From 5b6904b8d9cb5e8a343cde96fd5a8701f44dff90 Mon Sep 17 00:00:00 2001 From: Michele Di Giorgio Date: Mon, 29 Jan 2018 12:24:14 +0000 Subject: COMPMID-866: Integrate SGEMV Neon Assembly from RSH Change-Id: Icbb43de7642e2b433d7471d70b9dbbde850989d3 Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/118197 Tested-by: Jenkins Reviewed-by: Pablo Tello --- .../NEON/kernels/arm64/NEGEMVAArch64Kernel.cpp | 130 +++++++++++++++++++++ src/runtime/NEON/functions/NEGEMM.cpp | 41 ++++++- 2 files changed, 169 insertions(+), 2 deletions(-) create mode 100644 src/core/NEON/kernels/arm64/NEGEMVAArch64Kernel.cpp (limited to 'src') diff --git a/src/core/NEON/kernels/arm64/NEGEMVAArch64Kernel.cpp b/src/core/NEON/kernels/arm64/NEGEMVAArch64Kernel.cpp new file mode 100644 index 0000000000..07950f7c3e --- /dev/null +++ b/src/core/NEON/kernels/arm64/NEGEMVAArch64Kernel.cpp @@ -0,0 +1,130 @@ +/* + * Copyright (c) 2017-2018 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/NEGEMVAArch64Kernel.h" + +#include "arm_compute/core/AccessWindowStatic.h" +#include "arm_compute/core/AccessWindowTranspose.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/NEON/NEFixedPoint.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 +{ +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wswitch-default" +#pragma GCC diagnostic ignored "-Weffc++" +#include "arm_compute/core/NEON/kernels/assembly/gemv_transposed.hpp" +#include "arm_compute/core/NEON/kernels/assembly/kernels/a64_sgemv_trans.hpp" +#pragma GCC diagnostic pop +} // namespace arm_compute + +#include +#include +#include +#include + +namespace arm_compute +{ +void NEGEMVAArch64Kernel::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::F32); + ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input0, input1, output); + ARM_COMPUTE_ERROR_ON_MISMATCHING_FIXED_POINT(input0, input1, output); + + _input0 = input0; + _input1 = input1; + _output = output; + _workspace = workspace; + _alpha = alpha; + _beta = beta; + _is_transposed_0 = is_transposed_0; + _is_transposed_1 = is_transposed_1; + + // Configure kernel window + Window win = calculate_max_window(*output->info()); + + AccessWindowRectangle output_access(output->info(), 0, 0, 12, 8); + + const int input0_access_end = ceil_to_multiple(input0->info()->tensor_shape().x(), 8); + const int input1_access_end = ceil_to_multiple(input1->info()->tensor_shape().x(), 12); + + 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 NEGEMVAArch64Kernel::run(const Window &window, const ThreadInfo &info) +{ + ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); + ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window); + + const int lda = _input0->info()->strides_in_bytes().y() / sizeof(sgemv_trans::operand_type); + const int ldb = _input1->info()->strides_in_bytes().y() / sizeof(sgemv_trans::operand_type); + const int ldc = _output->info()->strides_in_bytes().y() / sizeof(sgemv_trans::result_type); + + const auto in1_ptr = reinterpret_cast(_input1->buffer()); + + 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); + + GemvTransposed gemm(&info.cpu_info, N, K); + 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); +} +} // namespace arm_compute diff --git a/src/runtime/NEON/functions/NEGEMM.cpp b/src/runtime/NEON/functions/NEGEMM.cpp index 29424f5d33..48a0d2af1c 100644 --- a/src/runtime/NEON/functions/NEGEMM.cpp +++ b/src/runtime/NEON/functions/NEGEMM.cpp @@ -28,6 +28,7 @@ #include "arm_compute/core/ITensor.h" #include "arm_compute/core/NEON/kernels/arm32/NEGEMMAArch32Kernel.h" #include "arm_compute/core/NEON/kernels/arm64/NEGEMMAArch64Kernel.h" +#include "arm_compute/core/NEON/kernels/arm64/NEGEMVAArch64Kernel.h" #include "arm_compute/core/NEON/kernels/arm64/NEHGEMMAArch64FP16Kernel.h" #include "arm_compute/core/TensorInfo.h" #include "arm_compute/core/Types.h" @@ -40,10 +41,13 @@ namespace arm_compute { #pragma GCC diagnostic push #pragma GCC diagnostic ignored "-Wswitch-default" +#pragma GCC diagnostic ignored "-Weffc++" #include "arm_compute/core/NEON/kernels/assembly/gemm_interleaved.hpp" +#include "arm_compute/core/NEON/kernels/assembly/gemv_transposed.hpp" #include "arm_compute/core/NEON/kernels/assembly/kernels/a32_sgemm_8x6.hpp" #include "arm_compute/core/NEON/kernels/assembly/kernels/a64_hgemm_24x8.hpp" #include "arm_compute/core/NEON/kernels/assembly/kernels/a64_sgemm_12x8.hpp" +#include "arm_compute/core/NEON/kernels/assembly/kernels/a64_sgemv_trans.hpp" #pragma GCC diagnostic pop } // namespace arm_compute @@ -83,8 +87,41 @@ void NEGEMM::configure(const ITensor *a, const ITensor *b, const ITensor *c, ITe // If so, all the kernels for reshaping the tensors can be skipped if(_run_vector_matrix_multiplication) { - // Configure the matrix multiply kernel - _mm_kernel.configure(a, b, d, alpha); +#if defined(__aarch64__) + if(NEScheduler::get().cpu_info().CPU >= CPUTarget::ARMV8 && a->info()->data_type() == DataType::F32 && (c == nullptr || beta == 0.f)) + { + _mm_optimised_kernel = support::cpp14::make_unique(); + } + + if(_mm_optimised_kernel != nullptr) + { + struct CPUInfo ci = NEScheduler::get().cpu_info(); + + const int N = d->info()->tensor_shape().x(); + const int K = a->info()->tensor_shape().x(); + + size_t workbench_size = 0; + + if(a->info()->data_type() == DataType::F32) + { + workbench_size = GemvTransposed(&ci, N, K).get_working_size(); + } + + constexpr size_t alignment = 4096; + ARM_COMPUTE_ERROR_ON_MSG(workbench_size == 0, "size cannot be 0"); + _workspace.allocator()->init(TensorInfo(TensorShape{ (workbench_size + alignment - 1) * NEScheduler::get().num_threads() }, 1, DataType::S8)); + _memory_group.manage(&_workspace); + + // Configure matrix multiplication kernel + _mm_optimised_kernel->configure(a, b, d, &_workspace, alpha, 0.f, false /* is_transposed_0 */, false /* is_transposed_1 */); + _workspace.allocator()->allocate(); + } + else +#endif /* defined(__aarch64__) */ + { + // Configure the matrix multiply kernel + _mm_kernel.configure(a, b, d, alpha); + } // Configure matrix addition kernel if(beta != 0 && c != nullptr) -- cgit v1.2.1