From 6ff12a0f7765f62b8d0fa8554021e1cac2789f19 Mon Sep 17 00:00:00 2001 From: Pablo Tello Date: Thu, 2 Nov 2017 16:09:35 +0000 Subject: COMPMID-662: Integrated the new a64_s8_gemm_12x8 + dot product kernel into ACL. Change-Id: Id8f919e486a132fc58346c9f84fccbeeb83d19b3 Reviewed-on: http://mpd-gerrit.cambridge.arm.com/94233 Tested-by: Kaizen Reviewed-by: Anthony Barbier Reviewed-by: Gian Marco Iodice --- .../functions/NEGEMMLowpMatrixMultiplyCore.cpp | 86 ++++++++++------------ 1 file changed, 37 insertions(+), 49 deletions(-) (limited to 'src/runtime/NEON/functions/NEGEMMLowpMatrixMultiplyCore.cpp') diff --git a/src/runtime/NEON/functions/NEGEMMLowpMatrixMultiplyCore.cpp b/src/runtime/NEON/functions/NEGEMMLowpMatrixMultiplyCore.cpp index 11ae054e11..29104cc378 100644 --- a/src/runtime/NEON/functions/NEGEMMLowpMatrixMultiplyCore.cpp +++ b/src/runtime/NEON/functions/NEGEMMLowpMatrixMultiplyCore.cpp @@ -26,9 +26,8 @@ #include "arm_compute/core/Error.h" #include "arm_compute/core/Helpers.h" #include "arm_compute/core/ITensor.h" +#include "arm_compute/core/NEON/kernels/NEGEMMAssemblyBaseKernel.h" #include "arm_compute/core/NEON/kernels/NEGEMMInterleave4x4Kernel.h" -#include "arm_compute/core/NEON/kernels/NEGEMMInterleaveBlockedKernel.h" -#include "arm_compute/core/NEON/kernels/NEGEMMLowpAssemblyBaseKernel.h" #include "arm_compute/core/NEON/kernels/NEGEMMLowpMatrixMultiplyKernel.h" #include "arm_compute/core/NEON/kernels/NEGEMMTranspose1xWKernel.h" #include "arm_compute/core/NEON/kernels/arm64/NEGEMMLowpAArch64V8P4Kernel.h" @@ -39,16 +38,22 @@ #include "arm_compute/runtime/TensorAllocator.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_12x8.hpp" +} // namespace arm_compute + using namespace arm_compute; NEGEMMLowpMatrixMultiplyCore::NEGEMMLowpMatrixMultiplyCore(std::shared_ptr memory_manager) - : _memory_group(std::move(memory_manager)), _mm_kernel(nullptr), _mtx_a_reshape_kernel(nullptr), _mtx_b_reshape_kernel(nullptr), _tmp_a(), _tmp_b() + : _memory_group(std::move(memory_manager)), _mm_kernel(nullptr), _mtx_a_reshape_kernel(nullptr), _mtx_b_reshape_kernel(nullptr), _tmp_a(), _tmp_b(), _workspace() { } void NEGEMMLowpMatrixMultiplyCore::configure(const ITensor *a, const ITensor *b, ITensor *output) { - ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(a, 1, DataType::U8); + ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(a, 1, DataType::S8); ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::S32); ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(a, b); ARM_COMPUTE_ERROR_ON_MSG((a)->info()->dimension(0) != (b)->info()->dimension(1), "The product AB is defined only if the number of columns in A is equal to the number of rows in B"); @@ -62,42 +67,22 @@ void NEGEMMLowpMatrixMultiplyCore::configure(const ITensor *a, const ITensor *b, if(cpu_has_dotprod != 0) { - TensorShape shape_a_int = a->info()->tensor_shape(); - shape_a_int.set(0, a->info()->dimension(0) * 8.f); - shape_a_int.set(1, std::ceil(a->info()->dimension(1) / 8.f)); - - TensorShape shape_b_int = b->info()->tensor_shape(); - shape_b_int.set(0, b->info()->dimension(0) * 12.f); - shape_b_int.set(1, std::ceil(b->info()->dimension(1) / 12.f)); - - TensorInfo info_a_int(shape_a_int, 1, a->info()->data_type()); - TensorInfo info_b_int(shape_b_int, 1, b->info()->data_type()); - _tmp_a.allocator()->init(info_a_int); - _tmp_b.allocator()->init(info_b_int); - _memory_group.manage(&_tmp_a); - _memory_group.manage(&_tmp_b); - - // Configure interleave blocked kernel for matrix A - { - auto k = arm_compute::support::cpp14::make_unique(); - k->configure(a, &_tmp_a, 8, 4, false); - _mtx_a_reshape_kernel = std::move(k); - } - - // Configure interleave blocked kernel for matrix B - { - auto k = arm_compute::support::cpp14::make_unique(); - k->configure(b, &_tmp_b, 12, 4, true); - _mtx_b_reshape_kernel = std::move(k); - } - // Configure matrix multiply kernel - { - // NEGEMMLowpAArch64V8P4Kernel only compiled in AArch64 targets - auto k = arm_compute::support::cpp14::make_unique(); - k->configure(&_tmp_a, &_tmp_b, output); - _mm_kernel = std::move(k); - } + struct CPUInfo ci = NEScheduler::get().cpu_info(); + const int M = output->info()->tensor_shape().y(); + const int N = output->info()->tensor_shape().x(); + const int K = a->info()->tensor_shape().x(); + + GemmInterleaved gemm(&ci, M, N, K, false, false); + constexpr size_t alignment = 4096; + _workspace.allocator()->init(TensorInfo(TensorShape{ (gemm.get_working_size() + alignment - 1) * NEScheduler::get().num_threads() }, 1, DataType::U8)); + _memory_group.manage(&_workspace); + // Configure matrix multiplication kernel + auto k = arm_compute::support::cpp14::make_unique(); + k->configure(a, b, output, &_workspace, 1.f, 1.f); + _mm_kernel = std::move(k); + + _workspace.allocator()->allocate(); } else #endif /* ARM_COMPUTE_AARCH64_V8_2 */ @@ -139,25 +124,28 @@ void NEGEMMLowpMatrixMultiplyCore::configure(const ITensor *a, const ITensor *b, k->configure(&_tmp_a, &_tmp_b, output); _mm_kernel = std::move(k); } - } - // Allocate tensors - _tmp_a.allocator()->allocate(); - _tmp_b.allocator()->allocate(); + // Allocate tensors + _tmp_a.allocator()->allocate(); + _tmp_b.allocator()->allocate(); + } } void NEGEMMLowpMatrixMultiplyCore::run() { _memory_group.acquire(); - // Run reshape matrix A - NEScheduler::get().schedule(_mtx_a_reshape_kernel.get(), Window::DimY); + if(_mtx_a_reshape_kernel) + { + NEScheduler::get().schedule(_mtx_a_reshape_kernel.get(), Window::DimY); + } - // Run reshape matrix B - NEScheduler::get().schedule(_mtx_b_reshape_kernel.get(), Window::DimY); + if(_mtx_b_reshape_kernel) + { + NEScheduler::get().schedule(_mtx_b_reshape_kernel.get(), Window::DimY); + } - // Run matrix multiply kernel NEScheduler::get().schedule(_mm_kernel.get(), Window::DimY); _memory_group.release(); -} \ No newline at end of file +} -- cgit v1.2.1