diff options
Diffstat (limited to 'src/core/gpu/cl/kernels/gemm/reshaped_only_rhs/ClGemmDefaultReshapedRhsOnlyValhall.cpp')
| -rw-r--r-- | src/core/gpu/cl/kernels/gemm/reshaped_only_rhs/ClGemmDefaultReshapedRhsOnlyValhall.cpp | 570 |
1 files changed, 570 insertions, 0 deletions
diff --git a/src/core/gpu/cl/kernels/gemm/reshaped_only_rhs/ClGemmDefaultReshapedRhsOnlyValhall.cpp b/src/core/gpu/cl/kernels/gemm/reshaped_only_rhs/ClGemmDefaultReshapedRhsOnlyValhall.cpp new file mode 100644 index 0000000000..4c6e633896 --- /dev/null +++ b/src/core/gpu/cl/kernels/gemm/reshaped_only_rhs/ClGemmDefaultReshapedRhsOnlyValhall.cpp @@ -0,0 +1,570 @@ +/* + * Copyright (c) 2020-2021 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/core/gpu/cl/kernels/gemm/reshaped_only_rhs/ClGemmDefaultConfigReshapedRhsOnlyValhall.h" + +#include "arm_compute/core/CL/CLHelpers.h" +#include "arm_compute/core/CL/CLKernelLibrary.h" +#include "arm_compute/core/GPUTarget.h" +#include "arm_compute/core/TensorInfo.h" +#include "arm_compute/core/TensorShape.h" +#include "arm_compute/core/utils/misc/ShapeCalculator.h" +#include "src/core/gpu/cl/kernels/gemm/ClGemmHelpers.h" + +#include <utility> + +namespace arm_compute +{ +namespace opencl +{ +namespace kernels +{ +namespace gemm +{ +using namespace arm_compute::misc::shape_calculator; + +ClGemmDefaultConfigReshapedRhsOnlyValhall::ClGemmDefaultConfigReshapedRhsOnlyValhall(GPUTarget gpu) + : IClGemmKernelConfig(gpu) +{ +} + +std::pair<GEMMLHSMatrixInfo, GEMMRHSMatrixInfo> ClGemmDefaultConfigReshapedRhsOnlyValhall::configure(unsigned int m, unsigned int n, unsigned int k, unsigned int b, DataType data_type) +{ + using ConfigurationFunctionExecutorPtr = std::pair<GEMMLHSMatrixInfo, GEMMRHSMatrixInfo> (ClGemmDefaultConfigReshapedRhsOnlyValhall::*)(unsigned int m, unsigned int n, unsigned int k, + unsigned int b); + + CLGEMMConfigArray<ConfigurationFunctionExecutorPtr> configs_G77(&ClGemmDefaultConfigReshapedRhsOnlyValhall::configure_G77_f32, + &ClGemmDefaultConfigReshapedRhsOnlyValhall::configure_G77_f16, + &ClGemmDefaultConfigReshapedRhsOnlyValhall::configure_G77_u8); + + CLGEMMConfigArray<ConfigurationFunctionExecutorPtr> configs_G78(&ClGemmDefaultConfigReshapedRhsOnlyValhall::configure_G78_f32, + &ClGemmDefaultConfigReshapedRhsOnlyValhall::configure_G78_f16, + &ClGemmDefaultConfigReshapedRhsOnlyValhall::configure_G77_u8); + + ConfigurationFunctionExecutorPtr func = nullptr; + + switch(_target) + { + case GPUTarget::G78: + func = configs_G78.get_function(data_type); + break; + case GPUTarget::G77: + default: + func = configs_G77.get_function(data_type); + break; + } + + ARM_COMPUTE_ERROR_ON_MSG(func == nullptr, "Data type not support for GEMM"); + return (this->*func)(m, n, k, b); +} + +std::pair<GEMMLHSMatrixInfo, GEMMRHSMatrixInfo> ClGemmDefaultConfigReshapedRhsOnlyValhall::configure_G77_f32(unsigned int m, unsigned int n, unsigned int k, unsigned int b) +{ + if(m == 1) + { + const float r_mn = static_cast<float>(m) / static_cast<float>(n); + const float r_mk = static_cast<float>(m) / static_cast<float>(k); + + if(r_mk <= 0.0064484127797186375) + { + if(r_mn <= 0.0028273810748942196) + { + GEMMLHSMatrixInfo lhs_info_buf; + GEMMRHSMatrixInfo rhs_info_buf; + GEMMLHSMatrixInfo lhs_info_img; + GEMMRHSMatrixInfo rhs_info_img; + + const unsigned int h0 = std::max(n / 4, 1U); + std::tie(lhs_info_img, rhs_info_img) = configure_lhs_rhs_info(m, n, 1, 4, 8, 1, 16, 0, 1, 0, 0, 1); + std::tie(lhs_info_buf, rhs_info_buf) = configure_lhs_rhs_info(m, n, 1, 4, 4, 1, h0, 0, 1, 0, 1, 0); + + return select_lhs_rhs_info(std::make_pair(lhs_info_img, rhs_info_img), + std::make_pair(lhs_info_buf, rhs_info_buf), + n, k, b, DataType::F32); + } + else + { + return configure_lhs_rhs_info(m, n, 1, 2, 16, 1, 8, 0, 1, 0, 0, 0); + } + } + else + { + if(r_mk <= 0.020312500186264515) + { + return configure_lhs_rhs_info(m, n, 1, 2, 16, 1, 4, 0, 1, 0, 0, 0); + } + else + { + return configure_lhs_rhs_info(m, n, 1, 4, 16, 1, 16, 0, 1, 0, 1, 0); + } + } + } + else + { + const float r_mn = static_cast<float>(m) / static_cast<float>(n); + const float workload = (static_cast<float>(m) * static_cast<float>(n) * static_cast<float>(b)) / 20.0f; + const float r_mk = static_cast<float>(m) / static_cast<float>(k); + + if(workload <= 1999.2000122070312) + { + if(workload <= 747.1999816894531) + { + return configure_lhs_rhs_info(m, n, 2, 2, 4, 1, 8, 0, 1, 0, 1, 0); + } + else + { + GEMMLHSMatrixInfo lhs_info_buf; + GEMMRHSMatrixInfo rhs_info_buf; + GEMMLHSMatrixInfo lhs_info_img; + GEMMRHSMatrixInfo rhs_info_img; + std::tie(lhs_info_img, rhs_info_img) = configure_lhs_rhs_info(m, n, 2, 4, 8, 1, 2, 0, 0, 0, 1, 1); + std::tie(lhs_info_buf, rhs_info_buf) = configure_lhs_rhs_info(m, n, 2, 2, 4, 1, 8, 0, 1, 0, 1, 0); + + return select_lhs_rhs_info(std::make_pair(lhs_info_img, rhs_info_img), + std::make_pair(lhs_info_buf, rhs_info_buf), + n, k, b, DataType::F32); + } + } + else + { + if(r_mn <= 0.03348214365541935) + { + if(r_mk <= 0.028125000186264515) + { + return configure_lhs_rhs_info(m, n, 2, 2, 4, 1, 8, 0, 1, 0, 1, 0); + } + else + { + GEMMLHSMatrixInfo lhs_info_buf; + GEMMRHSMatrixInfo rhs_info_buf; + GEMMLHSMatrixInfo lhs_info_img; + GEMMRHSMatrixInfo rhs_info_img; + std::tie(lhs_info_img, rhs_info_img) = configure_lhs_rhs_info(m, n, 2, 4, 8, 1, 2, 0, 0, 0, 1, 1); + std::tie(lhs_info_buf, rhs_info_buf) = configure_lhs_rhs_info(m, n, 2, 2, 4, 1, 8, 0, 1, 0, 1, 0); + + return select_lhs_rhs_info(std::make_pair(lhs_info_img, rhs_info_img), + std::make_pair(lhs_info_buf, rhs_info_buf), + n, k, b, DataType::F32); + } + } + else + { + GEMMLHSMatrixInfo lhs_info_buf; + GEMMRHSMatrixInfo rhs_info_buf; + GEMMLHSMatrixInfo lhs_info_img; + GEMMRHSMatrixInfo rhs_info_img; + std::tie(lhs_info_img, rhs_info_img) = configure_lhs_rhs_info(m, n, 4, 4, 4, 1, 2, 0, 1, 0, 0, 1); + std::tie(lhs_info_buf, rhs_info_buf) = configure_lhs_rhs_info(m, n, 4, 4, 4, 1, 16, 0, 1, 0, 1, 0); + + return select_lhs_rhs_info(std::make_pair(lhs_info_img, rhs_info_img), + std::make_pair(lhs_info_buf, rhs_info_buf), + n, k, b, DataType::F32); + } + } + } +} + +std::pair<GEMMLHSMatrixInfo, GEMMRHSMatrixInfo> ClGemmDefaultConfigReshapedRhsOnlyValhall::configure_G77_f16(unsigned int m, unsigned int n, unsigned int k, unsigned int b) +{ + ARM_COMPUTE_UNUSED(k); + ARM_COMPUTE_UNUSED(b); + + if(m == 1) + { + const unsigned int h0 = std::max(n / 2, 1U); + if(n <= 836.0) + { + return configure_lhs_rhs_info(m, n, 1, 2, 16, 1, h0, 0, 1, 0, 1, 0); + } + else + { + return configure_lhs_rhs_info(m, n, 1, 2, 8, 1, h0, 0, 1, 0, 1, 0); + } + } + else if(m < 128) + { + const int h0 = std::max(std::min(static_cast<int>(n / 4), static_cast<int>(256)), static_cast<int>(1)); + if(k >= 512) + { + return configure_lhs_rhs_info(m, n, 2, 4, 16, 1, h0, 0, 1, 0, 0); + } + else + { + return configure_lhs_rhs_info(m, n, 2, 4, 8, 1, h0, 0, 1, 0, 0); + } + } + else + { + const int h0 = std::max(std::min(static_cast<int>(n / 4), static_cast<int>(256)), static_cast<int>(1)); + if(n >= 64) + { + return configure_lhs_rhs_info(m, n, 4, 8, 4, 1, h0, 0, 1, 0, 0); + } + else + { + if(k >= 512) + { + return configure_lhs_rhs_info(m, n, 2, 4, 16, 1, h0, 0, 1, 0, 0); + } + else + { + return configure_lhs_rhs_info(m, n, 2, 4, 8, 1, h0, 0, 1, 0, 0); + } + } + } +} + +std::pair<GEMMLHSMatrixInfo, GEMMRHSMatrixInfo> ClGemmDefaultConfigReshapedRhsOnlyValhall::configure_G77_u8(unsigned int m, unsigned int n, unsigned int k, unsigned int b) +{ + ARM_COMPUTE_UNUSED(k); + ARM_COMPUTE_UNUSED(b); + + if(m == 1) + { + const unsigned int h0 = std::max(n / 2, 1U); + return configure_lhs_rhs_info(m, n, 1, 4, 16, 1, h0, 0, 1, 0, 1); + } + else + { + const int h0 = std::max(std::min(static_cast<int>(n / 4), static_cast<int>(256)), static_cast<int>(1)); + if(m >= 28) + { + return configure_lhs_rhs_info(m, n, 4, 4, 16, 1, h0, 0, 1, 0, 1); + } + else + { + return configure_lhs_rhs_info(m, n, 2, 4, 16, 1, h0, 0, 1, 0, 1); + } + } +} + +std::pair<GEMMLHSMatrixInfo, GEMMRHSMatrixInfo> ClGemmDefaultConfigReshapedRhsOnlyValhall::configure_G78_f32(unsigned int m, unsigned int n, unsigned int k, unsigned int b) +{ + const float r_mn = static_cast<float>(m) / static_cast<float>(n); + const float r_mk = static_cast<float>(m) / static_cast<float>(k); + const float r_nk = static_cast<float>(n) / static_cast<float>(k); + const float workload = (static_cast<float>(m) * static_cast<float>(n) * static_cast<float>(b)) / 20.0f; + + if(m == 1) + { + if(workload <= 278.7000f) + { + if(workload <= 7.5000f) + { + return configure_lhs_rhs_info(m, n, 1, 2, 8, 1, 2, 0, 1, 1, 0, 0); + } + else + { + if(r_mn <= 0.0031f) + { + if(workload <= 256.6000f) + { + if(workload <= 16.7500f) + { + if(r_nk <= 1.6671f) + { + return configure_lhs_rhs_info(m, n, 1, 2, 2, 1, 32, 0, 0, 0, 1, 0); + } + else + { + return configure_lhs_rhs_info(m, n, 1, 2, 8, 1, 2, 0, 1, 1, 0, 0); + } + } + else + { + return configure_lhs_rhs_info(m, n, 1, 2, 2, 1, 32, 0, 0, 0, 1, 0); + } + } + else + { + return configure_lhs_rhs_info(m, n, 1, 2, 2, 1, 32, 0, 0, 0, 1, 0); + } + } + else + { + if(r_mk <= 0.0027f) + { + if(r_mk <= 0.0014f) + { + return configure_lhs_rhs_info(m, n, 1, 2, 2, 1, 32, 0, 0, 0, 1, 0); + } + else + { + if(workload <= 8.9500f) + { + return configure_lhs_rhs_info(m, n, 1, 2, 8, 1, 2, 0, 1, 1, 0, 0); + } + else + { + return configure_lhs_rhs_info(m, n, 1, 2, 2, 1, 32, 0, 0, 0, 1, 0); + } + } + } + else + { + if(workload <= 14.1500f) + { + return configure_lhs_rhs_info(m, n, 1, 2, 8, 1, 2, 0, 1, 1, 0, 0); + } + else + { + if(r_mk <= 0.0041f) + { + return configure_lhs_rhs_info(m, n, 1, 2, 2, 1, 32, 0, 0, 0, 1, 0); + } + else + { + return configure_lhs_rhs_info(m, n, 1, 2, 8, 1, 2, 0, 1, 1, 0, 0); + } + } + } + } + } + } + else + { + if(workload <= 363.7000f) + { + if(r_mk <= 0.0031f) + { + return configure_lhs_rhs_info(m, n, 1, 4, 2, 1, 32, 0, 1, 0, 1, 0); + } + else + { + return configure_lhs_rhs_info(m, n, 1, 4, 4, 1, 32, 0, 1, 0, 1, 0); + } + } + else + { + return configure_lhs_rhs_info(m, n, 1, 4, 2, 1, 32, 0, 1, 0, 1, 0); + } + } + } + else + { + if(workload <= 1384.8000f) + { + if(workload <= 704.0000f) + { + return configure_lhs_rhs_info(m, n, 2, 2, 4, 1, 32, 0, 1, 0, 1, 0); + } + else + { + return configure_lhs_rhs_info(m, n, 2, 4, 8, 1, 4, 0, 0, 0, 1, 1); + } + } + else + { + if(workload <= 16761.6006f) + { + if(r_mn <= 187.1250f) + { + return configure_lhs_rhs_info(m, n, 4, 4, 4, 1, 16, 0, 0, 0, 1, 1); + } + else + { + return configure_lhs_rhs_info(m, n, 2, 4, 8, 1, 4, 0, 0, 0, 1, 1); + } + } + else + { + if(r_mk <= 432.4630f) + { + return configure_lhs_rhs_info(m, n, 5, 4, 4, 1, 16, 0, 0, 0, 1, 1); + } + else + { + return configure_lhs_rhs_info(m, n, 2, 4, 4, 1, 16, 0, 1, 0, 1, 1); + } + } + } + } +} + +std::pair<GEMMLHSMatrixInfo, GEMMRHSMatrixInfo> ClGemmDefaultConfigReshapedRhsOnlyValhall::configure_G78_f16(unsigned int m, unsigned int n, unsigned int k, unsigned int b) +{ + const float r_mn = static_cast<float>(m) / static_cast<float>(n); + const float r_mk = static_cast<float>(m) / static_cast<float>(k); + const float r_nk = static_cast<float>(n) / static_cast<float>(k); + const float workload = (static_cast<float>(m) * static_cast<float>(n) * static_cast<float>(b)) / 20.0f; + + if(m == 1) + { + if(r_mn <= 0.0038f) + { + if(workload <= 353.9000f) + { + if(workload <= 278.7000f) + { + return configure_lhs_rhs_info(m, n, 1, 2, 4, 1, 32, 0, 0, 1, 0, 0); + } + else + { + if(r_mk <= 0.0004f) + { + return configure_lhs_rhs_info(m, n, 1, 2, 4, 1, 32, 0, 0, 1, 0, 0); + } + else + { + if(r_mk <= 0.0030f) + { + return configure_lhs_rhs_info(m, n, 1, 8, 4, 1, 8, 0, 1, 1, 0, 1); + } + else + { + return configure_lhs_rhs_info(m, n, 1, 2, 4, 1, 32, 0, 0, 1, 0, 0); + } + } + } + } + else + { + if(r_nk <= 1.9384f) + { + return configure_lhs_rhs_info(m, n, 1, 2, 4, 1, 32, 0, 0, 1, 0, 0); + } + else + { + return configure_lhs_rhs_info(m, n, 1, 8, 4, 1, 8, 0, 1, 1, 0, 1); + } + } + } + else + { + if(r_nk <= 1.0368f) + { + return configure_lhs_rhs_info(m, n, 1, 2, 16, 1, 32, 0, 0, 1, 0, 0); + } + else + { + return configure_lhs_rhs_info(m, n, 1, 2, 4, 1, 32, 0, 0, 1, 0, 0); + } + } + } + else + { + if(workload <= 1422.4000f) + { + if(workload <= 704.0000f) + { + return configure_lhs_rhs_info(m, n, 2, 2, 8, 1, 32, 0, 0, 1, 0, 0); + } + else + { + if(workload <= 1197.6000f) + { + return configure_lhs_rhs_info(m, n, 2, 4, 8, 1, 8, 0, 1, 1, 0, 1); + } + else + { + if(workload <= 1241.6000f) + { + return configure_lhs_rhs_info(m, n, 2, 8, 8, 1, 16, 0, 1, 1, 0, 0); + } + else + { + return configure_lhs_rhs_info(m, n, 2, 4, 8, 1, 8, 0, 1, 1, 0, 1); + } + } + } + } + else + { + if(workload <= 2769.6000f) + { + if(workload <= 1846.4000f) + { + if(r_mn <= 2.4927f) + { + return configure_lhs_rhs_info(m, n, 2, 8, 8, 1, 16, 0, 1, 1, 0, 0); + } + else + { + return configure_lhs_rhs_info(m, n, 4, 4, 8, 1, 32, 0, 1, 1, 0, 0); + } + } + else + { + if(r_mn <= 0.6261f) + { + return configure_lhs_rhs_info(m, n, 4, 4, 8, 1, 32, 0, 1, 1, 0, 0); + } + else + { + if(r_mk <= 3.4453f) + { + if(r_mn <= 1.4135f) + { + return configure_lhs_rhs_info(m, n, 2, 8, 8, 1, 16, 0, 1, 1, 0, 0); + } + else + { + return configure_lhs_rhs_info(m, n, 4, 4, 8, 1, 32, 0, 1, 1, 0, 0); + } + } + else + { + return configure_lhs_rhs_info(m, n, 2, 8, 8, 1, 16, 0, 1, 1, 0, 0); + } + } + } + } + else + { + if(r_nk <= 0.0302f) + { + return configure_lhs_rhs_info(m, n, 2, 4, 8, 1, 8, 0, 1, 1, 0, 1); + } + else + { + if(r_mk <= 181.3750f) + { + return configure_lhs_rhs_info(m, n, 4, 4, 8, 1, 32, 0, 1, 1, 0, 0); + } + else + { + if(workload <= 28035.2002f) + { + return configure_lhs_rhs_info(m, n, 2, 8, 8, 1, 16, 0, 1, 1, 0, 0); + } + else + { + if(r_mk <= 808.6667f) + { + return configure_lhs_rhs_info(m, n, 4, 4, 8, 1, 32, 0, 1, 1, 0, 0); + } + else + { + return configure_lhs_rhs_info(m, n, 2, 8, 8, 1, 16, 0, 1, 1, 0, 0); + } + } + } + } + } + } + } +} +} // namespace gemm +} // namespace kernels +} // namespace opencl +} // namespace arm_compute |