/* * 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/NEON/kernels/arm64/NEGEMMLowpAArch64Kernel.h" #include "arm_compute/core/AccessWindowStatic.h" #include "arm_compute/core/Error.h" #include "arm_compute/core/Helpers.h" #include "arm_compute/core/IAccessWindow.h" #include "arm_compute/core/ITensor.h" #include "arm_compute/core/TensorInfo.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 "support/ToolchainSupport.h" namespace arm_compute { #include "arm_compute/core/NEON/kernels/assembly/gemm_interleaved.hpp" #include "arm_compute/core/NEON/kernels/assembly/kernels/a64_gemm_s8_4x4.hpp" #include "arm_compute/core/NEON/kernels/assembly/kernels/a64_gemm_u8_4x4.hpp" } // namespace arm_compute #include #include #include // Enable only if compiled for AArch64-V8A targets #ifdef ARM_COMPUTE_AARCH64_V8A namespace arm_compute { NEGEMMLowpAArch64Kernel::NEGEMMLowpAArch64Kernel() : _func(nullptr) { } void gemm_interleaved_s8(const ITensor *input0, const ITensor *input1, ITensor *output, ITensor *workspace, float alpha, float beta, bool is_transposed_0, bool is_transposed_1, const Window &window, const ThreadInfo &info) { const int lda = input0->info()->strides_in_bytes().y(); const int ldb = input1->info()->strides_in_bytes().y(); const int ldc = output->info()->strides_in_bytes().y() / sizeof(int32_t); const auto in1_ptr = reinterpret_cast(input1->buffer()); const int M = std::min(output->info()->tensor_shape().y(), static_cast(window.y().end())) - window.y().start(); const int N = output->info()->tensor_shape().x(); const int K = input0->info()->tensor_shape().x(); // Only iterate over batches Window win(window); win.set(0, Window::Dimension(0, 1, 1)); win.set(1, Window::Dimension(0, 1, 1)); Iterator in0(input0, window); Iterator out(output, window); GemmInterleaved gemm(&info.cpu_info, M, N, K, is_transposed_0, is_transposed_1); constexpr size_t alignment = 4096; const size_t offset = (gemm.get_working_size() + alignment - 1) * info.thread_id; void *_workspace = workspace->buffer() + offset; size_t workspace_size = workspace->info()->total_size(); if(support::cpp11::align(alignment, gemm.get_working_size(), _workspace, workspace_size) == nullptr) { ARM_COMPUTE_ERROR("Not enough space to align buffer!"); } execute_window_loop(win, [&](const Coordinates & id) { gemm.execute(reinterpret_cast(in0.ptr()), lda, reinterpret_cast(in1_ptr), ldb, reinterpret_cast(out.ptr()), ldc, alpha, beta, _workspace); }, in0, out); } void gemm_interleaved_u8(const ITensor *input0, const ITensor *input1, ITensor *output, ITensor *workspace, float alpha, float beta, bool is_transposed_0, bool is_transposed_1, const Window &window, const ThreadInfo &info) { const int lda = input0->info()->strides_in_bytes().y(); const int ldb = input1->info()->strides_in_bytes().y(); const int ldc = output->info()->strides_in_bytes().y() / sizeof(uint32_t); const auto in1_ptr = reinterpret_cast(input1->buffer()); const int M = std::min(output->info()->tensor_shape().y(), static_cast(window.y().end())) - window.y().start(); const int N = output->info()->tensor_shape().x(); const int K = input0->info()->tensor_shape().x(); // Only iterate over batches Window win(window); win.set(0, Window::Dimension(0, 1, 1)); win.set(1, Window::Dimension(0, 1, 1)); Iterator in0(input0, window); Iterator out(output, window); GemmInterleaved gemm(&info.cpu_info, M, N, K, is_transposed_0, is_transposed_1); constexpr size_t alignment = 4096; const size_t offset = (gemm.get_working_size() + alignment - 1) * info.thread_id; void *_workspace = workspace->buffer() + offset; size_t workspace_size = workspace->info()->total_size(); if(support::cpp11::align(alignment, gemm.get_working_size(), _workspace, workspace_size) == nullptr) { ARM_COMPUTE_ERROR("Not enough space to align buffer!"); } execute_window_loop(win, [&](const Coordinates & id) { gemm.execute(reinterpret_cast(in0.ptr()), lda, reinterpret_cast(in1_ptr), ldb, reinterpret_cast(out.ptr()), ldc, alpha, beta, _workspace); }, in0, out); } void NEGEMMLowpAArch64Kernel::internal_configure(const ITensor *input0, const ITensor *input1, ITensor *output, ITensor *workspace, float alpha, float beta, bool is_transposed_0, bool is_transposed_1) { ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input0, 1, DataType::S8, DataType::U8); ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::S32, DataType::U32); ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input0, input1); _input0 = input0; _input1 = input1; _output = output; _workspace = workspace; _alpha = alpha; _beta = beta; _is_transposed_0 = is_transposed_0; _is_transposed_1 = is_transposed_1; switch(input0->info()->data_type()) { case DataType::S8: _func = &gemm_interleaved_s8; break; case DataType::U8: _func = &gemm_interleaved_u8; break; default: ARM_COMPUTE_ERROR("Element size not supported"); break; } // Configure kernel window Window win = calculate_max_window(*output->info()); AccessWindowRectangle output_access(output->info(), 0, 0, 4, 4); const int input0_access_end = ceil_to_multiple(input0->info()->tensor_shape().x(), 4); const int input1_access_end = ceil_to_multiple(input1->info()->tensor_shape().x(), 4); update_window_and_padding(win, AccessWindowStatic(input0->info(), 0, 0, input0_access_end, input0->info()->tensor_shape().y()), AccessWindowStatic(input1->info(), 0, 0, input1_access_end, input1->info()->tensor_shape().y()), output_access); INEKernel::configure(win); } void NEGEMMLowpAArch64Kernel::run(const Window &window, const ThreadInfo &info) { ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window); ARM_COMPUTE_ERROR_ON(_func == nullptr); (*_func)(_input0, _input1, _output, _workspace, _alpha, _beta, _is_transposed_0, _is_transposed_1, window, info); } } // namespace arm_compute #endif /* ARM_COMPUTE_AARCH64_V8A */