| /* |
| * Copyright (c) 2023 Arm Limited. |
| * |
| * SPDX-License-Identifier: MIT |
| * |
| * Permission is hereby granted, free of charge, to any person obtaining a copy |
| * of this software and associated documentation files (the "Software"), to |
| * deal in the Software without restriction, including without limitation the |
| * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or |
| * sell copies of the Software, and to permit persons to whom the Software is |
| * furnished to do so, subject to the following conditions: |
| * |
| * The above copyright notice and this permission notice shall be included in all |
| * copies or substantial portions of the Software. |
| * |
| * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR |
| * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, |
| * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE |
| * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER |
| * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, |
| * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE |
| * SOFTWARE. |
| */ |
| #include "src/runtime/heuristics/matmul_native/ClMatMulNativeHelpers.h" |
| |
| #include "arm_compute/core/KernelDescriptors.h" |
| #include "arm_compute/core/TensorInfo.h" |
| #include "arm_compute/core/TensorShape.h" |
| #include "src/gpu/cl/kernels/ClMatMulNativeKernel.h" |
| |
| #include <limits> |
| #include <utility> |
| |
| namespace arm_compute |
| { |
| namespace cl_matmul |
| { |
| MatMulKernelInfo select_info(const MatMulKernelInfo &info0, |
| const MatMulKernelInfo &info1, |
| unsigned int m, unsigned int n, unsigned int k, unsigned int b, DataType data_type, bool rhs_lock_padding) |
| { |
| ARM_COMPUTE_ERROR_ON_MSG(info1.export_rhs_to_cl_image == true, "The fallback MatMul configuration cannot have export_to_cl_image = true"); |
| ARM_COMPUTE_ERROR_ON_MSG(info0.adj_lhs != info1.adj_lhs, "The MatMul configurations must have the same adj_lhs value"); |
| ARM_COMPUTE_ERROR_ON_MSG(info0.adj_rhs != info1.adj_rhs, "The MatMul configurations must have the same adj_rhs value"); |
| |
| const bool adj_lhs = info0.adj_lhs; |
| const bool adj_rhs = info0.adj_rhs; |
| |
| TensorInfo lhs_info = !adj_lhs ? TensorInfo(TensorShape(k, m, b), 1, data_type) : TensorInfo(TensorShape(m, k, b), 1, data_type); |
| TensorInfo rhs_info = !adj_rhs ? TensorInfo(TensorShape(n, k, b), 1, data_type) : TensorInfo(TensorShape(k, n, b), 1, data_type); |
| TensorInfo dst_info; |
| |
| if(rhs_lock_padding == false) |
| { |
| if(bool(opencl::kernels::ClMatMulNativeKernel::validate(&lhs_info, &rhs_info, &dst_info, info0))) |
| { |
| return info0; |
| } |
| else |
| { |
| return info1; |
| } |
| } |
| else |
| { |
| return info1; |
| } |
| } |
| |
| MatMulKernelInfo find_info(const MatMulNativeConfigsMatrix &configs, bool adj_lhs, bool adj_rhs, unsigned int m, unsigned int n, unsigned int k, unsigned int b) |
| { |
| size_t min_acc = std::numeric_limits<size_t>::max(); |
| size_t min_idx = 0; |
| |
| ARM_COMPUTE_ERROR_ON(configs.size() == 0); |
| const size_t num_rows = configs.size(); |
| const size_t num_cols = configs[0].size(); |
| |
| ARM_COMPUTE_ERROR_ON_MSG(num_cols != 8U, "The entry should have 8 integer values representing: M, N, K, B, M0, N0. K0, IMG_RHS"); |
| ARM_COMPUTE_UNUSED(num_cols); |
| |
| // Find nearest GeMM workload |
| // Note: the workload does not depend on the K dimension |
| for(size_t y = 0; y < num_rows; ++y) |
| { |
| size_t mc0 = static_cast<size_t>(configs[y][0]); |
| size_t nc0 = static_cast<size_t>(configs[y][1]); |
| size_t kc0 = static_cast<size_t>(configs[y][2]); |
| size_t bc0 = static_cast<size_t>(configs[y][3]); |
| |
| size_t acc = 0; |
| acc += (m - mc0) * (m - mc0); |
| acc += (n - nc0) * (n - nc0); |
| acc += (k - kc0) * (k - kc0); |
| acc += (b - bc0) * (b - bc0); |
| acc = std::sqrt(acc); |
| if(acc < min_acc) |
| { |
| min_acc = acc; |
| min_idx = y; |
| } |
| } |
| |
| // Get the configuration from the nearest GeMM shape |
| MatMulKernelInfo desc; |
| desc.adj_lhs = adj_lhs; |
| desc.adj_rhs = adj_rhs; |
| desc.m0 = configs[min_idx][4]; |
| desc.n0 = configs[min_idx][5]; |
| desc.k0 = configs[min_idx][6]; |
| desc.export_rhs_to_cl_image = configs[min_idx][7]; |
| |
| return desc; |
| } |
| } // namespace cl_matmul |
| } // namespace arm_compute |