| /* |
| * Copyright (c) 2017 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/CLGEMMMatrixMultiplyKernel.h" |
| |
| #include "arm_compute/core/AccessWindowStatic.h" |
| #include "arm_compute/core/AccessWindowTranspose.h" |
| #include "arm_compute/core/CL/CLHelpers.h" |
| #include "arm_compute/core/CL/CLKernelLibrary.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/FixedPoint.h" |
| #include "arm_compute/core/Helpers.h" |
| #include "arm_compute/core/Types.h" |
| #include "arm_compute/core/Utils.h" |
| #include "arm_compute/core/Validate.h" |
| #include "arm_compute/core/Window.h" |
| |
| #include <set> |
| #include <sstream> |
| #include <string> |
| |
| using namespace arm_compute; |
| |
| CLGEMMMatrixMultiplyKernel::CLGEMMMatrixMultiplyKernel() |
| : _input0(nullptr), _input1(nullptr), _output(nullptr) |
| { |
| } |
| |
| void CLGEMMMatrixMultiplyKernel::configure(const ICLTensor *input0, const ICLTensor *input1, ICLTensor *output, float alpha, bool is_interleaved_transposed) |
| { |
| ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input0, 1, DataType::QS8, DataType::QS16, DataType::F16, DataType::F32); |
| ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input0, input1, output); |
| ARM_COMPUTE_ERROR_ON_MISMATCHING_FIXED_POINT(input0, input1, output); |
| |
| if(!is_interleaved_transposed) |
| { |
| ARM_COMPUTE_ERROR_ON(input0->info()->dimension(0) != input1->info()->dimension(1)); |
| } |
| |
| _input0 = input0; |
| _input1 = input1; |
| _output = output; |
| |
| if(output->info()->dimension(1) == 196) |
| { |
| _lws_hint = cl::NDRange(1, 7); |
| } |
| else |
| { |
| _lws_hint = cl::NDRange(8, 8); |
| } |
| |
| std::set<std::string> build_opts; |
| build_opts.emplace(("-DCOLS_A=" + support::cpp11::to_string(input0->info()->dimension(0)))); |
| build_opts.emplace(("-DCOLS_B=" + support::cpp11::to_string(input1->info()->dimension(0)))); |
| |
| if(is_data_type_fixed_point(input0->info()->data_type())) |
| { |
| build_opts.emplace(("-DALPHA=" + support::cpp11::to_string((input0->info()->data_type() == DataType::QS8 ? |
| sqcvt_qs8_f32(alpha, input0->info()->fixed_point_position()) : |
| sqcvt_qs16_f32(alpha, input0->info()->fixed_point_position()))))); |
| |
| build_opts.emplace(("-DFIXED_POINT_POSITION=" + support::cpp11::to_string(input0->info()->fixed_point_position()))); |
| } |
| else |
| { |
| build_opts.emplace(("-DALPHA=" + float_to_string_with_full_precision(alpha))); |
| } |
| |
| if(is_interleaved_transposed) |
| { |
| // Create kernel |
| std::string data_type_name = lower_string(string_from_data_type(input0->info()->data_type())); |
| |
| if(data_type_name == "f32") |
| { |
| GPUTarget arch_target = get_arch_from_target(get_target()); |
| _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("gemm_mm_interleaved_transposed_f32_" + string_from_target(arch_target), build_opts)); |
| } |
| else |
| { |
| _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("gemm_mm_interleaved_transposed_" + data_type_name, build_opts)); |
| } |
| |
| // Configure window kernel |
| const unsigned int num_elems_processed_per_iteration_x = max_cl_vector_width / data_size_from_type(input0->info()->data_type()); |
| constexpr unsigned int num_elems_processed_per_iteration_y = 4; |
| |
| Window win = calculate_max_window(*output->info(), Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y)); |
| |
| AccessWindowRectangle input0_access(input0->info(), 0, 0, num_elems_processed_per_iteration_y, 1, 1.f, 0.25f); |
| AccessWindowTranspose input1_access(input1->info(), 0, 0, num_elems_processed_per_iteration_x, 1, 0.f, 0.25f); |
| AccessWindowRectangle output_access(output->info(), 0, 0, num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y); |
| |
| update_window_and_padding(win, input0_access, input1_access, output_access); |
| |
| output_access.set_valid_region(win, ValidRegion(Coordinates(0, 0), output->info()->tensor_shape())); |
| |
| ICLKernel::configure(win); |
| } |
| else // The input tensors have not been reshaped |
| { |
| ARM_COMPUTE_ERROR_ON(input0->info()->dimension(0) != input1->info()->dimension(1)); |
| |
| // Special case for 1xN, 2xN, 3xN and 4xN input0 tensor |
| const unsigned int num_elems_processed_per_iteration_x = max_cl_vector_width / data_size_from_type(input0->info()->data_type()); |
| const unsigned int num_elems_processed_per_iteration_y = std::min(static_cast<int>(output->info()->dimension(1)), 4); |
| |
| build_opts.emplace(("-DDATA_TYPE=" + get_cl_type_from_data_type(input0->info()->data_type()))); |
| build_opts.emplace(("-DNUM_ELEMS_PROCESSED_PER_THREAD_X=" + support::cpp11::to_string(num_elems_processed_per_iteration_x))); |
| build_opts.emplace(("-DNUM_ELEMS_PROCESSED_PER_THREAD_Y=" + support::cpp11::to_string(num_elems_processed_per_iteration_y))); |
| |
| // Create kernel |
| if(is_data_type_fixed_point(input0->info()->data_type())) |
| { |
| std::string kernel_name = "gemm_mm_" + lower_string(string_from_data_type(input0->info()->data_type())); |
| _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel((kernel_name), build_opts)); |
| } |
| else |
| { |
| std::string kernel_name = "gemm_mm_floating_point"; |
| _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel((kernel_name), build_opts)); |
| } |
| |
| Window win = calculate_max_window(*output->info(), Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y)); |
| |
| AccessWindowStatic input0_access(input0->info(), 0, 0, input0->info()->dimension(0), ceil_to_multiple(input0->info()->dimension(1), num_elems_processed_per_iteration_y)); |
| AccessWindowStatic input1_access(input1->info(), 0, 0, ceil_to_multiple(input1->info()->dimension(0), num_elems_processed_per_iteration_x), input1->info()->dimension(1)); |
| AccessWindowRectangle output_access(output->info(), 0, 0, num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y); |
| |
| update_window_and_padding(win, input0_access, input1_access, output_access); |
| |
| Coordinates coord; |
| coord.set_num_dimensions(output->info()->num_dimensions()); |
| output_access.set_valid_region(win, ValidRegion(coord, output->info()->tensor_shape())); |
| |
| ICLKernel::configure(win); |
| |
| // Set config_id for enabling LWS tuning |
| _config_id = "gemm_"; |
| _config_id += (is_interleaved_transposed ? "reshaped_" : ""); |
| _config_id += lower_string(string_from_data_type(input0->info()->data_type())); |
| _config_id += "_"; |
| _config_id += support::cpp11::to_string(output->info()->dimension(1)); |
| _config_id += "_"; |
| _config_id += support::cpp11::to_string(output->info()->dimension(0)); |
| _config_id += "_"; |
| _config_id += (is_interleaved_transposed ? support::cpp11::to_string(input1->info()->dimension(0)) : support::cpp11::to_string(input1->info()->dimension(1))); |
| } |
| } |
| |
| void CLGEMMMatrixMultiplyKernel::run(const Window &window, cl::CommandQueue &queue) |
| { |
| ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); |
| ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window); |
| |
| Window slice = window.first_slice_window_2D(); |
| Window slice_matrix_b = slice; |
| |
| slice_matrix_b.set(Window::DimX, Window::Dimension(0, 1, 1)); |
| slice_matrix_b.set(Window::DimY, Window::Dimension(0, 1, 1)); |
| |
| do |
| { |
| Window slice_b = slice; |
| // Don't slice matrix B along the z dimension if matrix B has just 2 dimensions and matrix A more than 2 |
| // This scenario can happen when the the matrix multiplication is used to perform a convolution operation |
| if(_input1->info()->num_dimensions() < 3) |
| { |
| slice_b = slice_matrix_b; |
| } |
| |
| unsigned int idx = 0; |
| add_2D_tensor_argument(idx, _input0, slice); |
| add_2D_tensor_argument(idx, _input1, slice_b); |
| add_2D_tensor_argument(idx, _output, slice); |
| enqueue(queue, *this, slice, _lws_hint); |
| } |
| while(window.slide_window_slice_2D(slice)); |
| } |