From 564ed39da0fd8a0d45d62e6f985f5bb798d8361d Mon Sep 17 00:00:00 2001 From: Michalis Spyrou Date: Fri, 24 Nov 2017 17:06:25 +0000 Subject: COMPMID-632: Integrated Assembly kernel GEMM U8 for Arm Cortex-A53. Change-Id: I053444f3cd4d0124df3a4a7aa8533b8395fb1336 Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/110659 Tested-by: BSG Visual Compute Jenkins server to access repositories on http://mpd-gerrit.cambridge.arm.com Reviewed-by: Georgios Pinitas Reviewed-by: Anthony Barbier --- .../kernels/arm64/NEGEMMLowpAArch64A53Kernel.cpp | 147 +++++++++++++++------ 1 file changed, 108 insertions(+), 39 deletions(-) (limited to 'src/core/NEON/kernels') diff --git a/src/core/NEON/kernels/arm64/NEGEMMLowpAArch64A53Kernel.cpp b/src/core/NEON/kernels/arm64/NEGEMMLowpAArch64A53Kernel.cpp index fe6e821ccb..e020cd9118 100644 --- a/src/core/NEON/kernels/arm64/NEGEMMLowpAArch64A53Kernel.cpp +++ b/src/core/NEON/kernels/arm64/NEGEMMLowpAArch64A53Kernel.cpp @@ -39,6 +39,7 @@ namespace arm_compute { #include "arm_compute/core/NEON/kernels/assembly/gemm_interleaved.hpp" #include "arm_compute/core/NEON/kernels/assembly/kernels/a64_gemm_s16_12x8.hpp" +#include "arm_compute/core/NEON/kernels/assembly/kernels/a64_gemm_u16_12x8.hpp" } // namespace arm_compute #include @@ -50,9 +51,100 @@ namespace arm_compute namespace arm_compute { +NEGEMMLowpAArch64A53Kernel::NEGEMMLowpAArch64A53Kernel() + : _func(nullptr) +{ +} + +void gemm_interleaved_s16_12x8(const ITensor *input0, const ITensor *input1, ITensor *output, ITensor *workspace, float alpha, float beta, bool transform_0, bool transform_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, !transform_1, !transform_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_u16_12x8(const ITensor *input0, const ITensor *input1, ITensor *output, ITensor *workspace, float alpha, float beta, bool transform_0, bool transform_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, !transform_1, !transform_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 NEGEMMLowpAArch64A53Kernel::internal_configure(const ITensor *input0, const ITensor *input1, ITensor *output, ITensor *workspace, float alpha, float beta, bool transform_0, bool transform_1) { - ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input0, 1, DataType::S8); + 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); ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input0, input1); @@ -65,6 +157,19 @@ void NEGEMMLowpAArch64A53Kernel::internal_configure(const ITensor *input0, const _transform_0 = transform_0; _transform_1 = transform_1; + switch(input0->info()->data_type()) + { + case DataType::S8: + _func = &gemm_interleaved_s16_12x8; + break; + case DataType::U8: + _func = &gemm_interleaved_u16_12x8; + break; + default: + ARM_COMPUTE_ERROR("Element size not supported"); + break; + } + // Configure kernel window Window win = calculate_max_window(*output->info()); @@ -85,45 +190,9 @@ void NEGEMMLowpAArch64A53Kernel::run(const Window &window, const ThreadInfo &inf { ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window); + ARM_COMPUTE_ERROR_ON(_func == nullptr); - 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, !_transform_1, !_transform_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); + (*_func)(_input0, _input1, _output, _workspace, _alpha, _beta, _transform_0, _transform_1, window, info); } } // namespace arm_compute #endif /* ARM_COMPUTE_AARCH64_V8A */ -- cgit v1.2.1