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Diffstat (limited to '')
| -rw-r--r-- | third_party/aom/av1/encoder/arm/neon/highbd_pickrst_neon.c | 1207 |
1 files changed, 1207 insertions, 0 deletions
diff --git a/third_party/aom/av1/encoder/arm/neon/highbd_pickrst_neon.c b/third_party/aom/av1/encoder/arm/neon/highbd_pickrst_neon.c new file mode 100644 index 0000000000..47b5f5cfb7 --- /dev/null +++ b/third_party/aom/av1/encoder/arm/neon/highbd_pickrst_neon.c @@ -0,0 +1,1207 @@ +/* + * Copyright (c) 2023, Alliance for Open Media. All rights reserved + * + * This source code is subject to the terms of the BSD 2 Clause License and + * the Alliance for Open Media Patent License 1.0. If the BSD 2 Clause License + * was not distributed with this source code in the LICENSE file, you can + * obtain it at www.aomedia.org/license/software. If the Alliance for Open + * Media Patent License 1.0 was not distributed with this source code in the + * PATENTS file, you can obtain it at www.aomedia.org/license/patent. + */ + +#include <arm_neon.h> +#include <assert.h> +#include <stdint.h> + +#include "aom_dsp/arm/mem_neon.h" +#include "aom_dsp/arm/sum_neon.h" +#include "av1/encoder/arm/neon/pickrst_neon.h" +#include "av1/encoder/pickrst.h" + +static INLINE void highbd_calc_proj_params_r0_r1_neon( + const uint8_t *src8, int width, int height, int src_stride, + const uint8_t *dat8, int dat_stride, int32_t *flt0, int flt0_stride, + int32_t *flt1, int flt1_stride, int64_t H[2][2], int64_t C[2]) { + assert(width % 8 == 0); + const int size = width * height; + const uint16_t *src = CONVERT_TO_SHORTPTR(src8); + const uint16_t *dat = CONVERT_TO_SHORTPTR(dat8); + + int64x2_t h00_lo = vdupq_n_s64(0); + int64x2_t h00_hi = vdupq_n_s64(0); + int64x2_t h11_lo = vdupq_n_s64(0); + int64x2_t h11_hi = vdupq_n_s64(0); + int64x2_t h01_lo = vdupq_n_s64(0); + int64x2_t h01_hi = vdupq_n_s64(0); + int64x2_t c0_lo = vdupq_n_s64(0); + int64x2_t c0_hi = vdupq_n_s64(0); + int64x2_t c1_lo = vdupq_n_s64(0); + int64x2_t c1_hi = vdupq_n_s64(0); + + do { + const uint16_t *src_ptr = src; + const uint16_t *dat_ptr = dat; + int32_t *flt0_ptr = flt0; + int32_t *flt1_ptr = flt1; + int w = width; + + do { + uint16x8_t s = vld1q_u16(src_ptr); + uint16x8_t d = vld1q_u16(dat_ptr); + int32x4_t f0_lo = vld1q_s32(flt0_ptr); + int32x4_t f0_hi = vld1q_s32(flt0_ptr + 4); + int32x4_t f1_lo = vld1q_s32(flt1_ptr); + int32x4_t f1_hi = vld1q_s32(flt1_ptr + 4); + + int32x4_t u_lo = + vreinterpretq_s32_u32(vshll_n_u16(vget_low_u16(d), SGRPROJ_RST_BITS)); + int32x4_t u_hi = vreinterpretq_s32_u32( + vshll_n_u16(vget_high_u16(d), SGRPROJ_RST_BITS)); + int32x4_t s_lo = + vreinterpretq_s32_u32(vshll_n_u16(vget_low_u16(s), SGRPROJ_RST_BITS)); + int32x4_t s_hi = vreinterpretq_s32_u32( + vshll_n_u16(vget_high_u16(s), SGRPROJ_RST_BITS)); + s_lo = vsubq_s32(s_lo, u_lo); + s_hi = vsubq_s32(s_hi, u_hi); + + f0_lo = vsubq_s32(f0_lo, u_lo); + f0_hi = vsubq_s32(f0_hi, u_hi); + f1_lo = vsubq_s32(f1_lo, u_lo); + f1_hi = vsubq_s32(f1_hi, u_hi); + + h00_lo = vmlal_s32(h00_lo, vget_low_s32(f0_lo), vget_low_s32(f0_lo)); + h00_lo = vmlal_s32(h00_lo, vget_high_s32(f0_lo), vget_high_s32(f0_lo)); + h00_hi = vmlal_s32(h00_hi, vget_low_s32(f0_hi), vget_low_s32(f0_hi)); + h00_hi = vmlal_s32(h00_hi, vget_high_s32(f0_hi), vget_high_s32(f0_hi)); + + h11_lo = vmlal_s32(h11_lo, vget_low_s32(f1_lo), vget_low_s32(f1_lo)); + h11_lo = vmlal_s32(h11_lo, vget_high_s32(f1_lo), vget_high_s32(f1_lo)); + h11_hi = vmlal_s32(h11_hi, vget_low_s32(f1_hi), vget_low_s32(f1_hi)); + h11_hi = vmlal_s32(h11_hi, vget_high_s32(f1_hi), vget_high_s32(f1_hi)); + + h01_lo = vmlal_s32(h01_lo, vget_low_s32(f0_lo), vget_low_s32(f1_lo)); + h01_lo = vmlal_s32(h01_lo, vget_high_s32(f0_lo), vget_high_s32(f1_lo)); + h01_hi = vmlal_s32(h01_hi, vget_low_s32(f0_hi), vget_low_s32(f1_hi)); + h01_hi = vmlal_s32(h01_hi, vget_high_s32(f0_hi), vget_high_s32(f1_hi)); + + c0_lo = vmlal_s32(c0_lo, vget_low_s32(f0_lo), vget_low_s32(s_lo)); + c0_lo = vmlal_s32(c0_lo, vget_high_s32(f0_lo), vget_high_s32(s_lo)); + c0_hi = vmlal_s32(c0_hi, vget_low_s32(f0_hi), vget_low_s32(s_hi)); + c0_hi = vmlal_s32(c0_hi, vget_high_s32(f0_hi), vget_high_s32(s_hi)); + + c1_lo = vmlal_s32(c1_lo, vget_low_s32(f1_lo), vget_low_s32(s_lo)); + c1_lo = vmlal_s32(c1_lo, vget_high_s32(f1_lo), vget_high_s32(s_lo)); + c1_hi = vmlal_s32(c1_hi, vget_low_s32(f1_hi), vget_low_s32(s_hi)); + c1_hi = vmlal_s32(c1_hi, vget_high_s32(f1_hi), vget_high_s32(s_hi)); + + src_ptr += 8; + dat_ptr += 8; + flt0_ptr += 8; + flt1_ptr += 8; + w -= 8; + } while (w != 0); + + src += src_stride; + dat += dat_stride; + flt0 += flt0_stride; + flt1 += flt1_stride; + } while (--height != 0); + + H[0][0] = horizontal_add_s64x2(vaddq_s64(h00_lo, h00_hi)) / size; + H[0][1] = horizontal_add_s64x2(vaddq_s64(h01_lo, h01_hi)) / size; + H[1][1] = horizontal_add_s64x2(vaddq_s64(h11_lo, h11_hi)) / size; + H[1][0] = H[0][1]; + C[0] = horizontal_add_s64x2(vaddq_s64(c0_lo, c0_hi)) / size; + C[1] = horizontal_add_s64x2(vaddq_s64(c1_lo, c1_hi)) / size; +} + +static INLINE void highbd_calc_proj_params_r0_neon( + const uint8_t *src8, int width, int height, int src_stride, + const uint8_t *dat8, int dat_stride, int32_t *flt0, int flt0_stride, + int64_t H[2][2], int64_t C[2]) { + assert(width % 8 == 0); + const int size = width * height; + const uint16_t *src = CONVERT_TO_SHORTPTR(src8); + const uint16_t *dat = CONVERT_TO_SHORTPTR(dat8); + + int64x2_t h00_lo = vdupq_n_s64(0); + int64x2_t h00_hi = vdupq_n_s64(0); + int64x2_t c0_lo = vdupq_n_s64(0); + int64x2_t c0_hi = vdupq_n_s64(0); + + do { + const uint16_t *src_ptr = src; + const uint16_t *dat_ptr = dat; + int32_t *flt0_ptr = flt0; + int w = width; + + do { + uint16x8_t s = vld1q_u16(src_ptr); + uint16x8_t d = vld1q_u16(dat_ptr); + int32x4_t f0_lo = vld1q_s32(flt0_ptr); + int32x4_t f0_hi = vld1q_s32(flt0_ptr + 4); + + int32x4_t u_lo = + vreinterpretq_s32_u32(vshll_n_u16(vget_low_u16(d), SGRPROJ_RST_BITS)); + int32x4_t u_hi = vreinterpretq_s32_u32( + vshll_n_u16(vget_high_u16(d), SGRPROJ_RST_BITS)); + int32x4_t s_lo = + vreinterpretq_s32_u32(vshll_n_u16(vget_low_u16(s), SGRPROJ_RST_BITS)); + int32x4_t s_hi = vreinterpretq_s32_u32( + vshll_n_u16(vget_high_u16(s), SGRPROJ_RST_BITS)); + s_lo = vsubq_s32(s_lo, u_lo); + s_hi = vsubq_s32(s_hi, u_hi); + + f0_lo = vsubq_s32(f0_lo, u_lo); + f0_hi = vsubq_s32(f0_hi, u_hi); + + h00_lo = vmlal_s32(h00_lo, vget_low_s32(f0_lo), vget_low_s32(f0_lo)); + h00_lo = vmlal_s32(h00_lo, vget_high_s32(f0_lo), vget_high_s32(f0_lo)); + h00_hi = vmlal_s32(h00_hi, vget_low_s32(f0_hi), vget_low_s32(f0_hi)); + h00_hi = vmlal_s32(h00_hi, vget_high_s32(f0_hi), vget_high_s32(f0_hi)); + + c0_lo = vmlal_s32(c0_lo, vget_low_s32(f0_lo), vget_low_s32(s_lo)); + c0_lo = vmlal_s32(c0_lo, vget_high_s32(f0_lo), vget_high_s32(s_lo)); + c0_hi = vmlal_s32(c0_hi, vget_low_s32(f0_hi), vget_low_s32(s_hi)); + c0_hi = vmlal_s32(c0_hi, vget_high_s32(f0_hi), vget_high_s32(s_hi)); + + src_ptr += 8; + dat_ptr += 8; + flt0_ptr += 8; + w -= 8; + } while (w != 0); + + src += src_stride; + dat += dat_stride; + flt0 += flt0_stride; + } while (--height != 0); + + H[0][0] = horizontal_add_s64x2(vaddq_s64(h00_lo, h00_hi)) / size; + C[0] = horizontal_add_s64x2(vaddq_s64(c0_lo, c0_hi)) / size; +} + +static INLINE void highbd_calc_proj_params_r1_neon( + const uint8_t *src8, int width, int height, int src_stride, + const uint8_t *dat8, int dat_stride, int32_t *flt1, int flt1_stride, + int64_t H[2][2], int64_t C[2]) { + assert(width % 8 == 0); + const int size = width * height; + const uint16_t *src = CONVERT_TO_SHORTPTR(src8); + const uint16_t *dat = CONVERT_TO_SHORTPTR(dat8); + + int64x2_t h11_lo = vdupq_n_s64(0); + int64x2_t h11_hi = vdupq_n_s64(0); + int64x2_t c1_lo = vdupq_n_s64(0); + int64x2_t c1_hi = vdupq_n_s64(0); + + do { + const uint16_t *src_ptr = src; + const uint16_t *dat_ptr = dat; + int32_t *flt1_ptr = flt1; + int w = width; + + do { + uint16x8_t s = vld1q_u16(src_ptr); + uint16x8_t d = vld1q_u16(dat_ptr); + int32x4_t f1_lo = vld1q_s32(flt1_ptr); + int32x4_t f1_hi = vld1q_s32(flt1_ptr + 4); + + int32x4_t u_lo = + vreinterpretq_s32_u32(vshll_n_u16(vget_low_u16(d), SGRPROJ_RST_BITS)); + int32x4_t u_hi = vreinterpretq_s32_u32( + vshll_n_u16(vget_high_u16(d), SGRPROJ_RST_BITS)); + int32x4_t s_lo = + vreinterpretq_s32_u32(vshll_n_u16(vget_low_u16(s), SGRPROJ_RST_BITS)); + int32x4_t s_hi = vreinterpretq_s32_u32( + vshll_n_u16(vget_high_u16(s), SGRPROJ_RST_BITS)); + s_lo = vsubq_s32(s_lo, u_lo); + s_hi = vsubq_s32(s_hi, u_hi); + + f1_lo = vsubq_s32(f1_lo, u_lo); + f1_hi = vsubq_s32(f1_hi, u_hi); + + h11_lo = vmlal_s32(h11_lo, vget_low_s32(f1_lo), vget_low_s32(f1_lo)); + h11_lo = vmlal_s32(h11_lo, vget_high_s32(f1_lo), vget_high_s32(f1_lo)); + h11_hi = vmlal_s32(h11_hi, vget_low_s32(f1_hi), vget_low_s32(f1_hi)); + h11_hi = vmlal_s32(h11_hi, vget_high_s32(f1_hi), vget_high_s32(f1_hi)); + + c1_lo = vmlal_s32(c1_lo, vget_low_s32(f1_lo), vget_low_s32(s_lo)); + c1_lo = vmlal_s32(c1_lo, vget_high_s32(f1_lo), vget_high_s32(s_lo)); + c1_hi = vmlal_s32(c1_hi, vget_low_s32(f1_hi), vget_low_s32(s_hi)); + c1_hi = vmlal_s32(c1_hi, vget_high_s32(f1_hi), vget_high_s32(s_hi)); + + src_ptr += 8; + dat_ptr += 8; + flt1_ptr += 8; + w -= 8; + } while (w != 0); + + src += src_stride; + dat += dat_stride; + flt1 += flt1_stride; + } while (--height != 0); + + H[1][1] = horizontal_add_s64x2(vaddq_s64(h11_lo, h11_hi)) / size; + C[1] = horizontal_add_s64x2(vaddq_s64(c1_lo, c1_hi)) / size; +} + +// The function calls 3 subfunctions for the following cases : +// 1) When params->r[0] > 0 and params->r[1] > 0. In this case all elements +// of C and H need to be computed. +// 2) When only params->r[0] > 0. In this case only H[0][0] and C[0] are +// non-zero and need to be computed. +// 3) When only params->r[1] > 0. In this case only H[1][1] and C[1] are +// non-zero and need to be computed. +void av1_calc_proj_params_high_bd_neon(const uint8_t *src8, int width, + int height, int src_stride, + const uint8_t *dat8, int dat_stride, + int32_t *flt0, int flt0_stride, + int32_t *flt1, int flt1_stride, + int64_t H[2][2], int64_t C[2], + const sgr_params_type *params) { + if ((params->r[0] > 0) && (params->r[1] > 0)) { + highbd_calc_proj_params_r0_r1_neon(src8, width, height, src_stride, dat8, + dat_stride, flt0, flt0_stride, flt1, + flt1_stride, H, C); + } else if (params->r[0] > 0) { + highbd_calc_proj_params_r0_neon(src8, width, height, src_stride, dat8, + dat_stride, flt0, flt0_stride, H, C); + } else if (params->r[1] > 0) { + highbd_calc_proj_params_r1_neon(src8, width, height, src_stride, dat8, + dat_stride, flt1, flt1_stride, H, C); + } +} + +static INLINE int16x8_t tbl2q(int16x8_t a, int16x8_t b, uint8x16_t idx) { +#if AOM_ARCH_AARCH64 + uint8x16x2_t table = { { vreinterpretq_u8_s16(a), vreinterpretq_u8_s16(b) } }; + return vreinterpretq_s16_u8(vqtbl2q_u8(table, idx)); +#else + uint8x8x4_t table = { { vreinterpret_u8_s16(vget_low_s16(a)), + vreinterpret_u8_s16(vget_high_s16(a)), + vreinterpret_u8_s16(vget_low_s16(b)), + vreinterpret_u8_s16(vget_high_s16(b)) } }; + return vreinterpretq_s16_u8(vcombine_u8(vtbl4_u8(table, vget_low_u8(idx)), + vtbl4_u8(table, vget_high_u8(idx)))); +#endif +} + +static INLINE int16x8_t tbl3q(int16x8_t a, int16x8_t b, int16x8_t c, + uint8x16_t idx) { +#if AOM_ARCH_AARCH64 + uint8x16x3_t table = { { vreinterpretq_u8_s16(a), vreinterpretq_u8_s16(b), + vreinterpretq_u8_s16(c) } }; + return vreinterpretq_s16_u8(vqtbl3q_u8(table, idx)); +#else + // This is a specific implementation working only for compute stats with + // wiener_win == 5. + uint8x8x3_t table_lo = { { vreinterpret_u8_s16(vget_low_s16(a)), + vreinterpret_u8_s16(vget_high_s16(a)), + vreinterpret_u8_s16(vget_low_s16(b)) } }; + uint8x8x3_t table_hi = { { vreinterpret_u8_s16(vget_low_s16(b)), + vreinterpret_u8_s16(vget_high_s16(b)), + vreinterpret_u8_s16(vget_low_s16(c)) } }; + return vreinterpretq_s16_u8(vcombine_u8( + vtbl3_u8(table_lo, vget_low_u8(idx)), + vtbl3_u8(table_hi, vsub_u8(vget_high_u8(idx), vdup_n_u8(16))))); +#endif +} + +static INLINE int64_t div_shift_s64(int64_t x, int power) { + return (x < 0 ? x + (1ll << power) - 1 : x) >> power; +} + +// The M matrix is accumulated in a bitdepth-dependent number of steps to +// speed up the computation. This function computes the final M from the +// accumulated (src_s64) and the residual parts (src_s32). It also transposes +// the result as the output needs to be column-major. +static INLINE void acc_transpose_M(int64_t *dst, const int64_t *src_s64, + const int32_t *src_s32, const int wiener_win, + int shift) { + for (int i = 0; i < wiener_win; ++i) { + for (int j = 0; j < wiener_win; ++j) { + int tr_idx = j * wiener_win + i; + *dst++ = div_shift_s64(src_s64[tr_idx] + src_s32[tr_idx], shift); + } + } +} + +// The resulting H is a column-major matrix accumulated from the transposed +// (column-major) samples of the filter kernel (5x5 or 7x7) viewed as a single +// vector. For the 7x7 filter case: H(49x49) = [49 x 1] x [1 x 49]. This +// function transforms back to the originally expected format (double +// transpose). The H matrix is accumulated in a bitdepth-dependent number of +// steps to speed up the computation. This function computes the final H from +// the accumulated (src_s64) and the residual parts (src_s32). The computed H is +// only an upper triangle matrix, this function also fills the lower triangle of +// the resulting matrix. +static INLINE void update_H(int64_t *dst, const int64_t *src_s64, + const int32_t *src_s32, const int wiener_win, + int stride, int shift) { + // For a simplified theoretical 3x3 case where `wiener_win` is 3 and + // `wiener_win2` is 9, the M matrix is 3x3: + // 0, 3, 6 + // 1, 4, 7 + // 2, 5, 8 + // + // This is viewed as a vector to compute H (9x9) by vector outer product: + // 0, 3, 6, 1, 4, 7, 2, 5, 8 + // + // Double transpose and upper triangle remapping for 3x3 -> 9x9 case: + // 0, 3, 6, 1, 4, 7, 2, 5, 8, + // 3, 30, 33, 12, 31, 34, 21, 32, 35, + // 6, 33, 60, 15, 42, 61, 24, 51, 62, + // 1, 12, 15, 10, 13, 16, 11, 14, 17, + // 4, 31, 42, 13, 40, 43, 22, 41, 44, + // 7, 34, 61, 16, 43, 70, 25, 52, 71, + // 2, 21, 24, 11, 22, 25, 20, 23, 26, + // 5, 32, 51, 14, 41, 52, 23, 50, 53, + // 8, 35, 62, 17, 44, 71, 26, 53, 80, + const int wiener_win2 = wiener_win * wiener_win; + + // Loop through the indices according to the remapping above, along the + // columns: + // 0, wiener_win, 2 * wiener_win, ..., 1, 1 + 2 * wiener_win, ..., + // wiener_win - 1, wiener_win - 1 + wiener_win, ... + // For the 3x3 case `j` will be: 0, 3, 6, 1, 4, 7, 2, 5, 8. + for (int i = 0; i < wiener_win; ++i) { + for (int j = i; j < wiener_win2; j += wiener_win) { + // These two inner loops are the same as the two outer loops, but running + // along rows instead of columns. For the 3x3 case `l` will be: + // 0, 3, 6, 1, 4, 7, 2, 5, 8. + for (int k = 0; k < wiener_win; ++k) { + for (int l = k; l < wiener_win2; l += wiener_win) { + // The nominal double transpose indexing would be: + // int idx = stride * j + l; + // However we need the upper-right triangle, it is easy with some + // min/max operations. + int tr_idx = stride * AOMMIN(j, l) + AOMMAX(j, l); + + // Resulting matrix is filled by combining the 64-bit and the residual + // 32-bit matrices together with scaling. + *dst++ = div_shift_s64(src_s64[tr_idx] + src_s32[tr_idx], shift); + } + } + } + } +} + +// Load 7x7 matrix into 7 128-bit vectors from consecutive rows, the last load +// address is offset to prevent out-of-bounds access. +static INLINE void load_and_pack_s16_8x7(int16x8_t dst[7], const int16_t *src, + ptrdiff_t stride) { + dst[0] = vld1q_s16(src); + src += stride; + dst[1] = vld1q_s16(src); + src += stride; + dst[2] = vld1q_s16(src); + src += stride; + dst[3] = vld1q_s16(src); + src += stride; + dst[4] = vld1q_s16(src); + src += stride; + dst[5] = vld1q_s16(src); + src += stride; + dst[6] = vld1q_s16(src - 1); +} + +static INLINE void highbd_compute_stats_win7_neon( + const uint16_t *dgd, const uint16_t *src, int avg, int width, int height, + int dgd_stride, int src_stride, int64_t *M, int64_t *H, + aom_bit_depth_t bit_depth) { + // Matrix names are capitalized to help readability. + DECLARE_ALIGNED(64, int16_t, DGD_AVG0[WIENER_WIN2_ALIGN3]); + DECLARE_ALIGNED(64, int16_t, DGD_AVG1[WIENER_WIN2_ALIGN3]); + DECLARE_ALIGNED(64, int32_t, M_s32[WIENER_WIN2_ALIGN3]); + DECLARE_ALIGNED(64, int64_t, M_s64[WIENER_WIN2_ALIGN3]); + DECLARE_ALIGNED(64, int32_t, H_s32[WIENER_WIN2 * WIENER_WIN2_ALIGN2]); + DECLARE_ALIGNED(64, int64_t, H_s64[WIENER_WIN2 * WIENER_WIN2_ALIGN2]); + + memset(M_s32, 0, sizeof(M_s32)); + memset(M_s64, 0, sizeof(M_s64)); + memset(H_s32, 0, sizeof(H_s32)); + memset(H_s64, 0, sizeof(H_s64)); + + // Look-up tables to create 8x6 matrix with consecutive elements from two 7x7 + // matrices. + // clang-format off + DECLARE_ALIGNED(16, static const uint8_t, shuffle_stats7_highbd[192]) = { + 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 16, 17, + 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 16, 17, 18, 19, + 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 16, 17, 18, 19, 20, 21, + 6, 7, 8, 9, 10, 11, 12, 13, 16, 17, 18, 19, 20, 21, 22, 23, + 8, 9, 10, 11, 12, 13, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, + 10, 11, 12, 13, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, + 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 18, 19, + 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 18, 19, 20, 21, + 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 18, 19, 20, 21, 22, 23, + 8, 9, 10, 11, 12, 13, 14, 15, 18, 19, 20, 21, 22, 23, 24, 25, + 10, 11, 12, 13, 14, 15, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, + 12, 13, 14, 15, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, + }; + // clang-format on + + const uint8x16_t lut0 = vld1q_u8(shuffle_stats7_highbd + 0); + const uint8x16_t lut1 = vld1q_u8(shuffle_stats7_highbd + 16); + const uint8x16_t lut2 = vld1q_u8(shuffle_stats7_highbd + 32); + const uint8x16_t lut3 = vld1q_u8(shuffle_stats7_highbd + 48); + const uint8x16_t lut4 = vld1q_u8(shuffle_stats7_highbd + 64); + const uint8x16_t lut5 = vld1q_u8(shuffle_stats7_highbd + 80); + const uint8x16_t lut6 = vld1q_u8(shuffle_stats7_highbd + 96); + const uint8x16_t lut7 = vld1q_u8(shuffle_stats7_highbd + 112); + const uint8x16_t lut8 = vld1q_u8(shuffle_stats7_highbd + 128); + const uint8x16_t lut9 = vld1q_u8(shuffle_stats7_highbd + 144); + const uint8x16_t lut10 = vld1q_u8(shuffle_stats7_highbd + 160); + const uint8x16_t lut11 = vld1q_u8(shuffle_stats7_highbd + 176); + + // We can accumulate up to 65536/4096/256 8/10/12-bit multiplication results + // in 32-bit. We are processing 2 pixels at a time, so the accumulator max can + // be as high as 32768/2048/128 for the compute stats. + const int acc_cnt_max = (1 << (32 - 2 * bit_depth)) >> 1; + int acc_cnt = acc_cnt_max; + const int src_next = src_stride - width; + const int dgd_next = dgd_stride - width; + const int16x8_t avg_s16 = vdupq_n_s16(avg); + + do { + int j = width; + while (j >= 2) { + // Load two adjacent, overlapping 7x7 matrices: a 8x7 matrix with the + // middle 6x7 elements being shared. + int16x8_t dgd_rows[7]; + load_and_pack_s16_8x7(dgd_rows, (const int16_t *)dgd, dgd_stride); + + const int16_t *dgd_ptr = (const int16_t *)dgd + dgd_stride * 6; + dgd += 2; + + dgd_rows[0] = vsubq_s16(dgd_rows[0], avg_s16); + dgd_rows[1] = vsubq_s16(dgd_rows[1], avg_s16); + dgd_rows[2] = vsubq_s16(dgd_rows[2], avg_s16); + dgd_rows[3] = vsubq_s16(dgd_rows[3], avg_s16); + dgd_rows[4] = vsubq_s16(dgd_rows[4], avg_s16); + dgd_rows[5] = vsubq_s16(dgd_rows[5], avg_s16); + dgd_rows[6] = vsubq_s16(dgd_rows[6], avg_s16); + + // Re-arrange the combined 8x7 matrix to have the 2 whole 7x7 matrices (1 + // for each of the 2 pixels) separated into distinct int16x8_t[6] arrays. + // These arrays contain 48 elements of the 49 (7x7). Compute `dgd - avg` + // for both buffers. Each DGD_AVG buffer contains 49 consecutive elements. + int16x8_t dgd_avg0[6]; + int16x8_t dgd_avg1[6]; + + dgd_avg0[0] = tbl2q(dgd_rows[0], dgd_rows[1], lut0); + dgd_avg1[0] = tbl2q(dgd_rows[0], dgd_rows[1], lut6); + dgd_avg0[1] = tbl2q(dgd_rows[1], dgd_rows[2], lut1); + dgd_avg1[1] = tbl2q(dgd_rows[1], dgd_rows[2], lut7); + dgd_avg0[2] = tbl2q(dgd_rows[2], dgd_rows[3], lut2); + dgd_avg1[2] = tbl2q(dgd_rows[2], dgd_rows[3], lut8); + dgd_avg0[3] = tbl2q(dgd_rows[3], dgd_rows[4], lut3); + dgd_avg1[3] = tbl2q(dgd_rows[3], dgd_rows[4], lut9); + dgd_avg0[4] = tbl2q(dgd_rows[4], dgd_rows[5], lut4); + dgd_avg1[4] = tbl2q(dgd_rows[4], dgd_rows[5], lut10); + dgd_avg0[5] = tbl2q(dgd_rows[5], dgd_rows[6], lut5); + dgd_avg1[5] = tbl2q(dgd_rows[5], dgd_rows[6], lut11); + + vst1q_s16(DGD_AVG0, dgd_avg0[0]); + vst1q_s16(DGD_AVG1, dgd_avg1[0]); + vst1q_s16(DGD_AVG0 + 8, dgd_avg0[1]); + vst1q_s16(DGD_AVG1 + 8, dgd_avg1[1]); + vst1q_s16(DGD_AVG0 + 16, dgd_avg0[2]); + vst1q_s16(DGD_AVG1 + 16, dgd_avg1[2]); + vst1q_s16(DGD_AVG0 + 24, dgd_avg0[3]); + vst1q_s16(DGD_AVG1 + 24, dgd_avg1[3]); + vst1q_s16(DGD_AVG0 + 32, dgd_avg0[4]); + vst1q_s16(DGD_AVG1 + 32, dgd_avg1[4]); + vst1q_s16(DGD_AVG0 + 40, dgd_avg0[5]); + vst1q_s16(DGD_AVG1 + 40, dgd_avg1[5]); + + // The remaining last (49th) elements of `dgd - avg`. + DGD_AVG0[48] = dgd_ptr[6] - avg; + DGD_AVG1[48] = dgd_ptr[7] - avg; + + // Accumulate into row-major variant of matrix M (cross-correlation) for 2 + // output pixels at a time. M is of size 7 * 7. It needs to be filled such + // that multiplying one element from src with each element of a row of the + // wiener window will fill one column of M. However this is not very + // convenient in terms of memory access, as it means we do contiguous + // loads of dgd but strided stores to M. As a result, we use an + // intermediate matrix M_s32 which is instead filled such that one row of + // the wiener window gives one row of M_s32. Once fully computed, M_s32 is + // then transposed to return M. + int src_avg0 = *src++ - avg; + int src_avg1 = *src++ - avg; + int16x4_t src_avg0_s16 = vdup_n_s16(src_avg0); + int16x4_t src_avg1_s16 = vdup_n_s16(src_avg1); + update_M_2pixels(M_s32 + 0, src_avg0_s16, src_avg1_s16, dgd_avg0[0], + dgd_avg1[0]); + update_M_2pixels(M_s32 + 8, src_avg0_s16, src_avg1_s16, dgd_avg0[1], + dgd_avg1[1]); + update_M_2pixels(M_s32 + 16, src_avg0_s16, src_avg1_s16, dgd_avg0[2], + dgd_avg1[2]); + update_M_2pixels(M_s32 + 24, src_avg0_s16, src_avg1_s16, dgd_avg0[3], + dgd_avg1[3]); + update_M_2pixels(M_s32 + 32, src_avg0_s16, src_avg1_s16, dgd_avg0[4], + dgd_avg1[4]); + update_M_2pixels(M_s32 + 40, src_avg0_s16, src_avg1_s16, dgd_avg0[5], + dgd_avg1[5]); + + // Last (49th) element of M_s32 can be computed as scalar more efficiently + // for 2 output pixels. + M_s32[48] += DGD_AVG0[48] * src_avg0 + DGD_AVG1[48] * src_avg1; + + // Start accumulating into row-major version of matrix H + // (auto-covariance), it expects the DGD_AVG[01] matrices to also be + // row-major. H is of size 49 * 49. It is filled by multiplying every pair + // of elements of the wiener window together (vector outer product). Since + // it is a symmetric matrix, we only compute the upper-right triangle, and + // then copy it down to the lower-left later. The upper triangle is + // covered by 4x4 tiles. The original algorithm assumes the M matrix is + // column-major and the resulting H matrix is also expected to be + // column-major. It is not efficient to work with column-major matrices, + // so we accumulate into a row-major matrix H_s32. At the end of the + // algorithm a double transpose transformation will convert H_s32 back to + // the expected output layout. + update_H_7x7_2pixels(H_s32, DGD_AVG0, DGD_AVG1); + + // The last element of the triangle of H_s32 matrix can be computed as a + // scalar more efficiently. + H_s32[48 * WIENER_WIN2_ALIGN2 + 48] += + DGD_AVG0[48] * DGD_AVG0[48] + DGD_AVG1[48] * DGD_AVG1[48]; + + // Accumulate into 64-bit after a bit depth dependent number of iterations + // to prevent overflow. + if (--acc_cnt == 0) { + acc_cnt = acc_cnt_max; + + accumulate_and_clear(M_s64, M_s32, WIENER_WIN2_ALIGN2); + + // The widening accumulation is only needed for the upper triangle part + // of the matrix. + int64_t *lh = H_s64; + int32_t *lh32 = H_s32; + for (int k = 0; k < WIENER_WIN2; ++k) { + // The widening accumulation is only run for the relevant parts + // (upper-right triangle) in a row 4-element aligned. + int k4 = k / 4 * 4; + accumulate_and_clear(lh + k4, lh32 + k4, 48 - k4); + + // Last element of the row is computed separately. + lh[48] += lh32[48]; + lh32[48] = 0; + + lh += WIENER_WIN2_ALIGN2; + lh32 += WIENER_WIN2_ALIGN2; + } + } + + j -= 2; + } + + // Computations for odd pixel in the row. + if (width & 1) { + // Load two adjacent, overlapping 7x7 matrices: a 8x7 matrix with the + // middle 6x7 elements being shared. + int16x8_t dgd_rows[7]; + load_and_pack_s16_8x7(dgd_rows, (const int16_t *)dgd, dgd_stride); + + const int16_t *dgd_ptr = (const int16_t *)dgd + dgd_stride * 6; + ++dgd; + + // Re-arrange the combined 8x7 matrix to have a whole 7x7 matrix tightly + // packed into a int16x8_t[6] array. This array contains 48 elements of + // the 49 (7x7). Compute `dgd - avg` for the whole buffer. The DGD_AVG + // buffer contains 49 consecutive elements. + int16x8_t dgd_avg0[6]; + + dgd_avg0[0] = vsubq_s16(tbl2q(dgd_rows[0], dgd_rows[1], lut0), avg_s16); + dgd_avg0[1] = vsubq_s16(tbl2q(dgd_rows[1], dgd_rows[2], lut1), avg_s16); + dgd_avg0[2] = vsubq_s16(tbl2q(dgd_rows[2], dgd_rows[3], lut2), avg_s16); + dgd_avg0[3] = vsubq_s16(tbl2q(dgd_rows[3], dgd_rows[4], lut3), avg_s16); + dgd_avg0[4] = vsubq_s16(tbl2q(dgd_rows[4], dgd_rows[5], lut4), avg_s16); + dgd_avg0[5] = vsubq_s16(tbl2q(dgd_rows[5], dgd_rows[6], lut5), avg_s16); + + vst1q_s16(DGD_AVG0, dgd_avg0[0]); + vst1q_s16(DGD_AVG0 + 8, dgd_avg0[1]); + vst1q_s16(DGD_AVG0 + 16, dgd_avg0[2]); + vst1q_s16(DGD_AVG0 + 24, dgd_avg0[3]); + vst1q_s16(DGD_AVG0 + 32, dgd_avg0[4]); + vst1q_s16(DGD_AVG0 + 40, dgd_avg0[5]); + + // The remaining last (49th) element of `dgd - avg`. + DGD_AVG0[48] = dgd_ptr[6] - avg; + + // Accumulate into row-major order variant of matrix M (cross-correlation) + // for 1 output pixel at a time. M is of size 7 * 7. It needs to be filled + // such that multiplying one element from src with each element of a row + // of the wiener window will fill one column of M. However this is not + // very convenient in terms of memory access, as it means we do + // contiguous loads of dgd but strided stores to M. As a result, we use an + // intermediate matrix M_s32 which is instead filled such that one row of + // the wiener window gives one row of M_s32. Once fully computed, M_s32 is + // then transposed to return M. + int src_avg0 = *src++ - avg; + int16x4_t src_avg0_s16 = vdup_n_s16(src_avg0); + update_M_1pixel(M_s32 + 0, src_avg0_s16, dgd_avg0[0]); + update_M_1pixel(M_s32 + 8, src_avg0_s16, dgd_avg0[1]); + update_M_1pixel(M_s32 + 16, src_avg0_s16, dgd_avg0[2]); + update_M_1pixel(M_s32 + 24, src_avg0_s16, dgd_avg0[3]); + update_M_1pixel(M_s32 + 32, src_avg0_s16, dgd_avg0[4]); + update_M_1pixel(M_s32 + 40, src_avg0_s16, dgd_avg0[5]); + + // Last (49th) element of M_s32 can be computed as scalar more efficiently + // for 1 output pixel. + M_s32[48] += DGD_AVG0[48] * src_avg0; + + // Start accumulating into row-major order version of matrix H + // (auto-covariance), it expects the DGD_AVG0 matrix to also be row-major. + // H is of size 49 * 49. It is filled by multiplying every pair of + // elements of the wiener window together (vector outer product). Since it + // is a symmetric matrix, we only compute the upper-right triangle, and + // then copy it down to the lower-left later. The upper triangle is + // covered by 4x4 tiles. The original algorithm assumes the M matrix is + // column-major and the resulting H matrix is also expected to be + // column-major. It is not efficient to work column-major matrices, so we + // accumulate into a row-major matrix H_s32. At the end of the algorithm a + // double transpose transformation will convert H_s32 back to the expected + // output layout. + update_H_1pixel(H_s32, DGD_AVG0, WIENER_WIN2_ALIGN2, 48); + + // The last element of the triangle of H_s32 matrix can be computed as + // scalar more efficiently. + H_s32[48 * WIENER_WIN2_ALIGN2 + 48] += DGD_AVG0[48] * DGD_AVG0[48]; + } + + src += src_next; + dgd += dgd_next; + } while (--height != 0); + + int bit_depth_shift = bit_depth - AOM_BITS_8; + + acc_transpose_M(M, M_s64, M_s32, WIENER_WIN, bit_depth_shift); + + update_H(H, H_s64, H_s32, WIENER_WIN, WIENER_WIN2_ALIGN2, bit_depth_shift); +} + +// Load 5x5 matrix into 5 128-bit vectors from consecutive rows, the last load +// address is offset to prevent out-of-bounds access. +static INLINE void load_and_pack_s16_6x5(int16x8_t dst[5], const int16_t *src, + ptrdiff_t stride) { + dst[0] = vld1q_s16(src); + src += stride; + dst[1] = vld1q_s16(src); + src += stride; + dst[2] = vld1q_s16(src); + src += stride; + dst[3] = vld1q_s16(src); + src += stride; + dst[4] = vld1q_s16(src - 3); +} + +static void highbd_compute_stats_win5_neon(const uint16_t *dgd, + const uint16_t *src, int avg, + int width, int height, + int dgd_stride, int src_stride, + int64_t *M, int64_t *H, + aom_bit_depth_t bit_depth) { + // Matrix names are capitalized to help readability. + DECLARE_ALIGNED(64, int16_t, DGD_AVG0[WIENER_WIN2_REDUCED_ALIGN3]); + DECLARE_ALIGNED(64, int16_t, DGD_AVG1[WIENER_WIN2_REDUCED_ALIGN3]); + DECLARE_ALIGNED(64, int32_t, M_s32[WIENER_WIN2_REDUCED_ALIGN3]); + DECLARE_ALIGNED(64, int64_t, M_s64[WIENER_WIN2_REDUCED_ALIGN3]); + DECLARE_ALIGNED(64, int32_t, + H_s32[WIENER_WIN2_REDUCED * WIENER_WIN2_REDUCED_ALIGN2]); + DECLARE_ALIGNED(64, int64_t, + H_s64[WIENER_WIN2_REDUCED * WIENER_WIN2_REDUCED_ALIGN2]); + + memset(M_s32, 0, sizeof(M_s32)); + memset(M_s64, 0, sizeof(M_s64)); + memset(H_s32, 0, sizeof(H_s32)); + memset(H_s64, 0, sizeof(H_s64)); + + // Look-up tables to create 8x3 matrix with consecutive elements from 5x5 + // matrix. + DECLARE_ALIGNED(16, static const uint8_t, shuffle_stats5_highbd[96]) = { + 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 16, 17, 18, 19, 20, 21, + 6, 7, 8, 9, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 32, 33, + 2, 3, 4, 5, 6, 7, 8, 9, 22, 23, 24, 25, 26, 27, 28, 29, + 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 18, 19, 20, 21, 22, 23, + 8, 9, 10, 11, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 34, 35, + 4, 5, 6, 7, 8, 9, 10, 11, 24, 25, 26, 27, 28, 29, 30, 31, + }; + + const uint8x16_t lut0 = vld1q_u8(shuffle_stats5_highbd + 0); + const uint8x16_t lut1 = vld1q_u8(shuffle_stats5_highbd + 16); + const uint8x16_t lut2 = vld1q_u8(shuffle_stats5_highbd + 32); + const uint8x16_t lut3 = vld1q_u8(shuffle_stats5_highbd + 48); + const uint8x16_t lut4 = vld1q_u8(shuffle_stats5_highbd + 64); + const uint8x16_t lut5 = vld1q_u8(shuffle_stats5_highbd + 80); + + // We can accumulate up to 65536/4096/256 8/10/12-bit multiplication results + // in 32-bit. We are processing 2 pixels at a time, so the accumulator max can + // be as high as 32768/2048/128 for the compute stats. + const int acc_cnt_max = (1 << (32 - 2 * bit_depth)) >> 1; + int acc_cnt = acc_cnt_max; + const int src_next = src_stride - width; + const int dgd_next = dgd_stride - width; + const int16x8_t avg_s16 = vdupq_n_s16(avg); + + do { + int j = width; + while (j >= 2) { + // Load two adjacent, overlapping 5x5 matrices: a 6x5 matrix with the + // middle 4x5 elements being shared. + int16x8_t dgd_rows[5]; + load_and_pack_s16_6x5(dgd_rows, (const int16_t *)dgd, dgd_stride); + + const int16_t *dgd_ptr = (const int16_t *)dgd + dgd_stride * 4; + dgd += 2; + + dgd_rows[0] = vsubq_s16(dgd_rows[0], avg_s16); + dgd_rows[1] = vsubq_s16(dgd_rows[1], avg_s16); + dgd_rows[2] = vsubq_s16(dgd_rows[2], avg_s16); + dgd_rows[3] = vsubq_s16(dgd_rows[3], avg_s16); + dgd_rows[4] = vsubq_s16(dgd_rows[4], avg_s16); + + // Re-arrange the combined 6x5 matrix to have the 2 whole 5x5 matrices (1 + // for each of the 2 pixels) separated into distinct int16x8_t[3] arrays. + // These arrays contain 24 elements of the 25 (5x5). Compute `dgd - avg` + // for both buffers. Each DGD_AVG buffer contains 25 consecutive elements. + int16x8_t dgd_avg0[3]; + int16x8_t dgd_avg1[3]; + + dgd_avg0[0] = tbl2q(dgd_rows[0], dgd_rows[1], lut0); + dgd_avg1[0] = tbl2q(dgd_rows[0], dgd_rows[1], lut3); + dgd_avg0[1] = tbl3q(dgd_rows[1], dgd_rows[2], dgd_rows[3], lut1); + dgd_avg1[1] = tbl3q(dgd_rows[1], dgd_rows[2], dgd_rows[3], lut4); + dgd_avg0[2] = tbl2q(dgd_rows[3], dgd_rows[4], lut2); + dgd_avg1[2] = tbl2q(dgd_rows[3], dgd_rows[4], lut5); + + vst1q_s16(DGD_AVG0, dgd_avg0[0]); + vst1q_s16(DGD_AVG1, dgd_avg1[0]); + vst1q_s16(DGD_AVG0 + 8, dgd_avg0[1]); + vst1q_s16(DGD_AVG1 + 8, dgd_avg1[1]); + vst1q_s16(DGD_AVG0 + 16, dgd_avg0[2]); + vst1q_s16(DGD_AVG1 + 16, dgd_avg1[2]); + + // The remaining last (25th) elements of `dgd - avg`. + DGD_AVG0[24] = dgd_ptr[4] - avg; + DGD_AVG1[24] = dgd_ptr[5] - avg; + + // Accumulate into row-major variant of matrix M (cross-correlation) for 2 + // output pixels at a time. M is of size 5 * 5. It needs to be filled such + // that multiplying one element from src with each element of a row of the + // wiener window will fill one column of M. However this is not very + // convenient in terms of memory access, as it means we do contiguous + // loads of dgd but strided stores to M. As a result, we use an + // intermediate matrix M_s32 which is instead filled such that one row of + // the wiener window gives one row of M_s32. Once fully computed, M_s32 is + // then transposed to return M. + int src_avg0 = *src++ - avg; + int src_avg1 = *src++ - avg; + int16x4_t src_avg0_s16 = vdup_n_s16(src_avg0); + int16x4_t src_avg1_s16 = vdup_n_s16(src_avg1); + update_M_2pixels(M_s32 + 0, src_avg0_s16, src_avg1_s16, dgd_avg0[0], + dgd_avg1[0]); + update_M_2pixels(M_s32 + 8, src_avg0_s16, src_avg1_s16, dgd_avg0[1], + dgd_avg1[1]); + update_M_2pixels(M_s32 + 16, src_avg0_s16, src_avg1_s16, dgd_avg0[2], + dgd_avg1[2]); + + // Last (25th) element of M_s32 can be computed as scalar more efficiently + // for 2 output pixels. + M_s32[24] += DGD_AVG0[24] * src_avg0 + DGD_AVG1[24] * src_avg1; + + // Start accumulating into row-major version of matrix H + // (auto-covariance), it expects the DGD_AVG[01] matrices to also be + // row-major. H is of size 25 * 25. It is filled by multiplying every pair + // of elements of the wiener window together (vector outer product). Since + // it is a symmetric matrix, we only compute the upper-right triangle, and + // then copy it down to the lower-left later. The upper triangle is + // covered by 4x4 tiles. The original algorithm assumes the M matrix is + // column-major and the resulting H matrix is also expected to be + // column-major. It is not efficient to work with column-major matrices, + // so we accumulate into a row-major matrix H_s32. At the end of the + // algorithm a double transpose transformation will convert H_s32 back to + // the expected output layout. + update_H_5x5_2pixels(H_s32, DGD_AVG0, DGD_AVG1); + + // The last element of the triangle of H_s32 matrix can be computed as a + // scalar more efficiently. + H_s32[24 * WIENER_WIN2_REDUCED_ALIGN2 + 24] += + DGD_AVG0[24] * DGD_AVG0[24] + DGD_AVG1[24] * DGD_AVG1[24]; + + // Accumulate into 64-bit after a bit depth dependent number of iterations + // to prevent overflow. + if (--acc_cnt == 0) { + acc_cnt = acc_cnt_max; + + accumulate_and_clear(M_s64, M_s32, WIENER_WIN2_REDUCED_ALIGN2); + + // The widening accumulation is only needed for the upper triangle part + // of the matrix. + int64_t *lh = H_s64; + int32_t *lh32 = H_s32; + for (int k = 0; k < WIENER_WIN2_REDUCED; ++k) { + // The widening accumulation is only run for the relevant parts + // (upper-right triangle) in a row 4-element aligned. + int k4 = k / 4 * 4; + accumulate_and_clear(lh + k4, lh32 + k4, 24 - k4); + + // Last element of the row is computed separately. + lh[24] += lh32[24]; + lh32[24] = 0; + + lh += WIENER_WIN2_REDUCED_ALIGN2; + lh32 += WIENER_WIN2_REDUCED_ALIGN2; + } + } + + j -= 2; + } + + // Computations for odd pixel in the row. + if (width & 1) { + // Load two adjacent, overlapping 5x5 matrices: a 6x5 matrix with the + // middle 4x5 elements being shared. + int16x8_t dgd_rows[5]; + load_and_pack_s16_6x5(dgd_rows, (const int16_t *)dgd, dgd_stride); + + const int16_t *dgd_ptr = (const int16_t *)dgd + dgd_stride * 4; + ++dgd; + + // Re-arrange (and widen) the combined 6x5 matrix to have a whole 5x5 + // matrix tightly packed into a int16x8_t[3] array. This array contains + // 24 elements of the 25 (5x5). Compute `dgd - avg` for the whole buffer. + // The DGD_AVG buffer contains 25 consecutive elements. + int16x8_t dgd_avg0[3]; + + dgd_avg0[0] = vsubq_s16(tbl2q(dgd_rows[0], dgd_rows[1], lut0), avg_s16); + dgd_avg0[1] = vsubq_s16( + tbl3q(dgd_rows[1], dgd_rows[2], dgd_rows[3], lut1), avg_s16); + dgd_avg0[2] = vsubq_s16(tbl2q(dgd_rows[3], dgd_rows[4], lut2), avg_s16); + + vst1q_s16(DGD_AVG0, dgd_avg0[0]); + vst1q_s16(DGD_AVG0 + 8, dgd_avg0[1]); + vst1q_s16(DGD_AVG0 + 16, dgd_avg0[2]); + + // The remaining last (25th) element of `dgd - avg`. + DGD_AVG0[24] = dgd_ptr[4] - avg; + DGD_AVG1[24] = dgd_ptr[5] - avg; + + // Accumulate into row-major order variant of matrix M (cross-correlation) + // for 1 output pixel at a time. M is of size 5 * 5. It needs to be filled + // such that multiplying one element from src with each element of a row + // of the wiener window will fill one column of M. However this is not + // very convenient in terms of memory access, as it means we do + // contiguous loads of dgd but strided stores to M. As a result, we use an + // intermediate matrix M_s32 which is instead filled such that one row of + // the wiener window gives one row of M_s32. Once fully computed, M_s32 is + // then transposed to return M. + int src_avg0 = *src++ - avg; + int16x4_t src_avg0_s16 = vdup_n_s16(src_avg0); + update_M_1pixel(M_s32 + 0, src_avg0_s16, dgd_avg0[0]); + update_M_1pixel(M_s32 + 8, src_avg0_s16, dgd_avg0[1]); + update_M_1pixel(M_s32 + 16, src_avg0_s16, dgd_avg0[2]); + + // Last (25th) element of M_s32 can be computed as scalar more efficiently + // for 1 output pixel. + M_s32[24] += DGD_AVG0[24] * src_avg0; + + // Start accumulating into row-major order version of matrix H + // (auto-covariance), it expects the DGD_AVG0 matrix to also be row-major. + // H is of size 25 * 25. It is filled by multiplying every pair of + // elements of the wiener window together (vector outer product). Since it + // is a symmetric matrix, we only compute the upper-right triangle, and + // then copy it down to the lower-left later. The upper triangle is + // covered by 4x4 tiles. The original algorithm assumes the M matrix is + // column-major and the resulting H matrix is also expected to be + // column-major. It is not efficient to work with column-major matrices, + // so we accumulate into a row-major matrix H_s32. At the end of the + // algorithm a double transpose transformation will convert H_s32 back to + // the expected output layout. + update_H_1pixel(H_s32, DGD_AVG0, WIENER_WIN2_REDUCED_ALIGN2, 24); + + // The last element of the triangle of H_s32 matrix can be computed as a + // scalar more efficiently. + H_s32[24 * WIENER_WIN2_REDUCED_ALIGN2 + 24] += + DGD_AVG0[24] * DGD_AVG0[24]; + } + + src += src_next; + dgd += dgd_next; + } while (--height != 0); + + int bit_depth_shift = bit_depth - AOM_BITS_8; + + acc_transpose_M(M, M_s64, M_s32, WIENER_WIN_REDUCED, bit_depth_shift); + + update_H(H, H_s64, H_s32, WIENER_WIN_REDUCED, WIENER_WIN2_REDUCED_ALIGN2, + bit_depth_shift); +} + +static uint16_t highbd_find_average_neon(const uint16_t *src, int src_stride, + int width, int height) { + assert(width > 0); + assert(height > 0); + + uint64x2_t sum_u64 = vdupq_n_u64(0); + uint64_t sum = 0; + + int h = height; + do { + uint32x4_t sum_u32[2] = { vdupq_n_u32(0), vdupq_n_u32(0) }; + + int w = width; + const uint16_t *row = src; + while (w >= 32) { + uint16x8_t s0 = vld1q_u16(row + 0); + uint16x8_t s1 = vld1q_u16(row + 8); + uint16x8_t s2 = vld1q_u16(row + 16); + uint16x8_t s3 = vld1q_u16(row + 24); + + s0 = vaddq_u16(s0, s1); + s2 = vaddq_u16(s2, s3); + sum_u32[0] = vpadalq_u16(sum_u32[0], s0); + sum_u32[1] = vpadalq_u16(sum_u32[1], s2); + + row += 32; + w -= 32; + } + + if (w >= 16) { + uint16x8_t s0 = vld1q_u16(row + 0); + uint16x8_t s1 = vld1q_u16(row + 8); + + s0 = vaddq_u16(s0, s1); + sum_u32[0] = vpadalq_u16(sum_u32[0], s0); + + row += 16; + w -= 16; + } + + if (w >= 8) { + uint16x8_t s0 = vld1q_u16(row); + sum_u32[1] = vpadalq_u16(sum_u32[1], s0); + + row += 8; + w -= 8; + } + + if (w >= 4) { + uint16x8_t s0 = vcombine_u16(vld1_u16(row), vdup_n_u16(0)); + sum_u32[0] = vpadalq_u16(sum_u32[0], s0); + + row += 4; + w -= 4; + } + + while (w-- > 0) { + sum += *row++; + } + + sum_u64 = vpadalq_u32(sum_u64, vaddq_u32(sum_u32[0], sum_u32[1])); + + src += src_stride; + } while (--h != 0); + + return (uint16_t)((horizontal_add_u64x2(sum_u64) + sum) / (height * width)); +} + +void av1_compute_stats_highbd_neon(int wiener_win, const uint8_t *dgd8, + const uint8_t *src8, int h_start, int h_end, + int v_start, int v_end, int dgd_stride, + int src_stride, int64_t *M, int64_t *H, + aom_bit_depth_t bit_depth) { + assert(wiener_win == WIENER_WIN || wiener_win == WIENER_WIN_REDUCED); + + const int wiener_halfwin = wiener_win >> 1; + const uint16_t *src = CONVERT_TO_SHORTPTR(src8); + const uint16_t *dgd = CONVERT_TO_SHORTPTR(dgd8); + const int height = v_end - v_start; + const int width = h_end - h_start; + + const uint16_t *dgd_start = dgd + h_start + v_start * dgd_stride; + const uint16_t *src_start = src + h_start + v_start * src_stride; + + // The wiener window will slide along the dgd frame, centered on each pixel. + // For the top left pixel and all the pixels on the side of the frame this + // means half of the window will be outside of the frame. As such the actual + // buffer that we need to subtract the avg from will be 2 * wiener_halfwin + // wider and 2 * wiener_halfwin higher than the original dgd buffer. + const int vert_offset = v_start - wiener_halfwin; + const int horiz_offset = h_start - wiener_halfwin; + const uint16_t *dgd_win = dgd + horiz_offset + vert_offset * dgd_stride; + + uint16_t avg = highbd_find_average_neon(dgd_start, dgd_stride, width, height); + + if (wiener_win == WIENER_WIN) { + highbd_compute_stats_win7_neon(dgd_win, src_start, avg, width, height, + dgd_stride, src_stride, M, H, bit_depth); + } else { + highbd_compute_stats_win5_neon(dgd_win, src_start, avg, width, height, + dgd_stride, src_stride, M, H, bit_depth); + } +} + +int64_t av1_highbd_pixel_proj_error_neon( + const uint8_t *src8, int width, int height, int src_stride, + const uint8_t *dat8, int dat_stride, int32_t *flt0, int flt0_stride, + int32_t *flt1, int flt1_stride, int xq[2], const sgr_params_type *params) { + const uint16_t *src = CONVERT_TO_SHORTPTR(src8); + const uint16_t *dat = CONVERT_TO_SHORTPTR(dat8); + int64_t sse = 0; + int64x2_t sse_s64 = vdupq_n_s64(0); + + if (params->r[0] > 0 && params->r[1] > 0) { + int32x2_t xq_v = vld1_s32(xq); + int32x2_t xq_sum_v = vshl_n_s32(vpadd_s32(xq_v, xq_v), 4); + + do { + int j = 0; + int32x4_t sse_s32 = vdupq_n_s32(0); + + do { + const uint16x8_t d = vld1q_u16(&dat[j]); + const uint16x8_t s = vld1q_u16(&src[j]); + int32x4_t flt0_0 = vld1q_s32(&flt0[j]); + int32x4_t flt0_1 = vld1q_s32(&flt0[j + 4]); + int32x4_t flt1_0 = vld1q_s32(&flt1[j]); + int32x4_t flt1_1 = vld1q_s32(&flt1[j + 4]); + + int32x4_t d_s32_lo = vreinterpretq_s32_u32( + vmull_lane_u16(vget_low_u16(d), vreinterpret_u16_s32(xq_sum_v), 0)); + int32x4_t d_s32_hi = vreinterpretq_s32_u32(vmull_lane_u16( + vget_high_u16(d), vreinterpret_u16_s32(xq_sum_v), 0)); + + int32x4_t v0 = vsubq_s32( + vdupq_n_s32(1 << (SGRPROJ_RST_BITS + SGRPROJ_PRJ_BITS - 1)), + d_s32_lo); + int32x4_t v1 = vsubq_s32( + vdupq_n_s32(1 << (SGRPROJ_RST_BITS + SGRPROJ_PRJ_BITS - 1)), + d_s32_hi); + + v0 = vmlaq_lane_s32(v0, flt0_0, xq_v, 0); + v1 = vmlaq_lane_s32(v1, flt0_1, xq_v, 0); + v0 = vmlaq_lane_s32(v0, flt1_0, xq_v, 1); + v1 = vmlaq_lane_s32(v1, flt1_1, xq_v, 1); + + int16x4_t vr0 = vshrn_n_s32(v0, SGRPROJ_RST_BITS + SGRPROJ_PRJ_BITS); + int16x4_t vr1 = vshrn_n_s32(v1, SGRPROJ_RST_BITS + SGRPROJ_PRJ_BITS); + + int16x8_t e = vaddq_s16(vcombine_s16(vr0, vr1), + vreinterpretq_s16_u16(vsubq_u16(d, s))); + int16x4_t e_lo = vget_low_s16(e); + int16x4_t e_hi = vget_high_s16(e); + + sse_s32 = vmlal_s16(sse_s32, e_lo, e_lo); + sse_s32 = vmlal_s16(sse_s32, e_hi, e_hi); + + j += 8; + } while (j <= width - 8); + + for (int k = j; k < width; ++k) { + int32_t v = 1 << (SGRPROJ_RST_BITS + SGRPROJ_PRJ_BITS - 1); + v += xq[0] * (flt0[k]) + xq[1] * (flt1[k]); + v -= (xq[1] + xq[0]) * (int32_t)(dat[k] << 4); + int32_t e = + (v >> (SGRPROJ_RST_BITS + SGRPROJ_PRJ_BITS)) + dat[k] - src[k]; + sse += ((int64_t)e * e); + } + + sse_s64 = vpadalq_s32(sse_s64, sse_s32); + + dat += dat_stride; + src += src_stride; + flt0 += flt0_stride; + flt1 += flt1_stride; + } while (--height != 0); + } else if (params->r[0] > 0 || params->r[1] > 0) { + int xq_active = (params->r[0] > 0) ? xq[0] : xq[1]; + int32_t *flt = (params->r[0] > 0) ? flt0 : flt1; + int flt_stride = (params->r[0] > 0) ? flt0_stride : flt1_stride; + int32x4_t xq_v = vdupq_n_s32(xq_active); + + do { + int j = 0; + int32x4_t sse_s32 = vdupq_n_s32(0); + do { + const uint16x8_t d0 = vld1q_u16(&dat[j]); + const uint16x8_t s0 = vld1q_u16(&src[j]); + int32x4_t flt0_0 = vld1q_s32(&flt[j]); + int32x4_t flt0_1 = vld1q_s32(&flt[j + 4]); + + uint16x8_t d_u16 = vshlq_n_u16(d0, 4); + int32x4_t sub0 = vreinterpretq_s32_u32( + vsubw_u16(vreinterpretq_u32_s32(flt0_0), vget_low_u16(d_u16))); + int32x4_t sub1 = vreinterpretq_s32_u32( + vsubw_u16(vreinterpretq_u32_s32(flt0_1), vget_high_u16(d_u16))); + + int32x4_t v0 = vmlaq_s32( + vdupq_n_s32(1 << (SGRPROJ_RST_BITS + SGRPROJ_PRJ_BITS - 1)), sub0, + xq_v); + int32x4_t v1 = vmlaq_s32( + vdupq_n_s32(1 << (SGRPROJ_RST_BITS + SGRPROJ_PRJ_BITS - 1)), sub1, + xq_v); + + int16x4_t vr0 = vshrn_n_s32(v0, SGRPROJ_RST_BITS + SGRPROJ_PRJ_BITS); + int16x4_t vr1 = vshrn_n_s32(v1, SGRPROJ_RST_BITS + SGRPROJ_PRJ_BITS); + + int16x8_t e = vaddq_s16(vcombine_s16(vr0, vr1), + vreinterpretq_s16_u16(vsubq_u16(d0, s0))); + int16x4_t e_lo = vget_low_s16(e); + int16x4_t e_hi = vget_high_s16(e); + + sse_s32 = vmlal_s16(sse_s32, e_lo, e_lo); + sse_s32 = vmlal_s16(sse_s32, e_hi, e_hi); + + j += 8; + } while (j <= width - 8); + + for (int k = j; k < width; ++k) { + int32_t v = 1 << (SGRPROJ_RST_BITS + SGRPROJ_PRJ_BITS - 1); + v += xq_active * (int32_t)((uint32_t)flt[j] - (uint16_t)(dat[k] << 4)); + const int32_t e = + (v >> (SGRPROJ_RST_BITS + SGRPROJ_PRJ_BITS)) + dat[k] - src[k]; + sse += ((int64_t)e * e); + } + + sse_s64 = vpadalq_s32(sse_s64, sse_s32); + + dat += dat_stride; + flt += flt_stride; + src += src_stride; + } while (--height != 0); + } else { + do { + int j = 0; + + do { + const uint16x8_t d = vld1q_u16(&dat[j]); + const uint16x8_t s = vld1q_u16(&src[j]); + + uint16x8_t diff = vabdq_u16(d, s); + uint16x4_t diff_lo = vget_low_u16(diff); + uint16x4_t diff_hi = vget_high_u16(diff); + + uint32x4_t sqr_lo = vmull_u16(diff_lo, diff_lo); + uint32x4_t sqr_hi = vmull_u16(diff_hi, diff_hi); + + sse_s64 = vpadalq_s32(sse_s64, vreinterpretq_s32_u32(sqr_lo)); + sse_s64 = vpadalq_s32(sse_s64, vreinterpretq_s32_u32(sqr_hi)); + + j += 8; + } while (j <= width - 8); + + for (int k = j; k < width; ++k) { + int32_t e = dat[k] - src[k]; + sse += e * e; + } + + dat += dat_stride; + src += src_stride; + } while (--height != 0); + } + + sse += horizontal_add_s64x2(sse_s64); + return sse; +} |