mirror of
https://github.com/ROCm/composable_kernel.git
synced 2026-05-11 17:00:18 +00:00
refactor
This commit is contained in:
Chao Liu
@@ -5,7 +5,7 @@
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#include "nvToolsExt.h"
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#include "tensor.hpp"
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#include "constant_tensor_descriptor.cuh"
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#include "direct_convolution_2.cuh"
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#include "device_direct_convolution_2.cuh"
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template <class T>
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struct GeneratorConstant
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@@ -109,95 +109,6 @@ void host_convolution(const Tensor<T>& in, const Tensor<T>& wei, Tensor<T>& out)
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f_par(std::thread::hardware_concurrency());
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}
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template <class T, class InDesc, class WeiDesc, class OutDesc>
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void device_convolution(
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InDesc, const Tensor<T>& in, WeiDesc, const Tensor<T>& wei, OutDesc, Tensor<T>& out)
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{
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std::size_t data_sz = sizeof(T);
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DeviceMem in_device_buf(data_sz * in.mDesc.GetElementSpace());
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DeviceMem wei_device_buf(data_sz * wei.mDesc.GetElementSpace());
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DeviceMem out_device_buf(data_sz * out.mDesc.GetElementSpace());
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int num_thread = std::thread::hardware_concurrency();
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in_device_buf.ToDevice(in.mData.data());
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wei_device_buf.ToDevice(wei.mData.data());
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out_device_buf.ToDevice(out.mData.data());
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constexpr auto I0 = Index<0>{};
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constexpr auto I1 = Index<1>{};
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constexpr auto I2 = Index<2>{};
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constexpr auto I3 = Index<3>{};
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constexpr auto in_desc = InDesc{};
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constexpr auto wei_desc = WeiDesc{};
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constexpr auto out_desc = OutDesc{};
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constexpr unsigned OutTileSizeH = 2;
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constexpr unsigned OutTileSizeW = 2;
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constexpr unsigned NPerBlock = 1;
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constexpr unsigned KPerBlock = 4;
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constexpr unsigned CPerBlock = 2;
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constexpr unsigned YPerBlock = 8;
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constexpr unsigned XPerBlock = 16;
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constexpr unsigned NBlockOpLen0 = 1;
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constexpr unsigned NBlockOpLen1 = 1;
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constexpr unsigned NBlockOpLen2 = 4;
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constexpr unsigned NBlockOpLen3 = 32;
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constexpr unsigned BlockSize = 128;
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constexpr unsigned GridSize = (out_desc.GetLength(I0) / NPerBlock) *
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(out_desc.GetLength(I1) / KPerBlock) *
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(out_desc.GetLength(I2) / (OutTileSizeH * YPerBlock)) *
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(out_desc.GetLength(I3) / (OutTileSizeW * XPerBlock));
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dim3 block_dim(BlockSize);
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dim3 grid_dim(GridSize);
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printf("%s: BlockSize %u, GridSize %u \n", __func__, BlockSize, GridSize);
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cudaEvent_t start, stop;
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float elapsedTime;
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cudaEventCreate(&start);
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cudaEventRecord(start, 0);
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gridwise_convolution<T,
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InDesc,
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WeiDesc,
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OutDesc,
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OutTileSizeH,
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OutTileSizeW,
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NPerBlock,
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KPerBlock,
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CPerBlock,
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YPerBlock,
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XPerBlock,
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NBlockOpLen0,
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NBlockOpLen1,
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NBlockOpLen2,
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NBlockOpLen3,
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BlockSize,
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GridSize>
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<<<grid_dim, block_dim>>>(InDesc{},
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static_cast<T*>(in_device_buf.GetDeviceBuffer()),
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WeiDesc{},
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static_cast<T*>(wei_device_buf.GetDeviceBuffer()),
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OutDesc{},
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static_cast<T*>(out_device_buf.GetDeviceBuffer()));
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cudaEventCreate(&stop);
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cudaEventRecord(stop, 0);
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cudaEventSynchronize(stop);
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cudaEventElapsedTime(&elapsedTime, start, stop);
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printf("Elapsed time : %f ms\n", elapsedTime);
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checkCudaErrors(cudaGetLastError());
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out_device_buf.FromDevice(out.mData.data());
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}
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int main()
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{
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#if 0
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91
driver/device_direct_convolution_2.cuh
Normal file
91
driver/device_direct_convolution_2.cuh
Normal file
@@ -0,0 +1,91 @@
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#pragma once
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#include "direct_convolution_2.cuh"
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template <class T, class InDesc, class WeiDesc, class OutDesc>
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void device_convolution(
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InDesc, const Tensor<T>& in, WeiDesc, const Tensor<T>& wei, OutDesc, Tensor<T>& out)
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{
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std::size_t data_sz = sizeof(T);
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DeviceMem in_device_buf(data_sz * in.mDesc.GetElementSpace());
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DeviceMem wei_device_buf(data_sz * wei.mDesc.GetElementSpace());
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DeviceMem out_device_buf(data_sz * out.mDesc.GetElementSpace());
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int num_thread = std::thread::hardware_concurrency();
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in_device_buf.ToDevice(in.mData.data());
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wei_device_buf.ToDevice(wei.mData.data());
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out_device_buf.ToDevice(out.mData.data());
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constexpr auto I0 = Index<0>{};
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constexpr auto I1 = Index<1>{};
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constexpr auto I2 = Index<2>{};
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constexpr auto I3 = Index<3>{};
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constexpr auto in_desc = InDesc{};
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constexpr auto wei_desc = WeiDesc{};
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constexpr auto out_desc = OutDesc{};
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constexpr unsigned OutTileSizeH = 2;
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constexpr unsigned OutTileSizeW = 2;
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constexpr unsigned NPerBlock = 1;
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constexpr unsigned KPerBlock = 4;
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constexpr unsigned CPerBlock = 2;
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constexpr unsigned YPerBlock = 8;
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constexpr unsigned XPerBlock = 16;
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constexpr unsigned NBlockOpLen0 = 1;
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constexpr unsigned NBlockOpLen1 = 1;
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constexpr unsigned NBlockOpLen2 = 4;
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constexpr unsigned NBlockOpLen3 = 32;
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constexpr unsigned BlockSize = 128;
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constexpr unsigned GridSize = (out_desc.GetLength(I0) / NPerBlock) *
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(out_desc.GetLength(I1) / KPerBlock) *
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(out_desc.GetLength(I2) / (OutTileSizeH * YPerBlock)) *
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(out_desc.GetLength(I3) / (OutTileSizeW * XPerBlock));
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dim3 block_dim(BlockSize);
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dim3 grid_dim(GridSize);
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printf("%s: BlockSize %u, GridSize %u \n", __func__, BlockSize, GridSize);
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cudaEvent_t start, stop;
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float elapsedTime;
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cudaEventCreate(&start);
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cudaEventRecord(start, 0);
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gridwise_convolution<T,
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InDesc,
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WeiDesc,
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OutDesc,
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OutTileSizeH,
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OutTileSizeW,
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NPerBlock,
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KPerBlock,
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CPerBlock,
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YPerBlock,
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XPerBlock,
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NBlockOpLen0,
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NBlockOpLen1,
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NBlockOpLen2,
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NBlockOpLen3,
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BlockSize,
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GridSize>
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<<<grid_dim, block_dim>>>(InDesc{},
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static_cast<T*>(in_device_buf.GetDeviceBuffer()),
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WeiDesc{},
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static_cast<T*>(wei_device_buf.GetDeviceBuffer()),
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OutDesc{},
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static_cast<T*>(out_device_buf.GetDeviceBuffer()));
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cudaEventCreate(&stop);
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cudaEventRecord(stop, 0);
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cudaEventSynchronize(stop);
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cudaEventElapsedTime(&elapsedTime, start, stop);
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printf("Elapsed time : %f ms\n", elapsedTime);
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checkCudaErrors(cudaGetLastError());
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out_device_buf.FromDevice(out.mData.data());
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}
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