mirror of https://github.com/axmolengine/axmol.git
215 lines
7.8 KiB
C
215 lines
7.8 KiB
C
/*
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* jfdctfst-neon.c - fast integer FDCT (Arm Neon)
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*
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* Copyright (C) 2020, Arm Limited. All Rights Reserved.
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*
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* This software is provided 'as-is', without any express or implied
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* warranty. In no event will the authors be held liable for any damages
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* arising from the use of this software.
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*
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* Permission is granted to anyone to use this software for any purpose,
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* including commercial applications, and to alter it and redistribute it
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* freely, subject to the following restrictions:
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*
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* 1. The origin of this software must not be misrepresented; you must not
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* claim that you wrote the original software. If you use this software
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* in a product, an acknowledgment in the product documentation would be
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* appreciated but is not required.
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* 2. Altered source versions must be plainly marked as such, and must not be
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* misrepresented as being the original software.
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* 3. This notice may not be removed or altered from any source distribution.
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*/
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#define JPEG_INTERNALS
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#include "../../jinclude.h"
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#include "../../jpeglib.h"
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#include "../../jsimd.h"
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#include "../../jdct.h"
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#include "../../jsimddct.h"
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#include "../jsimd.h"
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#include "align.h"
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#include <arm_neon.h>
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/* jsimd_fdct_ifast_neon() performs a fast, not so accurate forward DCT
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* (Discrete Cosine Transform) on one block of samples. It uses the same
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* calculations and produces exactly the same output as IJG's original
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* jpeg_fdct_ifast() function, which can be found in jfdctfst.c.
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*
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* Scaled integer constants are used to avoid floating-point arithmetic:
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* 0.382683433 = 12544 * 2^-15
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* 0.541196100 = 17795 * 2^-15
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* 0.707106781 = 23168 * 2^-15
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* 0.306562965 = 9984 * 2^-15
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*
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* See jfdctfst.c for further details of the DCT algorithm. Where possible,
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* the variable names and comments here in jsimd_fdct_ifast_neon() match up
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* with those in jpeg_fdct_ifast().
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*/
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#define F_0_382 12544
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#define F_0_541 17792
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#define F_0_707 23168
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#define F_0_306 9984
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ALIGN(16) static const int16_t jsimd_fdct_ifast_neon_consts[] = {
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F_0_382, F_0_541, F_0_707, F_0_306
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};
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void jsimd_fdct_ifast_neon(DCTELEM *data)
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{
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/* Load an 8x8 block of samples into Neon registers. De-interleaving loads
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* are used, followed by vuzp to transpose the block such that we have a
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* column of samples per vector - allowing all rows to be processed at once.
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*/
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int16x8x4_t data1 = vld4q_s16(data);
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int16x8x4_t data2 = vld4q_s16(data + 4 * DCTSIZE);
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int16x8x2_t cols_04 = vuzpq_s16(data1.val[0], data2.val[0]);
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int16x8x2_t cols_15 = vuzpq_s16(data1.val[1], data2.val[1]);
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int16x8x2_t cols_26 = vuzpq_s16(data1.val[2], data2.val[2]);
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int16x8x2_t cols_37 = vuzpq_s16(data1.val[3], data2.val[3]);
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int16x8_t col0 = cols_04.val[0];
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int16x8_t col1 = cols_15.val[0];
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int16x8_t col2 = cols_26.val[0];
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int16x8_t col3 = cols_37.val[0];
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int16x8_t col4 = cols_04.val[1];
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int16x8_t col5 = cols_15.val[1];
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int16x8_t col6 = cols_26.val[1];
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int16x8_t col7 = cols_37.val[1];
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/* Pass 1: process rows. */
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/* Load DCT conversion constants. */
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const int16x4_t consts = vld1_s16(jsimd_fdct_ifast_neon_consts);
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int16x8_t tmp0 = vaddq_s16(col0, col7);
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int16x8_t tmp7 = vsubq_s16(col0, col7);
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int16x8_t tmp1 = vaddq_s16(col1, col6);
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int16x8_t tmp6 = vsubq_s16(col1, col6);
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int16x8_t tmp2 = vaddq_s16(col2, col5);
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int16x8_t tmp5 = vsubq_s16(col2, col5);
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int16x8_t tmp3 = vaddq_s16(col3, col4);
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int16x8_t tmp4 = vsubq_s16(col3, col4);
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/* Even part */
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int16x8_t tmp10 = vaddq_s16(tmp0, tmp3); /* phase 2 */
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int16x8_t tmp13 = vsubq_s16(tmp0, tmp3);
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int16x8_t tmp11 = vaddq_s16(tmp1, tmp2);
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int16x8_t tmp12 = vsubq_s16(tmp1, tmp2);
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col0 = vaddq_s16(tmp10, tmp11); /* phase 3 */
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col4 = vsubq_s16(tmp10, tmp11);
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int16x8_t z1 = vqdmulhq_lane_s16(vaddq_s16(tmp12, tmp13), consts, 2);
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col2 = vaddq_s16(tmp13, z1); /* phase 5 */
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col6 = vsubq_s16(tmp13, z1);
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/* Odd part */
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tmp10 = vaddq_s16(tmp4, tmp5); /* phase 2 */
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tmp11 = vaddq_s16(tmp5, tmp6);
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tmp12 = vaddq_s16(tmp6, tmp7);
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int16x8_t z5 = vqdmulhq_lane_s16(vsubq_s16(tmp10, tmp12), consts, 0);
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int16x8_t z2 = vqdmulhq_lane_s16(tmp10, consts, 1);
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z2 = vaddq_s16(z2, z5);
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int16x8_t z4 = vqdmulhq_lane_s16(tmp12, consts, 3);
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z5 = vaddq_s16(tmp12, z5);
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z4 = vaddq_s16(z4, z5);
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int16x8_t z3 = vqdmulhq_lane_s16(tmp11, consts, 2);
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int16x8_t z11 = vaddq_s16(tmp7, z3); /* phase 5 */
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int16x8_t z13 = vsubq_s16(tmp7, z3);
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col5 = vaddq_s16(z13, z2); /* phase 6 */
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col3 = vsubq_s16(z13, z2);
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col1 = vaddq_s16(z11, z4);
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col7 = vsubq_s16(z11, z4);
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/* Transpose to work on columns in pass 2. */
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int16x8x2_t cols_01 = vtrnq_s16(col0, col1);
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int16x8x2_t cols_23 = vtrnq_s16(col2, col3);
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int16x8x2_t cols_45 = vtrnq_s16(col4, col5);
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int16x8x2_t cols_67 = vtrnq_s16(col6, col7);
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int32x4x2_t cols_0145_l = vtrnq_s32(vreinterpretq_s32_s16(cols_01.val[0]),
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vreinterpretq_s32_s16(cols_45.val[0]));
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int32x4x2_t cols_0145_h = vtrnq_s32(vreinterpretq_s32_s16(cols_01.val[1]),
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vreinterpretq_s32_s16(cols_45.val[1]));
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int32x4x2_t cols_2367_l = vtrnq_s32(vreinterpretq_s32_s16(cols_23.val[0]),
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vreinterpretq_s32_s16(cols_67.val[0]));
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int32x4x2_t cols_2367_h = vtrnq_s32(vreinterpretq_s32_s16(cols_23.val[1]),
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vreinterpretq_s32_s16(cols_67.val[1]));
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int32x4x2_t rows_04 = vzipq_s32(cols_0145_l.val[0], cols_2367_l.val[0]);
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int32x4x2_t rows_15 = vzipq_s32(cols_0145_h.val[0], cols_2367_h.val[0]);
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int32x4x2_t rows_26 = vzipq_s32(cols_0145_l.val[1], cols_2367_l.val[1]);
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int32x4x2_t rows_37 = vzipq_s32(cols_0145_h.val[1], cols_2367_h.val[1]);
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int16x8_t row0 = vreinterpretq_s16_s32(rows_04.val[0]);
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int16x8_t row1 = vreinterpretq_s16_s32(rows_15.val[0]);
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int16x8_t row2 = vreinterpretq_s16_s32(rows_26.val[0]);
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int16x8_t row3 = vreinterpretq_s16_s32(rows_37.val[0]);
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int16x8_t row4 = vreinterpretq_s16_s32(rows_04.val[1]);
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int16x8_t row5 = vreinterpretq_s16_s32(rows_15.val[1]);
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int16x8_t row6 = vreinterpretq_s16_s32(rows_26.val[1]);
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int16x8_t row7 = vreinterpretq_s16_s32(rows_37.val[1]);
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/* Pass 2: process columns. */
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tmp0 = vaddq_s16(row0, row7);
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tmp7 = vsubq_s16(row0, row7);
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tmp1 = vaddq_s16(row1, row6);
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tmp6 = vsubq_s16(row1, row6);
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tmp2 = vaddq_s16(row2, row5);
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tmp5 = vsubq_s16(row2, row5);
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tmp3 = vaddq_s16(row3, row4);
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tmp4 = vsubq_s16(row3, row4);
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/* Even part */
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tmp10 = vaddq_s16(tmp0, tmp3); /* phase 2 */
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tmp13 = vsubq_s16(tmp0, tmp3);
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tmp11 = vaddq_s16(tmp1, tmp2);
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tmp12 = vsubq_s16(tmp1, tmp2);
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row0 = vaddq_s16(tmp10, tmp11); /* phase 3 */
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row4 = vsubq_s16(tmp10, tmp11);
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z1 = vqdmulhq_lane_s16(vaddq_s16(tmp12, tmp13), consts, 2);
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row2 = vaddq_s16(tmp13, z1); /* phase 5 */
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row6 = vsubq_s16(tmp13, z1);
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/* Odd part */
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tmp10 = vaddq_s16(tmp4, tmp5); /* phase 2 */
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tmp11 = vaddq_s16(tmp5, tmp6);
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tmp12 = vaddq_s16(tmp6, tmp7);
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z5 = vqdmulhq_lane_s16(vsubq_s16(tmp10, tmp12), consts, 0);
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z2 = vqdmulhq_lane_s16(tmp10, consts, 1);
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z2 = vaddq_s16(z2, z5);
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z4 = vqdmulhq_lane_s16(tmp12, consts, 3);
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z5 = vaddq_s16(tmp12, z5);
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z4 = vaddq_s16(z4, z5);
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z3 = vqdmulhq_lane_s16(tmp11, consts, 2);
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z11 = vaddq_s16(tmp7, z3); /* phase 5 */
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z13 = vsubq_s16(tmp7, z3);
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row5 = vaddq_s16(z13, z2); /* phase 6 */
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row3 = vsubq_s16(z13, z2);
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row1 = vaddq_s16(z11, z4);
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row7 = vsubq_s16(z11, z4);
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vst1q_s16(data + 0 * DCTSIZE, row0);
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vst1q_s16(data + 1 * DCTSIZE, row1);
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vst1q_s16(data + 2 * DCTSIZE, row2);
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vst1q_s16(data + 3 * DCTSIZE, row3);
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vst1q_s16(data + 4 * DCTSIZE, row4);
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vst1q_s16(data + 5 * DCTSIZE, row5);
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vst1q_s16(data + 6 * DCTSIZE, row6);
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vst1q_s16(data + 7 * DCTSIZE, row7);
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}
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