/******************************************************************************* * Copyright 2016-2018 Intel Corporation * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * 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. *******************************************************************************/ #include "mkldnn_types.h" #include "c_types_map.hpp" #include "type_helpers.hpp" #include "mkldnn_thread.hpp" #include "utils.hpp" #include "cpu_isa_traits.hpp" #include "gemm_convolution_utils.hpp" #include "jit_generator.hpp" namespace mkldnn { namespace impl { namespace cpu { using namespace mkldnn::impl::status; using namespace mkldnn::impl::utils; using namespace prop_kind; using namespace data_type; namespace jit_gemm_convolution_utils { void im2col_3d(const jit_gemm_conv_conf_t &jcp, const float *im, float *col, int od) { const size_t OHW = jcp.oh * jcp.ow; const size_t im_step = jcp.ih * jcp.iw * jcp.id; const size_t col_step = jcp.ks * OHW; parallel_nd(jcp.ic, [&](int ic) { const float *__restrict im_loc = im + ic * im_step; float *__restrict col_loc = col + ic * col_step; int id = od * jcp.stride_d - jcp.f_pad; for (int kd = 0; kd < jcp.kd; ++kd) { float *__restrict col_ = col_loc + kd * jcp.kh * jcp.kw * OHW; if (id < 0 || id >= jcp.id) { int ih_ = -jcp.t_pad; for (int kh = 0; kh < jcp.kh; ++kh) { int ih = ih_; for (int oh = 0; oh < jcp.oh; ++oh) { if (ih < 0 || ih >= jcp.ih) { ih += jcp.stride_h; continue; } int iw_ = -jcp.l_pad; for (int kw = 0; kw < jcp.kw; ++kw) { int iw = iw_; for (int ow = 0; ow < jcp.ow; ++ow) { if (iw < 0 || iw >= jcp.iw) { iw += jcp.stride_w; continue; } const size_t col_idx = kw * OHW + oh * jcp.ow + ow; col_[col_idx] = 0; iw += jcp.stride_w; } iw_ += (1 + jcp.dilate_w); } ih += jcp.stride_h; } ih_ += (1 + jcp.dilate_h); col_ += jcp.kw * OHW; } } else { const float *__restrict im_ = im_loc + id * jcp.ih * jcp.iw; int ih_ = -jcp.t_pad; for (int kh = 0; kh < jcp.kh; ++kh) { int ih = ih_; for (int oh = 0; oh < jcp.oh; ++oh) { if (ih < 0 || ih >= jcp.ih) { ih += jcp.stride_h; continue; } int iw_ = -jcp.l_pad; for (int kw = 0; kw < jcp.kw; ++kw) { int iw = iw_; for (int ow = 0; ow < jcp.ow; ++ow) { if (iw < 0 || iw >= jcp.iw) { iw += jcp.stride_w; continue; } const size_t col_idx = kw * OHW + oh * jcp.ow + ow; const size_t im_idx = ih * jcp.iw + iw; col_[col_idx] = im_[im_idx]; iw += jcp.stride_w; } iw_ += (1 + jcp.dilate_w); } ih += jcp.stride_h; } ih_ += (1 + jcp.dilate_h); col_ += jcp.kw * OHW; } } id += (1 + jcp.dilate_d); } }); } /* col[ic][kh][kw][oh][ow] <-- im2col(im[ic][ih][iw]) */ void im2col(const jit_gemm_conv_conf_t &jcp, const float *__restrict im, float *__restrict col, int hs, int hb, int ws, int wb) { const size_t im_step = jcp.is; const size_t col_step = jcp.ks * hb * wb; if (jcp.stride_w == 1) { // Generated code is more optimized for stride_w == 1 // because innermost loop is by width auto ker = [&](int ic, int kh, int kw, int oh) { const float *__restrict im_ = im + ic * im_step; float *__restrict col_ = col + ic * col_step + ((kh * jcp.kw + kw) * hb + oh) * wb; const int ih = (oh + hs) * jcp.stride_h - jcp.t_pad + kh * (1 + jcp.dilate_h); if (ih < 0 || ih >= jcp.ih) { for (int ow = 0; ow < wb; ++ow) col_[ow] = 0.f; } else { for (int ow = 0; ow < wb; ++ow) { const int iw = ow + ws - jcp.l_pad + kw * (1 + jcp.dilate_w); if (iw < 0 || iw >= jcp.iw) col_[ow] = 0.f; else { const size_t im_idx = ih * jcp.iw + iw; col_[ow] = im_[im_idx]; } } } }; if (jcp.outer_threading) { for (int ic = 0; ic < jcp.ic; ic++) for (int kh = 0; kh < jcp.kh; kh++) for (int kw = 0; kw < jcp.kw; kw++) for (int oh = 0; oh < hb; oh++) ker(ic, kh, kw, oh); } else { parallel_nd(jcp.ic, jcp.kh, jcp.kw, hb, ker); } } else if (jcp.ic == 1) { parallel_nd(jcp.kh, hb, [&](int kh, int oh) { const int ih = (oh + hs) * jcp.stride_h - jcp.t_pad + kh * (1 + jcp.dilate_h); if (ih < 0 || ih >= jcp.ih) for (int kw = 0; kw < jcp.kw; ++kw) { for (int ow = 0; ow < wb; ++ow) { const size_t col_idx = ((kh * jcp.kw + kw) * hb + oh) * wb + ow; col[col_idx] = 0; } } else for (int kw = 0; kw < jcp.kw; ++kw) { for (int ow = 0; ow < wb; ++ow) { const int iw = (ow + ws) * jcp.stride_w - jcp.l_pad + kw * (1 + jcp.dilate_w); const size_t col_idx = ((kh * jcp.kw + kw) * hb + oh) * wb + ow; const size_t im_idx = ih * jcp.iw + iw; if (iw < 0 || iw >= jcp.iw) col[col_idx] = 0; else col[col_idx] = im[im_idx]; } } }); } else { parallel_nd(jcp.ic, jcp.kh, jcp.kw, hb, [&](int ic, int kh, int kw, int oh) { const float *__restrict im_ = im + ic * im_step; float *__restrict col_ = col + ic * col_step + ((kh * jcp.kw + kw) * hb + oh) * wb; const int ih = (oh + hs) * jcp.stride_h - jcp.t_pad + kh * (1 + jcp.dilate_h); if (ih < 0 || ih >= jcp.ih) { for (int ow = 0; ow < wb; ++ow) col_[ow] = 0.f; } else { for (int ow = 0; ow < wb; ++ow) { const int iw = (ow + ws) * jcp.stride_w - jcp.l_pad + kw * (1 + jcp.dilate_w); const size_t im_idx = ih * jcp.iw + iw; if (iw < 0 || iw >= jcp.iw) col_[ow] = 0.f; else col_[ow] = im_[im_idx]; } } }); } } inline int limit(int low, int upper, int value) { return nstl::max(low, nstl::min(upper, value)); } /* col[kh][kw][ic][oh][ow] <-- im2col_u8(im[ih][iw][ic]) */ template void im2col_u8(const jit_gemm_conv_conf_t &jcp, const T *__restrict im, T *__restrict imtr, uint8_t *__restrict col, int hs, int hb, int ws, int wb) { uint8_t shift = jcp.signed_input ? 128 : 0; const int dh = 1 + jcp.dilate_h; const int dw = 1 + jcp.dilate_w; const int sh = jcp.stride_h; const int sw = jcp.stride_w; const int im_iw_stride = jcp.ic * jcp.ngroups; const int im_ih_stride = jcp.iw * im_iw_stride; const int tp = jcp.t_pad; const int lp = jcp.l_pad; if (jcp.outer_threading && sh == 1 && sw == 1 && dh == 1 && dw == 1) { /* im[ih][iw][ic] --> imtr[ic][ih][iw] --> col[kh][kw][ic][oh][ow] */ const int hp = hs - tp; const int wp = ws - lp; const int ih_start = limit(0, jcp.ih, hp); const int ih_end = limit(0, jcp.ih, hp + hb + jcp.kh); const int iw_start = limit(0, jcp.iw, wp); const int iw_end = limit(0, jcp.iw, wp + wb + jcp.kw); const int ihb = ih_end - ih_start; const int iwb = iw_end - iw_start; const int imtr_ic_stride = ihb * iwb; const ptrdiff_t imtr_idx_shift = ih_start * iwb + iw_start; for (int ic = 0; ic < jcp.ic; ic++) { const ptrdiff_t imtr_idx_ic = ic * imtr_ic_stride - imtr_idx_shift; for (int ih = ih_start; ih < ih_end; ih++) { const ptrdiff_t im_idx_ih = ic + ih * im_ih_stride; const ptrdiff_t imtr_idx_ih = imtr_idx_ic + ih * iwb; for (int iw = iw_start; iw < iw_end; iw++) imtr[imtr_idx_ih + iw] = im[im_idx_ih + iw * im_iw_stride]; } } const int col_ic_str = hb * wb; const int col_kw_stride = jcp.ic * col_ic_str; const int col_kh_stride = jcp.kw * col_kw_stride; const int oh_init = ih_start - hp; const int ow_init = iw_start - wp; for (int kh = 0; kh < jcp.kh; kh++) { const ptrdiff_t col_idx_kh = kh * col_kh_stride; const int oh_kh = oh_init - kh; const int oh_start = limit(0, hb, oh_kh); const int oh_end = limit(0, hb, oh_kh + ihb); for (int kw = 0; kw < jcp.kw; kw++) { const ptrdiff_t col_idx_kw = col_idx_kh + kw * jcp.ic * col_ic_str; const int ow_kw = ow_init - kw; const int imtr_shift = oh_kh * iwb + ow_kw; const int ow_start = limit(0, wb, ow_kw); const int ow_end = limit(0, wb, ow_kw + iwb); for (int ic = 0; ic < jcp.ic; ic++) { const ptrdiff_t col_idx_ic = col_idx_kw + ic * col_ic_str; const int imtr_idx_ic = ic * imtr_ic_stride - imtr_shift; for (int oh = 0; oh < oh_start; oh++) { const ptrdiff_t col_idx_oh = col_idx_ic + oh * wb; for (int ow = 0; ow < wb; ++ow) col[col_idx_oh + ow] = shift; } for (int oh = oh_start; oh < oh_end; oh++) { const ptrdiff_t col_idx_oh = col_idx_ic + oh * wb; const ptrdiff_t imtr_idx_oh = imtr_idx_ic + oh * iwb; for (int ow = 0; ow < ow_start; ++ow) col[col_idx_oh + ow] = shift; for (int ow = ow_start; ow < ow_end; ++ow) col[col_idx_oh + ow] = imtr[imtr_idx_oh + ow] + shift; for (int ow = ow_end; ow < wb; ++ow) col[col_idx_oh + ow] = shift; } for (int oh = oh_end; oh < hb; oh++) { const ptrdiff_t col_idx_oh = col_idx_ic + oh * wb; for (int ow = 0; ow < wb; ++ow) col[col_idx_oh + ow] = shift; } } } } } else { parallel_nd(jcp.kh, jcp.kw, jcp.ic, hb, [&](int kh, int kw, int ic, int oh) { const int hp = tp - kh * dh; const int ih = (oh + hs) * sh - hp; const ptrdiff_t col_idx_base = (((kh * jcp.kw + kw) * jcp.ic + ic) * hb + oh) * wb; if (ih < 0 || ih >= jcp.ih) for (int ow = 0; ow < wb; ow++) col[col_idx_base + ow] = shift; else { const int wp = lp - kw * dw; const int ow_start = limit(0, wb, div_up(wp, sw) - ws); const int ow_end = limit(0, wb, div_up(jcp.iw + wp, sw) - ws); for (int ow = 0; ow < ow_start; ow++) col[col_idx_base + ow] = shift; const int iw_base = ws * sw - wp; const ptrdiff_t im_idx_base = ih * im_ih_stride + ic; for (int ow = ow_start; ow < ow_end; ow++) { const int iw = iw_base + ow * sw; const ptrdiff_t im_idx = im_idx_base + iw * im_iw_stride; col[col_idx_base + ow] = im[im_idx] + shift; } for (int ow = ow_end; ow < wb; ow++) col[col_idx_base + ow] = shift; } }); } } template void im2col_u8(const jit_gemm_conv_conf_t &jcp, const int8_t *__restrict im, int8_t *__restrict imtr, uint8_t *__restrict col, int hs, int hb, int ws, int wb); template void im2col_u8(const jit_gemm_conv_conf_t &jcp, const uint8_t *__restrict im, uint8_t *__restrict imtr, uint8_t *__restrict col, int hs, int hb, int ws, int wb); /* im[ih][iw][ic] <-- col2im_s32(col[oh][ow][kh][kw][ic]) */ void col2im_s32(const jit_gemm_conv_conf_t &jcp, const int32_t *__restrict col, int32_t *__restrict im) { parallel(0, [&](const int ithr, const int nthr) { int h_nthr = nstl::min(jcp.ih, nthr); int w_nthr = nstl::min(jcp.iw, nthr / h_nthr); int h_ithr = 1, h_s = 0, h_e = 0, w_ithr = 1, w_s = 0, w_e = 0; if (ithr < h_nthr * w_nthr) { h_ithr = ithr / w_nthr; w_ithr = ithr % w_nthr; balance211(jcp.ih, h_nthr, h_ithr, h_s, h_e); balance211(jcp.iw, w_nthr, w_ithr, w_s, w_e); } else { h_ithr = w_ithr = -ithr; h_s = h_e = w_s = w_e = -1; } for (int ih = h_s; ih < h_e; ++ih) { for (int iw = w_s; iw < w_e; ++iw) { PRAGMA_OMP_SIMD() for (int ic = 0; ic < jcp.ic; ++ic) { im[(ih * jcp.iw + iw) * jcp.ic + ic] = 0; } } } // TODO: reduce region: [0.. oh] --> [h_s * sh .. h_e * sh] for (int oh = 0; oh < jcp.oh; ++oh) { for (int ow = 0; ow < jcp.ow; ++ow) { for (int kh = 0; kh < jcp.kh; ++kh) { const int ih = oh * jcp.stride_h - jcp.t_pad + kh * (1 + jcp.dilate_h); if (ih < h_s || ih >= h_e) continue; for (int kw = 0; kw < jcp.kw; ++kw) { const int iw = ow * jcp.stride_w - jcp.l_pad + kw * (1 + jcp.dilate_w); if (iw < w_s || iw >= w_e) continue; const size_t col_idx = (((oh * jcp.ow + ow) * jcp.kh + kh) * jcp.kw + kw) * jcp.ic; const size_t im_idx = (ih * jcp.iw + iw) * jcp.ic; PRAGMA_OMP_SIMD() for (int ic = 0; ic < jcp.ic; ++ic) { im[im_idx + ic] += col[col_idx + ic]; } } } } } }); } void col2im_3d(const jit_gemm_conv_conf_t &jcp, const float *col, float *im, int od) { parallel_nd(jcp.ic, [&](int ic) { const float *__restrict col_ = col + (size_t)ic * jcp.ks * jcp.os; float *__restrict im_ic = im + (size_t)ic * jcp.ih * jcp.iw * jcp.id; int id = od * jcp.stride_d - jcp.f_pad; for (int kd = 0; kd < jcp.kd; ++kd) { if (id < 0 || id >= jcp.id) { col_ += jcp.kh * jcp.kw * jcp.os; id += (1 + jcp.dilate_d); continue; } float *__restrict im_ = im_ic + id * jcp.ih * jcp.iw; for (int oh = 0; oh < jcp.oh; ++oh) { for (int kh = 0; kh < jcp.kh; ++kh) { const int ih = oh * jcp.stride_h - jcp.t_pad + kh * (1 + jcp.dilate_h); if (ih < 0 || ih >= jcp.ih) continue; for (int ow = 0; ow < jcp.ow; ++ow) { for (int kw = 0; kw < jcp.kw; ++kw) { const int iw = ow * jcp.stride_w - jcp.l_pad + kw * (1 + jcp.dilate_w); if (iw < 0 || iw >= jcp.iw) continue; const size_t col_idx = ((kh*jcp.kw + kw)*jcp.oh+oh)*jcp.ow+ow; const size_t im_idx = ih*jcp.iw + iw; im_[im_idx] += col_[col_idx]; }} }} col_ += jcp.kh * jcp.kw * jcp.os; id += (1 + jcp.dilate_d); } }); } void col2im(const jit_gemm_conv_conf_t &jcp, const float *col, float *im) { const size_t col_step = jcp.ks * jcp.os; const size_t im_step = jcp.ih * jcp.iw; const int iS = jcp.ih * jcp.iw; parallel_nd(jcp.ic, [&](int ic) { float *__restrict im_ = im + ic * im_step; const float *__restrict col_ = col + ic * col_step; PRAGMA_OMP_SIMD() for (int is = 0; is < iS; ++is) im_[is] = 0.; for (int kh = 0; kh < jcp.kh; ++kh) { for (int oh = 0; oh < jcp.oh; ++oh) { const int ih = oh * jcp.stride_h - jcp.t_pad + kh * (1 + jcp.dilate_h); if (ih < 0 || ih >= jcp.ih) continue; for (int kw = 0; kw < jcp.kw; ++kw) { for (int ow = 0; ow < jcp.ow; ++ow) { const int iw = ow * jcp.stride_w - jcp.l_pad + kw * (1 + jcp.dilate_w); if (iw < 0 || iw >= jcp.iw) continue; const size_t col_idx = ((kh*jcp.kw + kw)*jcp.oh+oh)*jcp.ow+ow; const size_t im_idx = ih*jcp.iw + iw; im_[im_idx] += col_[col_idx]; } } } } }); } status_t init_conf(jit_gemm_conv_conf_t &jcp, memory_tracking::registrar_t &scratchpad, const convolution_desc_t &cd, const memory_desc_wrapper &src_d, const memory_desc_wrapper &weights_d, const memory_desc_wrapper &dst_d, int max_threads) { const bool with_groups = weights_d.ndims() == src_d.ndims() + 1; const int ndims = src_d.ndims(); const int is_1d = ndims == 3; const int is_3d = ndims == 5; jcp.prop_kind = cd.prop_kind; jcp.ngroups = with_groups ? weights_d.dims()[0] : 1; jcp.mb = src_d.dims()[0]; jcp.oc = dst_d.dims()[1] / jcp.ngroups; jcp.ic = src_d.dims()[1] / jcp.ngroups; jcp.id = is_3d ? src_d.dims()[2] : 1; jcp.ih = is_1d ? 1 : src_d.dims()[ndims - 2]; jcp.iw = src_d.dims()[ndims - 1]; jcp.od = is_3d ? dst_d.dims()[2] : 1; jcp.oh = is_1d ? 1 : dst_d.dims()[ndims - 2]; jcp.ow = dst_d.dims()[ndims - 1]; jcp.kd = is_3d ? weights_d.dims()[with_groups + 2] : 1; jcp.kh = is_1d ? 1 : weights_d.dims()[with_groups + ndims - 2]; jcp.kw = weights_d.dims()[with_groups + ndims - 1]; jcp.f_pad = is_3d ? cd.padding[0][0] : 0; jcp.t_pad = is_1d ? 0 : cd.padding[0][ndims - 4]; jcp.l_pad = cd.padding[0][ndims - 3]; jcp.stride_d = is_3d ? cd.strides[0] : 1; jcp.stride_h = is_1d ? 1 : cd.strides[ndims - 4]; jcp.stride_w = cd.strides[ndims - 3]; jcp.dilate_d = is_3d ? cd.dilates[0] : 0; jcp.dilate_h = is_1d ? 0 : cd.dilates[ndims - 4]; jcp.dilate_w = cd.dilates[ndims - 3]; jcp.with_bias = cd.bias_desc.format_kind != format_kind::undef || cd.diff_bias_desc.format_kind != format_kind::undef; jcp.is = jcp.ih * jcp.iw; jcp.os = jcp.oh * jcp.ow; jcp.ks = jcp.kh * jcp.kw * jcp.kd; jcp.signed_input = src_d.data_type() == data_type::s8; jcp.im2col_sz = !everyone_is(true, jcp.ow == jcp.iw, jcp.oh == jcp.ih, jcp.od == jcp.id, jcp.stride_w == 1, jcp.stride_h == 1, jcp.stride_d == 1, jcp.ks == 1, !jcp.signed_input) ? (ptrdiff_t)jcp.ic * jcp.ks * jcp.os : 0; jcp.outer_threading = false; bool is_int8_conv = utils::one_of(src_d.data_type(), s32, s8, u8) && weights_d.data_type() == s8; const int vlen = mayiuse(avx512_common) ? cpu_isa_traits::vlen : mayiuse(avx) ? cpu_isa_traits::vlen : mayiuse(sse42) ? cpu_isa_traits::vlen : 4; const int simd_w = vlen / (is_int8_conv ? 1 : 4); const bool is_bwd_d = jcp.prop_kind == backward_data; const bool is_bwd_w = jcp.prop_kind == backward_weights; const bool is_fwd = !is_bwd_d && !is_bwd_w; jcp.oh_block = is_fwd ? jcp.oh : jcp.ih; jcp.ow_block = is_fwd ? jcp.ow : jcp.iw; using namespace memory_tracking::names; bool is_depthwise = jcp.ic == 1 && jcp.oc == 1 && jcp.ngroups != 1; // TODO: maybe mitigate blocking restriction const int wei_size = jcp.oc * jcp.ic * jcp.kh * jcp.kw; const int L2 = get_cache_size(2, true) / (is_int8_conv ? sizeof(int8_t) : sizeof(float)); bool is_blocking_applicable = true && is_fwd && jcp.im2col_sz && jcp.id == 1 && jcp.od == 1 && jcp.dilate_h == 0 && jcp.dilate_w == 0 && !is_depthwise && wei_size < L2/2; if (is_blocking_applicable) { // looking for oh and ow blocking int h_block{ jcp.oh_block }, w_block{ jcp.ow_block }; const int ic = jcp.ic; const int oc = jcp.oc; const int iw = jcp.iw; const int ow = jcp.ow; const int oh = jcp.oh; const int os = oh * ow; // 1. cache requirement int row_size = ic * ow * jcp.ks + 2 * (ic * iw + oc * ow); if (is_int8_conv) { // Heuristic rule: gemm needed a lot of memory for internal usage row_size *= 5; // memory for accumulators row_size += oc * ow * sizeof(uint32_t); // memory for transposition row_size += ic * iw; } h_block = nstl::max(1, nstl::min(oh, div_up(L2, row_size))); if (h_block == 1) { int col_size = ic * jcp.ks + 2 * (ic + oc); if (is_int8_conv) { col_size *= 5; col_size += oc * sizeof(uint32_t); col_size += ic; } w_block = nstl::max(1, nstl::min(ow, div_up(L2, col_size))); } // 2. threading requirement if (h_block != oh) h_block = nstl::max(1, rnd_dn(h_block, 4)); if (w_block != ow) w_block = nstl::max(1, rnd_dn(w_block, simd_w)); float thr_eff = 0.f; float thr_eff_treshold = 0.9f; if (w_block == ow) { do { int nb_h = div_up(oh, h_block); size_t work = jcp.ngroups * jcp.mb * jcp.od * nb_h; float disb = (float)oh / rnd_up(oh, h_block); thr_eff = (float)work / rnd_up(work, max_threads); thr_eff = (thr_eff + disb) / 2.f; if (thr_eff >= thr_eff_treshold) break; h_block = rnd_dn(h_block - 4, 4); } while (h_block > 0); } if (thr_eff < thr_eff_treshold) // we didn't find suitable h_block { h_block = 1; int nb_h = oh; do { int nb_w = div_up(ow, w_block); size_t work_amount = jcp.ngroups * jcp.mb * nb_h * nb_w; float disb = (float)ow / rnd_up(ow, w_block); thr_eff = (float)work_amount / rnd_up(work_amount, max_threads); thr_eff = (thr_eff + disb) / 2.f; if (thr_eff > thr_eff_treshold) break; w_block = rnd_dn(w_block - simd_w, simd_w); } while (w_block > 0); } h_block = nstl::max(1, h_block); w_block = nstl::max(1, w_block); const size_t inner_work = div_up(os, simd_w) * div_up(oc, simd_w); const float inner_thr_eff = (float)inner_work / rnd_up(inner_work, max_threads); if (thr_eff >= inner_thr_eff / 2 && h_block > 0 && w_block > 0) { jcp.oh_block = h_block; jcp.ow_block = w_block; jcp.outer_threading = true; } // updating jcp.im2col_sz if (jcp.oh_block != 1) jcp.ow_block = ow; jcp.im2col_sz = (ptrdiff_t)ic * jcp.ks * jcp.oh_block * jcp.ow_block; } // For threading selection in bwd_d we do: // 1. Rough estimation of efficiency for inner and outer threading. // 2. Gemm size estimation in assumption that it does not work // so effectively for small sizes. // 64K - this is heuristic gemm size per thread threshold. const int gemm_thrld = 64 * 1024; if (is_int8_conv) { if (is_fwd) { if (!jcp.outer_threading) { bool is_depthwise = jcp.ic == 1 && jcp.oc == 1 && jcp.ngroups != 1; const size_t outer_work = jcp.ngroups * jcp.mb; const float outer_thr_eff = (float)outer_work / rnd_up(outer_work, max_threads); const size_t inner_work = div_up(jcp.is, simd_w) * div_up(jcp.ic, simd_w); const float inner_thr_eff = (float)inner_work / rnd_up(inner_work, max_threads); jcp.outer_threading = (is_depthwise || (jcp.is / max_threads < 64 && jcp.mb != 1)) && (outer_thr_eff / inner_thr_eff >= 1.f || (jcp.os * jcp.ic * jcp.oc) / max_threads < gemm_thrld); } jcp.nthr = jcp.outer_threading ? max_threads : 1; scratchpad.book(key_conv_gemm_col, sizeof(int8_t) * jcp.nthr * jcp.im2col_sz); scratchpad.book(key_conv_int_dat_in_acc_dt, sizeof(int32_t) * jcp.nthr * jcp.oh_block * jcp.ow_block * jcp.oc); scratchpad.book(key_conv_gemm_imtr, sizeof(int8_t) * jcp.nthr * jcp.is * jcp.ic); } else if (is_bwd_d) { bool is_depthwise = jcp.ic == 1 && jcp.oc == 1 && jcp.ngroups != 1; const size_t outer_work = jcp.ngroups * jcp.mb; const float outer_thr_eff = (float)outer_work / rnd_up(outer_work, max_threads); const size_t inner_work = div_up(jcp.is, simd_w) * div_up(jcp.ic, simd_w); const float inner_thr_eff = (float)inner_work / rnd_up(inner_work, max_threads); jcp.outer_threading = (is_depthwise || (jcp.is / max_threads < 64 && jcp.mb != 1)) && (outer_thr_eff / inner_thr_eff >= 1.f || (jcp.is * jcp.ic * jcp.oc) / max_threads < gemm_thrld); jcp.nthr = jcp.outer_threading ? max_threads : 1; scratchpad.book(key_conv_gemm_col, sizeof(int32_t) * jcp.nthr * jcp.im2col_sz); scratchpad.book(key_conv_int_dat_in_acc_dt, sizeof(int32_t) * jcp.nthr * jcp.is * jcp.ic); } else if (is_bwd_w) { assert(!"unimplemented prop_kind"); return status::unimplemented; } } else { if (is_fwd) { if (!jcp.outer_threading) { const size_t outer_work_amount = jcp.ngroups * jcp.mb * jcp.od; const float outer_thr_eff = (float)outer_work_amount / rnd_up(outer_work_amount, max_threads); const size_t inner_work_amount = div_up(jcp.os, simd_w) * div_up(jcp.oc, simd_w); const float inner_thr_eff = (float)inner_work_amount / rnd_up(inner_work_amount, max_threads); jcp.outer_threading = jcp.os / max_threads < 512 && IMPLICATION(jcp.od == 1, jcp.mb != 1 || jcp.ngroups > 2) && (outer_thr_eff / inner_thr_eff >= 1.f || (jcp.os * jcp.ic * jcp.oc) / max_threads < gemm_thrld); } } else if (is_bwd_d) { const size_t outer_work_amount = jcp.ngroups * jcp.mb; const float outer_thr_eff = (float)outer_work_amount / rnd_up(outer_work_amount, max_threads); const size_t inner_work = div_up(jcp.is, simd_w) * div_up(jcp.ic, simd_w); const float inner_thr_eff = (float)inner_work / rnd_up(inner_work, max_threads); jcp.outer_threading = (jcp.os / max_threads < 512 || jcp.ks < 64) && (jcp.mb != 1 || jcp.ngroups > 2) && (outer_thr_eff / inner_thr_eff >= 1.f || (jcp.is * jcp.ic * jcp.oc) / max_threads < gemm_thrld); } else if (is_bwd_w) jcp.outer_threading = jcp.os / max_threads < 256 && (jcp.mb != 1 || jcp.ngroups > 2); jcp.nthr = jcp.outer_threading ? max_threads : 1; scratchpad.book(key_conv_gemm_col, sizeof(float) * jcp.nthr * jcp.im2col_sz); if (is_bwd_w) { jcp.need_wei_reduction = mkldnn_thr_syncable() ? jcp.mb != 1 && jcp.nthr != 1 : false; scratchpad.book(key_conv_wei_reduction, sizeof(float) * jcp.nthr * jcp.ngroups * weights_d.size()); } } return status::success; } void bwd_weights_balance(int ithr, int nthr, int ngroups, int mb, int &ithr_g, int &nthr_g, int &ithr_mb, int &nthr_mb) { nthr_g = nstl::min(ngroups, nthr); nthr_mb = nstl::min(mb, nthr / nthr_g); if (ithr / nthr_mb >= ngroups) { ithr_g = ithr_mb = -1; } else { ithr_g = ithr / nthr_mb; ithr_mb = ithr % nthr_mb; } } void bwd_weights_reduction_par(int ithr, int nthr, const jit_gemm_conv_conf_t &jcp, const float *weights_reduce_ws, float *weights) { const size_t weights_g_size = jcp.ic * jcp.oc * jcp.ks; size_t weights_start{0}, weights_end{0}; balance211(weights_g_size, nthr, ithr, weights_start, weights_end); for (int i = 0; i < nthr; ++i) { const float *ws_i = weights_reduce_ws + i * weights_g_size; for (size_t s = weights_start; s < weights_end; ++s) weights[s] = (i == 0 ? 0 : weights[s]) + ws_i[s]; } } }; } } }