image-match/python/opencv/3rdparty/libjpeg-turbo/simd/arm/jfdctfst-neon.c

/*
 * Fast integer FDCT (Arm Neon)
 *
 * Copyright (C) 2020, Arm Limited.  All Rights Reserved.
 * Copyright (C) 2024, D. R. Commander.  All Rights Reserved.
 *
 * This software is provided 'as-is', without any express or implied
 * warranty.  In no event will the authors be held liable for any damages
 * arising from the use of this software.
 *
 * Permission is granted to anyone to use this software for any purpose,
 * including commercial applications, and to alter it and redistribute it
 * freely, subject to the following restrictions:
 *
 * 1. The origin of this software must not be misrepresented; you must not
 *    claim that you wrote the original software. If you use this software
 *    in a product, an acknowledgment in the product documentation would be
 *    appreciated but is not required.
 * 2. Altered source versions must be plainly marked as such, and must not be
 *    misrepresented as being the original software.
 * 3. This notice may not be removed or altered from any source distribution.
 */

#define JPEG_INTERNALS
#include "../../src/jinclude.h"
#include "../../src/jpeglib.h"
#include "../../src/jsimd.h"
#include "../../src/jdct.h"
#include "../../src/jsimddct.h"
#include "../jsimd.h"
#include "align.h"
#include "neon-compat.h"

#include <arm_neon.h>


/* jsimd_fdct_ifast_neon() performs a fast, not so accurate forward DCT
 * (Discrete Cosine Transform) on one block of samples.  It uses the same
 * calculations and produces exactly the same output as IJG's original
 * jpeg_fdct_ifast() function, which can be found in jfdctfst.c.
 *
 * Scaled integer constants are used to avoid floating-point arithmetic:
 *    0.382683433 = 12544 * 2^-15
 *    0.541196100 = 17795 * 2^-15
 *    0.707106781 = 23168 * 2^-15
 *    0.306562965 =  9984 * 2^-15
 *
 * See jfdctfst.c for further details of the DCT algorithm.  Where possible,
 * the variable names and comments here in jsimd_fdct_ifast_neon() match up
 * with those in jpeg_fdct_ifast().
 */

#define F_0_382  12544
#define F_0_541  17792
#define F_0_707  23168
#define F_0_306  9984


ALIGN(16) static const int16_t jsimd_fdct_ifast_neon_consts[] = {
  F_0_382, F_0_541, F_0_707, F_0_306
};

void jsimd_fdct_ifast_neon(DCTELEM *data)
{
  /* Load an 8x8 block of samples into Neon registers.  De-interleaving loads
   * are used, followed by vuzp to transpose the block such that we have a
   * column of samples per vector - allowing all rows to be processed at once.
   */
  int16x8x4_t data1 = vld4q_s16(data);
  int16x8x4_t data2 = vld4q_s16(data + 4 * DCTSIZE);

  int16x8x2_t cols_04 = vuzpq_s16(data1.val[0], data2.val[0]);
  int16x8x2_t cols_15 = vuzpq_s16(data1.val[1], data2.val[1]);
  int16x8x2_t cols_26 = vuzpq_s16(data1.val[2], data2.val[2]);
  int16x8x2_t cols_37 = vuzpq_s16(data1.val[3], data2.val[3]);

  int16x8_t col0 = cols_04.val[0];
  int16x8_t col1 = cols_15.val[0];
  int16x8_t col2 = cols_26.val[0];
  int16x8_t col3 = cols_37.val[0];
  int16x8_t col4 = cols_04.val[1];
  int16x8_t col5 = cols_15.val[1];
  int16x8_t col6 = cols_26.val[1];
  int16x8_t col7 = cols_37.val[1];

  /* Pass 1: process rows. */

  /* Load DCT conversion constants. */
  const int16x4_t consts = vld1_s16(jsimd_fdct_ifast_neon_consts);

  int16x8_t tmp0 = vaddq_s16(col0, col7);
  int16x8_t tmp7 = vsubq_s16(col0, col7);
  int16x8_t tmp1 = vaddq_s16(col1, col6);
  int16x8_t tmp6 = vsubq_s16(col1, col6);
  int16x8_t tmp2 = vaddq_s16(col2, col5);
  int16x8_t tmp5 = vsubq_s16(col2, col5);
  int16x8_t tmp3 = vaddq_s16(col3, col4);
  int16x8_t tmp4 = vsubq_s16(col3, col4);

  /* Even part */
  int16x8_t tmp10 = vaddq_s16(tmp0, tmp3);    /* phase 2 */
  int16x8_t tmp13 = vsubq_s16(tmp0, tmp3);
  int16x8_t tmp11 = vaddq_s16(tmp1, tmp2);
  int16x8_t tmp12 = vsubq_s16(tmp1, tmp2);

  col0 = vaddq_s16(tmp10, tmp11);             /* phase 3 */
  col4 = vsubq_s16(tmp10, tmp11);

  int16x8_t z1 = vqdmulhq_lane_s16(vaddq_s16(tmp12, tmp13), consts, 2);
  col2 = vaddq_s16(tmp13, z1);                /* phase 5 */
  col6 = vsubq_s16(tmp13, z1);

  /* Odd part */
  tmp10 = vaddq_s16(tmp4, tmp5);              /* phase 2 */
  tmp11 = vaddq_s16(tmp5, tmp6);
  tmp12 = vaddq_s16(tmp6, tmp7);

  int16x8_t z5 = vqdmulhq_lane_s16(vsubq_s16(tmp10, tmp12), consts, 0);
  int16x8_t z2 = vqdmulhq_lane_s16(tmp10, consts, 1);
  z2 = vaddq_s16(z2, z5);
  int16x8_t z4 = vqdmulhq_lane_s16(tmp12, consts, 3);
  z5 = vaddq_s16(tmp12, z5);
  z4 = vaddq_s16(z4, z5);
  int16x8_t z3 = vqdmulhq_lane_s16(tmp11, consts, 2);

  int16x8_t z11 = vaddq_s16(tmp7, z3);        /* phase 5 */
  int16x8_t z13 = vsubq_s16(tmp7, z3);

  col5 = vaddq_s16(z13, z2);                  /* phase 6 */
  col3 = vsubq_s16(z13, z2);
  col1 = vaddq_s16(z11, z4);
  col7 = vsubq_s16(z11, z4);

  /* Transpose to work on columns in pass 2. */
  int16x8x2_t cols_01 = vtrnq_s16(col0, col1);
  int16x8x2_t cols_23 = vtrnq_s16(col2, col3);
  int16x8x2_t cols_45 = vtrnq_s16(col4, col5);
  int16x8x2_t cols_67 = vtrnq_s16(col6, col7);

  int32x4x2_t cols_0145_l = vtrnq_s32(vreinterpretq_s32_s16(cols_01.val[0]),
                                      vreinterpretq_s32_s16(cols_45.val[0]));
  int32x4x2_t cols_0145_h = vtrnq_s32(vreinterpretq_s32_s16(cols_01.val[1]),
                                      vreinterpretq_s32_s16(cols_45.val[1]));
  int32x4x2_t cols_2367_l = vtrnq_s32(vreinterpretq_s32_s16(cols_23.val[0]),
                                      vreinterpretq_s32_s16(cols_67.val[0]));
  int32x4x2_t cols_2367_h = vtrnq_s32(vreinterpretq_s32_s16(cols_23.val[1]),
                                      vreinterpretq_s32_s16(cols_67.val[1]));

  int32x4x2_t rows_04 = vzipq_s32(cols_0145_l.val[0], cols_2367_l.val[0]);
  int32x4x2_t rows_15 = vzipq_s32(cols_0145_h.val[0], cols_2367_h.val[0]);
  int32x4x2_t rows_26 = vzipq_s32(cols_0145_l.val[1], cols_2367_l.val[1]);
  int32x4x2_t rows_37 = vzipq_s32(cols_0145_h.val[1], cols_2367_h.val[1]);

  int16x8_t row0 = vreinterpretq_s16_s32(rows_04.val[0]);
  int16x8_t row1 = vreinterpretq_s16_s32(rows_15.val[0]);
  int16x8_t row2 = vreinterpretq_s16_s32(rows_26.val[0]);
  int16x8_t row3 = vreinterpretq_s16_s32(rows_37.val[0]);
  int16x8_t row4 = vreinterpretq_s16_s32(rows_04.val[1]);
  int16x8_t row5 = vreinterpretq_s16_s32(rows_15.val[1]);
  int16x8_t row6 = vreinterpretq_s16_s32(rows_26.val[1]);
  int16x8_t row7 = vreinterpretq_s16_s32(rows_37.val[1]);

  /* Pass 2: process columns. */

  tmp0 = vaddq_s16(row0, row7);
  tmp7 = vsubq_s16(row0, row7);
  tmp1 = vaddq_s16(row1, row6);
  tmp6 = vsubq_s16(row1, row6);
  tmp2 = vaddq_s16(row2, row5);
  tmp5 = vsubq_s16(row2, row5);
  tmp3 = vaddq_s16(row3, row4);
  tmp4 = vsubq_s16(row3, row4);

  /* Even part */
  tmp10 = vaddq_s16(tmp0, tmp3);              /* phase 2 */
  tmp13 = vsubq_s16(tmp0, tmp3);
  tmp11 = vaddq_s16(tmp1, tmp2);
  tmp12 = vsubq_s16(tmp1, tmp2);

  row0 = vaddq_s16(tmp10, tmp11);             /* phase 3 */
  row4 = vsubq_s16(tmp10, tmp11);

  z1 = vqdmulhq_lane_s16(vaddq_s16(tmp12, tmp13), consts, 2);
  row2 = vaddq_s16(tmp13, z1);                /* phase 5 */
  row6 = vsubq_s16(tmp13, z1);

  /* Odd part */
  tmp10 = vaddq_s16(tmp4, tmp5);              /* phase 2 */
  tmp11 = vaddq_s16(tmp5, tmp6);
  tmp12 = vaddq_s16(tmp6, tmp7);

  z5 = vqdmulhq_lane_s16(vsubq_s16(tmp10, tmp12), consts, 0);
  z2 = vqdmulhq_lane_s16(tmp10, consts, 1);
  z2 = vaddq_s16(z2, z5);
  z4 = vqdmulhq_lane_s16(tmp12, consts, 3);
  z5 = vaddq_s16(tmp12, z5);
  z4 = vaddq_s16(z4, z5);
  z3 = vqdmulhq_lane_s16(tmp11, consts, 2);

  z11 = vaddq_s16(tmp7, z3);                  /* phase 5 */
  z13 = vsubq_s16(tmp7, z3);

  row5 = vaddq_s16(z13, z2);                  /* phase 6 */
  row3 = vsubq_s16(z13, z2);
  row1 = vaddq_s16(z11, z4);
  row7 = vsubq_s16(z11, z4);

  vst1q_s16(data + 0 * DCTSIZE, row0);
  vst1q_s16(data + 1 * DCTSIZE, row1);
  vst1q_s16(data + 2 * DCTSIZE, row2);
  vst1q_s16(data + 3 * DCTSIZE, row3);
  vst1q_s16(data + 4 * DCTSIZE, row4);
  vst1q_s16(data + 5 * DCTSIZE, row5);
  vst1q_s16(data + 6 * DCTSIZE, row6);
  vst1q_s16(data + 7 * DCTSIZE, row7);
}