diff options
Diffstat (limited to 'compute/ncnn/src/srcn/conv_sgemm_singlethread.cc')
-rw-r--r-- | compute/ncnn/src/srcn/conv_sgemm_singlethread.cc | 366 |
1 files changed, 366 insertions, 0 deletions
diff --git a/compute/ncnn/src/srcn/conv_sgemm_singlethread.cc b/compute/ncnn/src/srcn/conv_sgemm_singlethread.cc new file mode 100644 index 000000000..4cbbf217f --- /dev/null +++ b/compute/ncnn/src/srcn/conv_sgemm_singlethread.cc @@ -0,0 +1,366 @@ +/* + * Copyright (c) 2019 Samsung Electronics Co., Ltd. All Rights Reserved + * + * 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 <stdexcept> + +#include "common.h" +#include "sgemm_kernel.h" +#include "sgemm_pack.h" +#include "conv_sgemm_singlethread.h" + +namespace nnfw +{ +namespace srcn +{ + +void conv_sgemm_singlethread::param_init() +{ + if (n_ > 3 * m_) + { + shard_type_ = shardByRow; + } + else + { + shard_type_ = shardByCol; + } + +#if __aarch64__ + if (conv_type_ == row_major) + { + if (shard_type_ == shardByRow) + { + mr_ = 8; + nr_ = 12; + } + else + { + mr_ = 12; + nr_ = 8; + } + } + else if (conv_type_ == col_major) + { +#ifndef BATCH_DILATION_FIX + mr_ = 12; + nr_ = 8; +#else // BATCH_DILATION_FIX + // TODO: batch(dilation) + inw * inh + if (out_mat_.n > 1) + { + mr_ = 24; + nr_ = 4; + } + else + { + mr_ = 12; + nr_ = 8; + } +#endif // BATCH_DILATION_FIX + } +#else // __aarch64__ + if (conv_type_ == row_major) + { + mr_ = 6; + nr_ = 8; + } + else if (conv_type_ == col_major) + { + mr_ = 8; + nr_ = 6; + } +#endif // __aarch64__ + + int k_div = (nr_ * sizeof_RhsScalar); + int k_sub = (mr_ * nr_ * sizeof_ResScalar); + + const int k_cache = MIN(divup((int)(L1_CACHE_SIZE - k_sub), (int)k_div), MAX_K); + bk_ = MIN(k_cache, k_); + + if (shard_type_ == shardByCol) + { + int m_sub = (bk_ * nr_ * sizeof_RhsScalar); + int m_cache = divup((L2_CACHE_SIZE - m_sub), (sizeof_LhsScalar * bk_ * 2)); + bm_ = MIN(m_cache, m_); + + bn_ = MIN(GEN_COL, n_); + if (L3_CACHE_SIZE) + { + int n_sub = (bk_ * bm_ * sizeof_RhsScalar); + int n_cache = divup((L3_CACHE_SIZE - n_sub), (sizeof_LhsScalar * bk_ * 2)); + bn_ = MIN(n_cache, bn_); + } + } + else + { + int n_sub = (bk_ * mr_ * sizeof_RhsScalar); + int n_cache = divup((L2_CACHE_SIZE - n_sub), (sizeof_LhsScalar * bk_ * 2)); + bn_ = MIN(n_cache, n_); + + bm_ = MIN(GEN_COL, m_); + if (L3_CACHE_SIZE) + { + int m_sub = (bk_ * bn_ * sizeof_RhsScalar); + int m_cache = divup((L3_CACHE_SIZE - m_sub), (sizeof_LhsScalar * bk_ * 2)); + bm_ = MIN(m_cache, bm_); + } + } + + nm_ = divup(m_, bm_); + nn_ = divup(n_, bn_); + nk_ = divup(k_, bk_); + + rm_ = m_ % bm_; + rn_ = n_ % bn_; + rk_ = k_ % bk_; +} + +conv_sgemm_singlethread::conv_sgemm_singlethread(const convMat_t &in_mat, + const convMat_t &weights_mat, convMat_t &out_mat, + const convParams_t &in_param, convType_t conv_type) + : in_mat_(in_mat), weights_mat_(weights_mat), out_mat_(out_mat), in_param_(in_param), + conv_type_(conv_type) +{ + m_ = out_mat_.c; +#ifdef NCNN + n_ = out_mat_.n * alignSize(out_mat_.h * out_mat_.w, 16 / sizeof(float)); +#else + n_ = out_mat_.n * out_mat_.w * out_mat_.h; +#endif + k_ = in_param_.kernel_h * in_param_.kernel_w * in_mat.c; + + param_init(); + + if (in_param_.kernel_w != 1 || in_param_.kernel_h != 1 || in_param_.stride_w != 1 || + in_param_.stride_h != 1 || in_param_.padding != 0 || out_mat_.n > 1) + { + need_im2col_ = 1; + } + else + { + need_im2col_ = 0; + } +} + +conv_sgemm_singlethread::~conv_sgemm_singlethread() {} + +void conv_sgemm_singlethread::run() +{ + int mstride = (bm_ + mr_ - 1) / mr_ * mr_; + int nstride = (bn_ + nr_ - 1) / nr_ * nr_; + + float *plhs_ptr = new float[mstride * bk_]; + float *prhs_ptr = new float[nstride * bk_]; + + if (conv_type_ == row_major) + { + if (shard_type_ == shardByCol) + { + for (int j = 0; j < nn_; j++) + { + const int bn = (j != nn_ - 1 || rn_ == 0) ? bn_ : rn_; + + for (int l = 0; l < nk_; l++) + { + const int bk = (l != nk_ - 1 || rk_ == 0) ? bk_ : rk_; + + if (need_im2col_) + { + if (out_mat_.n == 1) + { + _pack_rowmajor_image_rhs(nr_, bn, bk, l * bk_, j * bn_, + const_cast<convMat_t *>(&in_mat_), &out_mat_, + const_cast<convParams_t *>(&in_param_), prhs_ptr); + } + else + { + _pack_rowmajor_image_rhs_batch(nr_, bn, bk, l * bk_, j * bn_, + const_cast<convMat_t *>(&in_mat_), &out_mat_, + const_cast<convParams_t *>(&in_param_), prhs_ptr); + } + } + else + { + _pack_rowmajor_notrans_rhs(nr_, bn, bk, n_, &in_mat_.data[l * bk_ * n_ + j * bn_], + prhs_ptr); + } + + for (int i = 0; i < nm_; i++) + { + const int bm = (i != nm_ - 1 || rm_ == 0) ? bm_ : rm_; + + _pack_rowmajor_notrans_lhs(mr_, bm, bk, k_, &weights_mat_.data[i * bm_ * k_ + l * bk_], + plhs_ptr); + + _sgemm_rowmajor_macro_kernel_divnm(mr_, nr_, bm, bn, bk, plhs_ptr, prhs_ptr, + &out_mat_.data[i * bm_ * n_ + j * bn_], l, n_, bk); + } + } + } + } + else if (shard_type_ == shardByRow) + { + for (int i = 0; i < nm_; i++) + { + const int bm = (i != nm_ - 1 || rm_ == 0) ? bm_ : rm_; + + for (int l = 0; l < nk_; l++) + { + const int bk = (l != nk_ - 1 || rk_ == 0) ? bk_ : rk_; + + _pack_rowmajor_notrans_lhs(mr_, bm, bk, k_, &weights_mat_.data[i * bm_ * k_ + l * bk_], + plhs_ptr); + + for (int j = 0; j < nn_; j++) + { + const int bn = (j != nn_ - 1 || rn_ == 0) ? bn_ : rn_; + + if (need_im2col_) + { + if (out_mat_.n == 1) + { + _pack_rowmajor_image_rhs(nr_, bn, bk, l * bk_, j * bn_, + const_cast<convMat_t *>(&in_mat_), &out_mat_, + const_cast<convParams_t *>(&in_param_), prhs_ptr); + } + else + { + _pack_rowmajor_image_rhs_batch(nr_, bn, bk, l * bk_, j * bn_, + const_cast<convMat_t *>(&in_mat_), &out_mat_, + const_cast<convParams_t *>(&in_param_), prhs_ptr); + } + } + else + { + _pack_rowmajor_notrans_rhs(nr_, bn, bk, n_, &in_mat_.data[l * bk_ * n_ + j * bn_], + prhs_ptr); + } + + _sgemm_rowmajor_macro_kernel_divmn(mr_, nr_, bm, bn, bk, plhs_ptr, prhs_ptr, + &out_mat_.data[i * bm_ * n_ + j * bn_], l, n_, bk); + } + } + } + } + else + { + throw std::runtime_error{"Error shrad type!"}; + } + } + else if (conv_type_ == col_major) + { + if (shard_type_ == shardByCol) + { + for (int j = 0; j < nn_; j++) + { + const int bn = (j != nn_ - 1 || rn_ == 0) ? bn_ : rn_; + for (int l = 0; l < nk_; l++) + { + const int bk = (l != nk_ - 1 || rk_ == 0) ? bk_ : rk_; + + if (need_im2col_) + { + if (out_mat_.n == 1) + { + _pack_colmajor_image_rhs(nr_, bn, bk, l * bk_, j * bn_, + const_cast<convMat_t *>(&in_mat_), &out_mat_, + const_cast<convParams_t *>(&in_param_), prhs_ptr); + } + else + { + _pack_colmajor_image_rhs_batch(nr_, bn, bk, l * bk_, j * bn_, + const_cast<convMat_t *>(&in_mat_), &out_mat_, + const_cast<convParams_t *>(&in_param_), prhs_ptr); + } + } + else + { + _pack_colmajor_notrans_rhs(nr_, bn, bk, k_, &in_mat_.data[j * bn_ * k_ + l * bk_], + prhs_ptr); + } + + for (int i = 0; i < nm_; i++) + { + const int bm = (i != nm_ - 1 || rm_ == 0) ? bm_ : rm_; + + _pack_colmajor_notrans_lhs(mr_, bm, bk, m_, &weights_mat_.data[l * bk_ * m_ + i * bm_], + plhs_ptr); + + _sgemm_colmajor_macro_kernel_divnm(mr_, nr_, bm, bn, bk, plhs_ptr, prhs_ptr, + &out_mat_.data[j * bn_ * m_ + i * bm_], l, m_, bk); + } + } + } + } + else if (shard_type_ == shardByRow) + { + for (int i = 0; i < nm_; i++) + { + const int bm = (i != nm_ - 1 || rm_ == 0) ? bm_ : rm_; + + for (int l = 0; l < nk_; l++) + { + const int bk = (l != nk_ - 1 || rk_ == 0) ? bk_ : rk_; + + _pack_colmajor_notrans_lhs(mr_, bm, bk, m_, &weights_mat_.data[l * bk_ * m_ + i * bm_], + plhs_ptr); + + for (int j = 0; j < nn_; j++) + { + const int bn = (j != nn_ - 1 || rn_ == 0) ? bn_ : rn_; + + if (need_im2col_) + { + if (out_mat_.n == 1) + { + _pack_colmajor_image_rhs(nr_, bn, bk, l * bk_, j * bn_, + const_cast<convMat_t *>(&in_mat_), &out_mat_, + const_cast<convParams_t *>(&in_param_), prhs_ptr); + } + else + { + _pack_colmajor_image_rhs_batch(nr_, bn, bk, l * bk_, j * bn_, + const_cast<convMat_t *>(&in_mat_), &out_mat_, + const_cast<convParams_t *>(&in_param_), prhs_ptr); + } + } + else + { + _pack_colmajor_notrans_rhs(nr_, bn, bk, k_, &in_mat_.data[j * bn_ * k_ + l * bk_], + prhs_ptr); + } + + _sgemm_colmajor_macro_kernel_divmn(mr_, nr_, bm, bn, bk, plhs_ptr, prhs_ptr, + &out_mat_.data[j * bn_ * m_ + i * bm_], l, m_, bk); + } + } + } + } + else + { + throw std::runtime_error{"Error shrad type!"}; + } + } + else + { + throw std::runtime_error{"Error conv type!"}; + } + + delete[] plhs_ptr; + delete[] prhs_ptr; +} + +} // namespace srcn +} // namespace nnfw |