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Diffstat (limited to 'src/routines/levelx/xconvgemm.cpp')
| -rw-r--r-- | src/routines/levelx/xconvgemm.cpp | 176 |
1 files changed, 176 insertions, 0 deletions
diff --git a/src/routines/levelx/xconvgemm.cpp b/src/routines/levelx/xconvgemm.cpp new file mode 100644 index 00000000..5ad39751 --- /dev/null +++ b/src/routines/levelx/xconvgemm.cpp @@ -0,0 +1,176 @@ + +// ================================================================================================= +// This file is part of the CLBlast project. The project is licensed under Apache Version 2.0. This +// project loosely follows the Google C++ styleguide and uses a tab-size of two spaces and a max- +// width of 100 characters per line. +// +// Author(s): +// Cedric Nugteren <www.cedricnugteren.nl> +// +// This file implements the Xconvgemm class (see the header for information about the class). +// +// ================================================================================================= + +#include <string> +#include <vector> + +#include "routines/levelx/xconvgemm.hpp" +#include "routines/levelx/xim2col.hpp" + +namespace clblast { +// ================================================================================================= + +// Constructor: forwards to base class constructor +template <typename T> +Xconvgemm<T>::Xconvgemm(Queue &queue, EventPointer event, const std::string &name, + const ConvGemmMethod method): + Routine(queue, event, name, {"XgemmDirect"}, + PrecisionValue<T>(), {}, { + (method == ConvGemmMethod::kWithIm2Col) ? "#define CONVGEMM_WITH_IM2COL\n" : "", + #include "../../kernels/level3/level3.opencl" + , // separated in multiple parts to prevent C1091 in MSVC 2013 + #include "../../kernels/level3/xgemm_direct_part1.opencl" + #include "../../kernels/level3/xgemm_direct_part2.opencl" + #include "../../kernels/level3/xgemm_direct_part3.opencl" + , // separated in multiple parts to prevent C1091 in MSVC 2013 + #include "../../kernels/levelx/xconvgemm_part1.opencl" + #include "../../kernels/levelx/xconvgemm_part2.opencl" + }), + method_(method) { +} + +// ================================================================================================= + +template <typename T> +void Xconvgemm<T>::DoConvgemm(const size_t channels, const size_t height, const size_t width, + const size_t kernel_h, const size_t kernel_w, const size_t pad_h, + const size_t pad_w, const size_t stride_h, const size_t stride_w, + const size_t dilation_h, const size_t dilation_w, + const size_t num_kernels, const size_t batch_count, + const Buffer<T> &im_buffer, const size_t im_offset, + const Buffer<T> &kernel_buffer, const size_t kernel_offset, + const Buffer<T> &result_buffer, const size_t result_offset) { + + // Tests for a valid batch count + if (batch_count == 0) { + throw BLASError(StatusCode::kInvalidBatchCount); + } + + // Makes sure all dimensions are larger than zero + if ((channels == 0) || (height == 0) || (width == 0) || (num_kernels == 0)) { + throw BLASError(StatusCode::kInvalidDimension); + } + + // Sets the output height and width + const auto size_h = height + 2 * pad_h; + const auto padding_h = dilation_h * (kernel_h - 1) + 1; + const auto output_h = (size_h >= padding_h) ? (size_h - padding_h) / stride_h + 1 : 1; + const auto size_w = width + 2 * pad_w; + const auto padding_w = dilation_w * (kernel_w - 1) + 1; + const auto output_w = (size_w >= padding_w) ? (size_w - padding_w) / stride_w + 1 : 1; + + // Sets other useful variables + const auto patch_size = kernel_h * kernel_w * channels; + const auto num_patches = output_h * output_w; + + // Possible approach: im2col + GEMM + // result = GEMM(im2col(image), kernel) + auto col_buffer = Buffer<T>(context_, 0); // nullptr, will be optionally created later + if (method_ == ConvGemmMethod::kWithIm2Col) { + + // Temporary col matrix + const auto col_size = (method_ == ConvGemmMethod::kWithIm2Col) ? patch_size * num_patches * batch_count : 1; + col_buffer = Buffer<T>(context_, col_size); + + // Loops over each batch + for (auto batch_id = size_t{0}; batch_id < batch_count; ++batch_id) { + + // im2col + const auto im_batch_offset = batch_id * channels * height * width + im_offset; + const auto col_batch_offset = batch_id * patch_size * num_patches; + auto im2col_event = Event(); + auto im2col = Xim2col<T>(queue_, im2col_event.pointer()); + im2col.DoIm2col(channels, height, width, kernel_h, kernel_w, + pad_h, pad_w, stride_h, stride_w, dilation_h, dilation_w, + im_buffer, im_batch_offset, + col_buffer, col_batch_offset); + im2col_event.WaitForCompletion(); + } + } + + // Strided batched GEMM: C (result) = alpha (1) * A (col) * B (kernel) + beta (0) * C (result) + const auto col_stride = patch_size * num_patches; + const auto result_stride = num_kernels * output_h * output_w; + + // Tests the matrices for validity + TestMatrixB(patch_size, num_kernels, kernel_buffer, kernel_offset, patch_size); + for (auto batch = size_t{0}; batch < batch_count; ++batch) { + if (method_ == ConvGemmMethod::kWithIm2Col) { + TestMatrixA(num_patches, patch_size, col_buffer, col_stride * batch, num_patches); + } + else { + // TODO: check for valid image tensor + } + TestMatrixC(num_patches, num_kernels, result_buffer, result_offset + result_stride * batch, num_patches); + } + + // Retrieves the proper XgemmDirect kernel from the compiled binary + auto kernel = Kernel(program_, "Xconvgemm"); + + // Sets the kernel arguments + kernel.SetArgument(0, static_cast<int>(num_patches)); + kernel.SetArgument(1, static_cast<int>(num_kernels)); + kernel.SetArgument(2, static_cast<int>(patch_size)); + kernel.SetArgument(3, kernel_buffer()); + kernel.SetArgument(4, static_cast<int>(kernel_offset)); + kernel.SetArgument(5, result_buffer()); + kernel.SetArgument(6, static_cast<int>(result_offset)); + kernel.SetArgument(7, static_cast<int>(result_stride)); + if (method_ == ConvGemmMethod::kWithIm2Col) { + kernel.SetArgument(8, col_buffer()); + kernel.SetArgument(9, static_cast<int>(0)); + kernel.SetArgument(10, static_cast<int>(col_stride)); + } + if (method_ == ConvGemmMethod::kSingleKernel) { + kernel.SetArgument(8, im_buffer()); + kernel.SetArgument(9, static_cast<int>(im_offset)); + kernel.SetArgument(10, static_cast<int>(height)); + kernel.SetArgument(11, static_cast<int>(width)); + kernel.SetArgument(12, static_cast<int>(channels)); + kernel.SetArgument(13, static_cast<int>(kernel_h)); + kernel.SetArgument(14, static_cast<int>(kernel_w)); + kernel.SetArgument(15, static_cast<int>(pad_h)); + kernel.SetArgument(16, static_cast<int>(pad_w)); + kernel.SetArgument(17, static_cast<int>(stride_h)); + kernel.SetArgument(18, static_cast<int>(stride_w)); + kernel.SetArgument(19, static_cast<int>(dilation_h)); + kernel.SetArgument(20, static_cast<int>(dilation_w)); + kernel.SetArgument(21, static_cast<int>(output_h)); + kernel.SetArgument(22, static_cast<int>(output_w)); + } + + // Computes the global and local thread sizes + const auto m_ceiled = Ceil(num_patches, db_["WGD"]); + const auto n_ceiled = Ceil(num_kernels, db_["WGD"]); + const auto global = std::vector<size_t>{ + (m_ceiled * db_["MDIMCD"]) / db_["WGD"], + (n_ceiled * db_["NDIMCD"]) / db_["WGD"], + batch_count + }; + const auto local = std::vector<size_t>{db_["MDIMCD"], db_["NDIMCD"], 1}; + + // Launches the kernel + RunKernel(kernel, queue_, device_, global, local, event_); +} + +// ================================================================================================= + +// Compiles the templated class +template class Xconvgemm<half>; +template class Xconvgemm<float>; +template class Xconvgemm<double>; +template class Xconvgemm<float2>; +template class Xconvgemm<double2>; + +// ================================================================================================= +} // namespace clblast |