diff options
Diffstat (limited to 'src/gpu/cl/kernels/gemm/ClGemmHelpers.cpp')
| -rw-r--r-- | src/gpu/cl/kernels/gemm/ClGemmHelpers.cpp | 64 |
1 files changed, 62 insertions, 2 deletions
diff --git a/src/gpu/cl/kernels/gemm/ClGemmHelpers.cpp b/src/gpu/cl/kernels/gemm/ClGemmHelpers.cpp index 9e7029a7ae..b97ffedfe5 100644 --- a/src/gpu/cl/kernels/gemm/ClGemmHelpers.cpp +++ b/src/gpu/cl/kernels/gemm/ClGemmHelpers.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2019-2022 Arm Limited. + * Copyright (c) 2019-2023 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -28,6 +28,7 @@ #include "arm_compute/core/CL/OpenCL.h" #include "arm_compute/core/utils/misc/ShapeCalculator.h" +#include <limits> #include <utility> namespace arm_compute @@ -42,8 +43,18 @@ std::pair<GEMMLHSMatrixInfo, GEMMRHSMatrixInfo> configure_lhs_rhs_info(unsigned bool lhs_interleave, bool rhs_interleave, bool lhs_transpose, bool rhs_transpose, bool export_to_cl_image) { ARM_COMPUTE_ERROR_ON(m0 == 0 || n0 == 0); + ARM_COMPUTE_ERROR_ON(v0 == 0); v0 = std::max(std::min(static_cast<int>(m / m0), static_cast<int>(v0)), static_cast<int>(1)); - h0 = std::max(std::min(static_cast<int>(n / n0), static_cast<int>(h0)), static_cast<int>(1)); + + if(h0 == 0) + { + // When h0 is 0, we should take the maximum H0 possible + h0 = std::max(n / n0, 1U); + } + else + { + h0 = std::max(std::min(static_cast<int>(n / n0), static_cast<int>(h0)), static_cast<int>(1)); + } const GEMMLHSMatrixInfo lhs_info(m0, k0, v0, lhs_transpose, lhs_interleave); const GEMMRHSMatrixInfo rhs_info(n0, k0, h0, rhs_transpose, rhs_interleave, export_to_cl_image); @@ -55,6 +66,8 @@ std::pair<GEMMLHSMatrixInfo, GEMMRHSMatrixInfo> select_lhs_rhs_info(std::pair<GE std::pair<GEMMLHSMatrixInfo, GEMMRHSMatrixInfo> info_buf, unsigned int n, unsigned int k, unsigned int b, DataType data_type) { + ARM_COMPUTE_ERROR_ON_MSG(info_buf.second.export_to_cl_image == true, "The fallback GeMM configuration cannot have export_to_cl_image = true"); + const TensorInfo tensor_rhs_info(TensorShape(n, k, b), 1, data_type); const TensorShape shape = misc::shape_calculator::compute_rhs_reshaped_shape(tensor_rhs_info, info_img.second); const TensorInfo tensor_reshaped_info(shape, 1, data_type); @@ -127,6 +140,53 @@ bool is_mmul_kernel_preferred(const unsigned int m, const unsigned int n, const return ((k % mmul_k0) == 0) && (gws_y > 4); } + +std::pair<GEMMLHSMatrixInfo, GEMMRHSMatrixInfo> find_lhs_rhs_info(const GeMMConfigsMatrix &configs, unsigned int m, unsigned int n, unsigned int k, unsigned int b) +{ + float min_acc = std::numeric_limits<float>::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 != 14U, "The entry should have 14 integer values representing: M, N, K, B, M0, N0. K0, V0, H0, INT_LHS, INT_RHS, TRA_LHS, TRA_RHS, IMG_RHS"); + ARM_COMPUTE_UNUSED(num_cols); + + // Find nearest GeMM shape + for(size_t y = 0; y < num_rows; ++y) + { + float mc0 = configs[y][0]; + float nc0 = configs[y][1]; + float kc0 = configs[y][2]; + float bc0 = configs[y][3]; + float acc = 0; + acc += (m - mc0) * (m - mc0); + acc += (n - nc0) * (n - nc0); + acc += (k - kc0) * (n - kc0); + acc += (b - bc0) * (n - bc0); + acc = std::sqrt(acc); + if(acc < min_acc) + { + min_acc = acc; + min_idx = y; + } + } + + // Get the configuration from the nearest GeMM shape + const int m0 = configs[min_idx][4]; + const int n0 = configs[min_idx][5]; + const int k0 = configs[min_idx][6]; + const int v0 = configs[min_idx][7]; + const int h0 = configs[min_idx][8]; + const int i_lhs = configs[min_idx][9]; + const int i_rhs = configs[min_idx][10]; + const int t_lhs = configs[min_idx][11]; + const int t_rhs = configs[min_idx][12]; + const int im_rhs = configs[min_idx][13]; + + return configure_lhs_rhs_info(m, n, m0, n0, k0, v0, h0, i_lhs, i_rhs, t_lhs, t_rhs, im_rhs); +} } // namespace gemm } // namespace kernels } // namespace opencl |