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Diffstat (limited to 'compute/ARMComputeEx/src/runtime/CL/functions/CLGEMMMatrixAccumulateBiasesKernel.cpp')
| -rw-r--r-- | compute/ARMComputeEx/src/runtime/CL/functions/CLGEMMMatrixAccumulateBiasesKernel.cpp | 171 |
1 files changed, 171 insertions, 0 deletions
diff --git a/compute/ARMComputeEx/src/runtime/CL/functions/CLGEMMMatrixAccumulateBiasesKernel.cpp b/compute/ARMComputeEx/src/runtime/CL/functions/CLGEMMMatrixAccumulateBiasesKernel.cpp new file mode 100644 index 000000000..cd7409417 --- /dev/null +++ b/compute/ARMComputeEx/src/runtime/CL/functions/CLGEMMMatrixAccumulateBiasesKernel.cpp @@ -0,0 +1,171 @@ +/* + * Copyright (c) 2021 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. + */ +/* + * Copyright (c) 2017-2020 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 "arm_compute/core/CL/kernels/CLGEMMMatrixAccumulateBiasesKernel.h" + +#include "arm_compute/core/CL/CLKernelLibrary.h" +#include "arm_compute/core/CL/CLKernelLibraryEx.h" +#include "arm_compute/core/CL/CLHelpers.h" +#include "arm_compute/core/CL/ICLTensor.h" +#include "arm_compute/core/CL/OpenCL.h" +#include "arm_compute/core/Error.h" +#include "arm_compute/core/Helpers.h" +#include "arm_compute/core/Types.h" +#include "arm_compute/core/Utils.h" +#include "support/StringSupport.h" +#include "src/core/CL/CLValidate.h" +#include "src/core/AccessWindowStatic.h" +#include "src/core/helpers/WindowHelpers.h" + +using namespace arm_compute; + +namespace +{ +Status validate_arguments(const ITensorInfo *accum, const ITensorInfo *biases) +{ + ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(accum); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(accum, 1, DataType::F16, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(biases, accum); + ARM_COMPUTE_RETURN_ERROR_ON(biases->num_dimensions() != 1); + + return Status{}; +} + +std::pair<Status, Window> +validate_and_configure_window(ITensorInfo *accum, ITensorInfo *biases, GPUTarget gpu_target, + unsigned int &num_elems_processed_per_iteration) +{ + // Select the vector size to use (8 for Bifrost; 16 for Midgard). + bool is_gpu_bifrost = + gpu_target_is_in(gpu_target, GPUTarget::G71, GPUTarget::G72, GPUTarget::G76, GPUTarget::G51, + GPUTarget::G51BIG, GPUTarget::G51LIT, GPUTarget::G52, GPUTarget::G52LIT); + num_elems_processed_per_iteration = is_gpu_bifrost ? 8 : 16; + + // Configure kernel window + Window win = calculate_max_window(*accum, Steps(num_elems_processed_per_iteration)); + + AccessWindowStatic biases_access( + biases, 0, 0, ceil_to_multiple(biases->dimension(0), num_elems_processed_per_iteration), + biases->dimension(1)); + AccessWindowHorizontal accum_access(accum, 0, num_elems_processed_per_iteration); + + bool window_changed = update_window_and_padding(win, biases_access, accum_access); + + Status err = (window_changed) + ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") + : Status{}; + return std::make_pair(err, win); +} +} // namespace + +CLGEMMMatrixAccumulateBiasesKernel::CLGEMMMatrixAccumulateBiasesKernel() + : _accum(nullptr), _biases(nullptr) +{ +} + +void CLGEMMMatrixAccumulateBiasesKernel::configure(ICLTensor *accum, const ICLTensor *biases) +{ + configure(CLKernelLibrary::get().get_compile_context(), accum, biases); +} + +void CLGEMMMatrixAccumulateBiasesKernel::configure(const CLCompileContext &compile_context, + ICLTensor *accum, const ICLTensor *biases) +{ + ARM_COMPUTE_UNUSED(compile_context); + // Perform validate step + ARM_COMPUTE_ERROR_ON_NULLPTR(accum, biases); + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(accum->info(), biases->info())); + + _biases = biases; + _accum = accum; + + // Get the target gpu + GPUTarget gpu_target = get_target(); + unsigned int vector_size = 0; + + // Configure kernel window + auto win_config = + validate_and_configure_window(accum->info(), biases->info(), gpu_target, vector_size); + ARM_COMPUTE_ERROR_THROW_ON(win_config.first); + ICLKernel::configure_internal(win_config.second); + + // Add build options + CLBuildOptions build_opts; + build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(accum->info()->data_type())); + build_opts.add_option("-DVECTOR_SIZE=" + support::cpp11::to_string(vector_size)); + + // Create kernel + _kernel = static_cast<cl::Kernel>( + CLKernelLibraryEx::get().create_kernel("gemm_accumulate_biases", build_opts.options())); +} + +Status CLGEMMMatrixAccumulateBiasesKernel::validate(const ITensorInfo *accum, + const ITensorInfo *biases, GPUTarget gpu_target) +{ + unsigned int num_elems_processed_per_iteration = 0; + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(accum, biases)); + ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(accum->clone().get(), + biases->clone().get(), gpu_target, + num_elems_processed_per_iteration) + .first); + + return Status{}; +} + +void CLGEMMMatrixAccumulateBiasesKernel::run(const Window &window, cl::CommandQueue &queue) +{ + ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); + ARM_COMPUTE_ERROR_ON_MISMATCHING_WINDOWS(ICLKernel::window(), window); + + Window accum_slice = window.first_slice_window_2D(); + + Window biases_slice(accum_slice); + biases_slice.set(Window::DimY, Window::Dimension(0, 1, 1)); + + // Run kernel + do + { + // Set arguments + unsigned int idx = 0; + add_2D_tensor_argument(idx, _accum, accum_slice); + add_1D_tensor_argument(idx, _biases, biases_slice); + + enqueue(queue, *this, accum_slice, lws_hint()); + } while (window.slide_window_slice_2D(accum_slice)); +} |