint.
 *
 * Upon successful return the process will be in the CHECKPOINTED state.
 *
 * \param pid - The process ID of the CUDA process
 * \param args - Optional checkpoint operation arguments
 *
 * \return
 * ::CUDA_SUCCESS
 * ::CUDA_ERROR_INVALID_VALUE
 * ::CUDA_ERROR_NOT_INITIALIZED
 * ::CUDA_ERROR_ILLEGAL_STATE
 * ::CUDA_ERROR_NOT_SUPPORTED
 */
CUresult CUDAAPI cuCheckpointProcessCheckpoint(int pid, CUcheckpointCheckpointArgs *args);

/**
 * \brief Restore a CUDA process's GPU memory contents from its last checkpoint
 *
 * Restores a CUDA process specified by \p pid from its last checkpoint. Process
 * must be in the CHECKPOINTED state to restore.
 *
 * Upon successful return the process will be in the LOCKED state.
 *
 * CUDA process restore requires persistence mode to be enabled or ::cuInit to
 * have been called before execution.
 *
 * \param pid - The process ID of the CUDA process
 * \param args - Optional restore operation arguments
 *
 * \return
 * ::CUDA_SUCCESS
 * ::CUDA_ERROR_INVALID_VALUE
 * ::CUDA_ERROR_NOT_INITIALIZED
 * ::CUDA_ERROR_ILLEGAL_STATE
 * ::CUDA_ERROR_NOT_SUPPORTED
 *
 * \sa
 * ::cuInit
 */
CUresult CUDAAPI cuCheckpointProcessRestore(int pid, CUcheckpointRestoreArgs *args);

/**
 * \brief Unlock a CUDA process to allow CUDA API calls
 *
 * Unlocks a process specified by \p pid allowing it to resume making CUDA API
 * calls. Process must be in the LOCKED state.
 *
 * Upon successful return the process will be in the RUNNING state.
 *
 * \param pid - The process ID of the CUDA process
 * \param args - Optional unlock operation arguments
 *
 * \return
 * ::CUDA_SUCCESS
 * ::CUDA_ERROR_INVALID_VALUE
 * ::CUDA_ERROR_NOT_INITIALIZED
 * ::CUDA_ERROR_ILLEGAL_STATE
 * ::CUDA_ERROR_NOT_SUPPORTED
 */
CUresult CUDAAPI cuCheckpointProcessUnlock(int pid, CUcheckpointUnlockArgs *args);

/** @} */ /* End CUDA_CHECKPOINT */

#ifdef __cplusplus
}
#endif

#if defined(__GNUC__)
  #if defined(__CUDA_API_PUSH_VISIBILITY_DEFAULT)
    #pragma GCC visibility pop
  #endif
#endif

#undef __CUDA_DEPRECATED

#endif /* __cuda_cuda_h__ */