// Tencent is pleased to support the open source community by making ncnn available. // // Copyright (C) 2022 THL A29 Limited, a Tencent company. All rights reserved. // // Licensed under the BSD 3-Clause License (the "License"); you may not use this file except // in compliance with the License. You may obtain a copy of the License at // // https://opensource.org/licenses/BSD-3-Clause // // Unless required by applicable law or agreed to in writing, software distributed // under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR // CONDITIONS OF ANY KIND, either express or implied. See the License for the // specific language governing permissions and limitations under the License. static void im2col_sgemm_pack1to4_int8_msa(const Mat& bottom_im2col, Mat& top_blob, const Mat& kernel, const Option& opt) { // Mat bottom_im2col(size, maxk, inch, 8u, 8, opt.workspace_allocator); const int size = bottom_im2col.w; const int maxk = bottom_im2col.h; const int inch = bottom_im2col.c; const int outch = top_blob.c; // permute Mat tmp; if (inch >= 4) { if (size >= 2) tmp.create(2 * maxk, inch / 4 + inch % 4, size / 2 + size % 2, 4u, 4, opt.workspace_allocator); else tmp.create(maxk, inch / 4 + inch % 4, size, 4u, 4, opt.workspace_allocator); } else { if (size >= 2) tmp.create(2 * maxk, inch, size / 2 + size % 2, 1u, 1, opt.workspace_allocator); else tmp.create(maxk, inch, size, 1u, 1, opt.workspace_allocator); } { int remain_size_start = 0; int nn_size = (size - remain_size_start) >> 1; #pragma omp parallel for num_threads(opt.num_threads) for (int ii = 0; ii < nn_size; ii++) { int i = remain_size_start + ii * 2; signed char* tmpptr = tmp.channel(i / 2); int q = 0; for (; q + 3 < inch; q += 4) { const signed char* img0 = (const signed char*)bottom_im2col.channel(q) + i; const signed char* img1 = (const signed char*)bottom_im2col.channel(q + 1) + i; const signed char* img2 = (const signed char*)bottom_im2col.channel(q + 2) + i; const signed char* img3 = (const signed char*)bottom_im2col.channel(q + 3) + i; for (int k = 0; k < maxk; k++) { tmpptr[0] = img0[0]; tmpptr[1] = img1[0]; tmpptr[2] = img2[0]; tmpptr[3] = img3[0]; tmpptr[4] = img0[1]; tmpptr[5] = img1[1]; tmpptr[6] = img2[1]; tmpptr[7] = img3[1]; tmpptr += 8; img0 += size; img1 += size; img2 += size; img3 += size; } } for (; q < inch; q++) { const signed char* img0 = (const signed char*)bottom_im2col.channel(q) + i; for (int k = 0; k < maxk; k++) { tmpptr[0] = img0[0]; tmpptr[1] = img0[1]; tmpptr += 2; img0 += size; } } } remain_size_start += nn_size << 1; #pragma omp parallel for num_threads(opt.num_threads) for (int i = remain_size_start; i < size; i++) { signed char* tmpptr = tmp.channel(i / 2 + i % 2); int q = 0; for (; q + 3 < inch; q += 4) { const signed char* img0 = (const signed char*)bottom_im2col.channel(q) + i; const signed char* img1 = (const signed char*)bottom_im2col.channel(q + 1) + i; const signed char* img2 = (const signed char*)bottom_im2col.channel(q + 2) + i; const signed char* img3 = (const signed char*)bottom_im2col.channel(q + 3) + i; for (int k = 0; k < maxk; k++) { tmpptr[0] = img0[0]; tmpptr[1] = img1[0]; tmpptr[2] = img2[0]; tmpptr[3] = img3[0]; tmpptr += 4; img0 += size; img1 += size; img2 += size; img3 += size; } } for (; q < inch; q++) { const signed char* img0 = (const signed char*)bottom_im2col.channel(q) + i; for (int k = 0; k < maxk; k++) { tmpptr[0] = img0[0]; tmpptr += 1; img0 += size; } } } } #pragma omp parallel for num_threads(opt.num_threads) for (int p = 0; p < outch; p++) { int* outptr0 = top_blob.channel(p); int i = 0; for (; i + 1 < size; i += 2) { const signed char* tmpptr = tmp.channel(i / 2); const signed char* kptr = kernel.channel(p); int nn4 = (inch / 4) * maxk; int nn1 = (inch % 4) * maxk; v4i32 _sum00 = __msa_fill_w(0); v4i32 _sum10 = __msa_fill_w(0); if (nn4 > 0) { v4i32 _sum01 = __msa_fill_w(0); v4i32 _sum02 = __msa_fill_w(0); v4i32 _sum03 = __msa_fill_w(0); v4i32 _sum11 = __msa_fill_w(0); v4i32 _sum12 = __msa_fill_w(0); v4i32 _sum13 = __msa_fill_w(0); int j = 0; for (; j < nn4; j++) { __builtin_prefetch(tmpptr + 32); __builtin_prefetch(kptr + 64); v16i8 _val = __msa_ld_b(tmpptr, 0); v8i16 _val01 = (v8i16)__msa_ilvr_b(__msa_clti_s_b(_val, 0), _val); v8i16 _val0 = (v8i16)__msa_ilvr_d((v2i64)_val01, (v2i64)_val01); v8i16 _val1 = (v8i16)__msa_ilvl_d((v2i64)_val01, (v2i64)_val01); v16i8 _w01 = __msa_ld_b(kptr, 0); v16i8 _extw01 = __msa_clti_s_b(_w01, 0); v8i16 _w0 = (v8i16)__msa_ilvr_b(_extw01, _w01); v8i16 _w1 = (v8i16)__msa_ilvl_b(_extw01, _w01); v8i16 _s00 = __msa_mulv_h(_val0, _w0); v8i16 _s01 = __msa_mulv_h(_val0, _w1); v8i16 _s10 = __msa_mulv_h(_val1, _w0); v8i16 _s11 = __msa_mulv_h(_val1, _w1); v8i16 _exts00 = __msa_clti_s_h(_s00, 0); v8i16 _exts01 = __msa_clti_s_h(_s01, 0); v8i16 _exts10 = __msa_clti_s_h(_s10, 0); v8i16 _exts11 = __msa_clti_s_h(_s11, 0); v4i32 _s00l = (v4i32)__msa_ilvr_h(_exts00, _s00); v4i32 _s00h = (v4i32)__msa_ilvl_h(_exts00, _s00); v4i32 _s01l = (v4i32)__msa_ilvr_h(_exts01, _s01); v4i32 _s01h = (v4i32)__msa_ilvl_h(_exts01, _s01); v4i32 _s10l = (v4i32)__msa_ilvr_h(_exts10, _s10); v4i32 _s10h = (v4i32)__msa_ilvl_h(_exts10, _s10); v4i32 _s11l = (v4i32)__msa_ilvr_h(_exts11, _s11); v4i32 _s11h = (v4i32)__msa_ilvl_h(_exts11, _s11); _sum00 = __msa_addv_w(_sum00, _s00l); _sum01 = __msa_addv_w(_sum01, _s00h); _sum02 = __msa_addv_w(_sum02, _s01l); _sum03 = __msa_addv_w(_sum03, _s01h); _sum10 = __msa_addv_w(_sum10, _s10l); _sum11 = __msa_addv_w(_sum11, _s10h); _sum12 = __msa_addv_w(_sum12, _s11l); _sum13 = __msa_addv_w(_sum13, _s11h); tmpptr += 8; kptr += 16; } // transpose 4x4 { v4i32 _tmp0, _tmp1, _tmp2, _tmp3; _tmp0 = __msa_ilvr_w(_sum01, _sum00); _tmp1 = __msa_ilvr_w(_sum03, _sum02); _tmp2 = __msa_ilvl_w(_sum01, _sum00); _tmp3 = __msa_ilvl_w(_sum03, _sum02); _sum00 = (v4i32)__msa_ilvr_d((v2i64)_tmp1, (v2i64)_tmp0); _sum01 = (v4i32)__msa_ilvl_d((v2i64)_tmp1, (v2i64)_tmp0); _sum02 = (v4i32)__msa_ilvr_d((v2i64)_tmp3, (v2i64)_tmp2); _sum03 = (v4i32)__msa_ilvl_d((v2i64)_tmp3, (v2i64)_tmp2); } { v4i32 _tmp0, _tmp1, _tmp2, _tmp3; _tmp0 = __msa_ilvr_w(_sum11, _sum10); _tmp1 = __msa_ilvr_w(_sum13, _sum12); _tmp2 = __msa_ilvl_w(_sum11, _sum10); _tmp3 = __msa_ilvl_w(_sum13, _sum12); _sum10 = (v4i32)__msa_ilvr_d((v2i64)_tmp1, (v2i64)_tmp0); _sum11 = (v4i32)__msa_ilvl_d((v2i64)_tmp1, (v2i64)_tmp0); _sum12 = (v4i32)__msa_ilvr_d((v2i64)_tmp3, (v2i64)_tmp2); _sum13 = (v4i32)__msa_ilvl_d((v2i64)_tmp3, (v2i64)_tmp2); } _sum00 = __msa_addv_w(_sum00, _sum01); _sum02 = __msa_addv_w(_sum02, _sum03); _sum10 = __msa_addv_w(_sum10, _sum11); _sum12 = __msa_addv_w(_sum12, _sum13); _sum00 = __msa_addv_w(_sum00, _sum02); _sum10 = __msa_addv_w(_sum10, _sum12); } int j = 0; for (; j < nn1; j++) { v8i16 _val0 = __msa_fill_h(tmpptr[0]); v8i16 _val1 = __msa_fill_h(tmpptr[1]); v8i16 _val = (v8i16)__msa_ilvr_d((v2i64)_val1, (v2i64)_val0); v16i8 _w = __msa_ld_b(kptr, 0); v8i16 _w16 = (v8i16)__msa_ilvr_b(__msa_clti_s_b(_w, 0), _w); _w16 = (v8i16)__msa_ilvr_d((v2i64)_w16, (v2i64)_w16); v8i16 _s0 = __msa_mulv_h(_val, _w16); v8i16 _exts0 = __msa_clti_s_h(_s0, 0); v4i32 _s0l = (v4i32)__msa_ilvr_h(_exts0, _s0); v4i32 _s0h = (v4i32)__msa_ilvl_h(_exts0, _s0); _sum00 = __msa_addv_w(_sum00, _s0l); _sum10 = __msa_addv_w(_sum10, _s0h); tmpptr += 2; kptr += 4; } __msa_st_w(_sum00, outptr0, 0); __msa_st_w(_sum10, outptr0 + 4, 0); outptr0 += 8; } for (; i < size; i++) { const signed char* tmpptr = tmp.channel(i / 2 + i % 2); const signed char* kptr = kernel.channel(p); int nn4 = (inch / 4) * maxk; int nn1 = (inch % 4) * maxk; v4i32 _sum0 = __msa_fill_w(0); if (nn4 > 0) { v4i32 _sum1 = __msa_fill_w(0); v4i32 _sum2 = __msa_fill_w(0); v4i32 _sum3 = __msa_fill_w(0); int j = 0; for (; j < nn4; j++) { __builtin_prefetch(tmpptr + 16); __builtin_prefetch(kptr + 64); v16i8 _val = __msa_ld_b(tmpptr, 0); v8i16 _val16 = (v8i16)__msa_ilvr_b(__msa_clti_s_b(_val, 0), _val); _val16 = (v8i16)__msa_ilvr_d((v2i64)_val16, (v2i64)_val16); v16i8 _w01 = __msa_ld_b(kptr, 0); v16i8 _extw01 = __msa_clti_s_b(_w01, 0); v8i16 _w0 = (v8i16)__msa_ilvr_b(_extw01, _w01); v8i16 _w1 = (v8i16)__msa_ilvl_b(_extw01, _w01); v8i16 _s0 = __msa_mulv_h(_val16, _w0); v8i16 _s1 = __msa_mulv_h(_val16, _w1); v8i16 _exts0 = __msa_clti_s_h(_s0, 0); v8i16 _exts1 = __msa_clti_s_h(_s1, 0); v4i32 _s0l = (v4i32)__msa_ilvr_h(_exts0, _s0); v4i32 _s0h = (v4i32)__msa_ilvl_h(_exts0, _s0); v4i32 _s1l = (v4i32)__msa_ilvr_h(_exts1, _s1); v4i32 _s1h = (v4i32)__msa_ilvl_h(_exts1, _s1); _sum0 = __msa_addv_w(_sum0, _s0l); _sum1 = __msa_addv_w(_sum1, _s0h); _sum2 = __msa_addv_w(_sum2, _s1l); _sum3 = __msa_addv_w(_sum3, _s1h); tmpptr += 4; kptr += 16; } // transpose 4x4 { v4i32 _tmp0, _tmp1, _tmp2, _tmp3; _tmp0 = __msa_ilvr_w(_sum1, _sum0); _tmp1 = __msa_ilvr_w(_sum3, _sum2); _tmp2 = __msa_ilvl_w(_sum1, _sum0); _tmp3 = __msa_ilvl_w(_sum3, _sum2); _sum0 = (v4i32)__msa_ilvr_d((v2i64)_tmp1, (v2i64)_tmp0); _sum1 = (v4i32)__msa_ilvl_d((v2i64)_tmp1, (v2i64)_tmp0); _sum2 = (v4i32)__msa_ilvr_d((v2i64)_tmp3, (v2i64)_tmp2); _sum3 = (v4i32)__msa_ilvl_d((v2i64)_tmp3, (v2i64)_tmp2); } _sum0 = __msa_addv_w(_sum0, _sum1); _sum2 = __msa_addv_w(_sum2, _sum3); _sum0 = __msa_addv_w(_sum0, _sum2); } int j = 0; for (; j < nn1; j++) { v8i16 _val = __msa_fill_h(tmpptr[0]); v16i8 _w = __msa_ld_b(kptr, 0); v8i16 _w16 = (v8i16)__msa_ilvr_b(__msa_clti_s_b(_w, 0), _w); v8i16 _s0 = __msa_mulv_h(_val, _w16); v4i32 _s032 = (v4i32)__msa_ilvr_h(__msa_clti_s_h(_s0, 0), _s0); _sum0 = __msa_addv_w(_sum0, _s032); tmpptr += 1; kptr += 4; } __msa_st_w(_sum0, outptr0, 0); outptr0 += 4; } } } static void convolution_im2col_sgemm_transform_kernel_pack1to4_int8_msa(const Mat& _kernel, Mat& kernel_tm, int inch, int outch, int kernel_w, int kernel_h) { const int maxk = kernel_w * kernel_h; // interleave // src = maxk-inch-outch // dst = 4a-4b-maxk-inch/4a-outch/4b Mat kernel = _kernel.reshape(maxk, inch, outch); if (inch >= 4) kernel_tm.create(16 * maxk, inch / 4 + inch % 4, outch / 4, (size_t)1u); else kernel_tm.create(4 * maxk, inch, outch / 4, (size_t)1u); for (int q = 0; q + 3 < outch; q += 4) { signed char* g00 = kernel_tm.channel(q / 4); int p = 0; for (; p + 3 < inch; p += 4) { for (int k = 0; k < maxk; k++) { for (int i = 0; i < 4; i++) { for (int j = 0; j < 4; j++) { const signed char* k00 = kernel.channel(q + i).row(p + j); g00[0] = k00[k]; g00++; } } } } for (; p < inch; p++) { for (int k = 0; k < maxk; k++) { for (int i = 0; i < 4; i++) { const signed char* k00 = kernel.channel(q + i).row(p); g00[0] = k00[k]; g00++; } } } } } static void convolution_im2col_sgemm_pack1to4_int8_msa(const Mat& bottom_blob, Mat& top_blob, const Mat& kernel, int kernel_w, int kernel_h, int dilation_w, int dilation_h, int stride_w, int stride_h, const Option& opt) { int w = bottom_blob.w; int inch = bottom_blob.c; int outw = top_blob.w; int outh = top_blob.h; const int size = outw * outh; const int maxk = kernel_w * kernel_h; // im2col Mat bottom_im2col(size, maxk, inch, 1u, 1, opt.workspace_allocator); { const int gap = w * stride_h - outw * stride_w; #pragma omp parallel for num_threads(opt.num_threads) for (int p = 0; p < inch; p++) { const Mat img = bottom_blob.channel(p); signed char* ptr = bottom_im2col.channel(p); for (int u = 0; u < kernel_h; u++) { for (int v = 0; v < kernel_w; v++) { const signed char* sptr = img.row(dilation_h * u) + dilation_w * v; for (int i = 0; i < outh; i++) { int j = 0; for (; j + 3 < outw; j += 4) { ptr[0] = sptr[0]; ptr[1] = sptr[stride_w]; ptr[2] = sptr[stride_w * 2]; ptr[3] = sptr[stride_w * 3]; sptr += stride_w * 4; ptr += 4; } for (; j + 1 < outw; j += 2) { ptr[0] = sptr[0]; ptr[1] = sptr[stride_w]; sptr += stride_w * 2; ptr += 2; } for (; j < outw; j++) { ptr[0] = sptr[0]; sptr += stride_w; ptr += 1; } sptr += gap; } } } } } im2col_sgemm_pack1to4_int8_msa(bottom_im2col, top_blob, kernel, opt); }