diff options
Diffstat (limited to 'media/libjpeg/simd/arm/jfdctfst-neon.c')
| -rw-r--r-- | media/libjpeg/simd/arm/jfdctfst-neon.c | 214 |
1 files changed, 214 insertions, 0 deletions
diff --git a/media/libjpeg/simd/arm/jfdctfst-neon.c b/media/libjpeg/simd/arm/jfdctfst-neon.c new file mode 100644 index 0000000000..bb371be399 --- /dev/null +++ b/media/libjpeg/simd/arm/jfdctfst-neon.c @@ -0,0 +1,214 @@ +/* + * jfdctfst-neon.c - fast integer FDCT (Arm Neon) + * + * Copyright (C) 2020, Arm Limited. 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 "../../jinclude.h" +#include "../../jpeglib.h" +#include "../../jsimd.h" +#include "../../jdct.h" +#include "../../jsimddct.h" +#include "../jsimd.h" +#include "align.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); +} |