#pragma once #include #include "device.hpp" #include "gridwise_direct_convolution_2.cuh" template void device_direct_convolution_2(InDesc, const Tensor& in, WeiDesc, const Tensor& wei, OutDesc, Tensor& out, unsigned nrepeat) { std::size_t data_sz = sizeof(T); DeviceMem in_device_buf(data_sz * in.mDesc.GetElementSpace()); DeviceMem wei_device_buf(data_sz * wei.mDesc.GetElementSpace()); DeviceMem out_device_buf(data_sz * out.mDesc.GetElementSpace()); int num_thread = std::thread::hardware_concurrency(); in_device_buf.ToDevice(in.mData.data()); wei_device_buf.ToDevice(wei.mData.data()); out_device_buf.ToDevice(out.mData.data()); constexpr auto I0 = Number<0>{}; constexpr auto I1 = Number<1>{}; constexpr auto I2 = Number<2>{}; constexpr auto I3 = Number<3>{}; constexpr auto in_desc = InDesc{}; constexpr auto wei_desc = WeiDesc{}; constexpr auto out_desc = OutDesc{}; #if 1 // 3x3, 34x34, 128 thread constexpr unsigned OutTileSizeH = 2; constexpr unsigned OutTileSizeW = 2; constexpr unsigned NPerBlock = 2; constexpr unsigned KPerBlock = 32; constexpr unsigned CPerBlock = 4; constexpr unsigned YPerBlock = 1; constexpr unsigned XPerBlock = 16; constexpr unsigned NPerThread = 2; constexpr unsigned KPerThread = 4; constexpr unsigned CPerThread = 2; constexpr unsigned BlockSize = 128; #elif 0 // 3x3, 34x34, 256 thread constexpr unsigned OutTileSizeH = 2; constexpr unsigned OutTileSizeW = 2; constexpr unsigned NPerBlock = 2; constexpr unsigned KPerBlock = 32; constexpr unsigned CPerBlock = 4; constexpr unsigned YPerBlock = 1; constexpr unsigned XPerBlock = 32; constexpr unsigned NPerThread = 2; constexpr unsigned KPerThread = 4; constexpr unsigned CPerThread = 2; constexpr unsigned BlockSize = 256; #endif constexpr unsigned GridSize = (out_desc.GetLength(I0) / NPerBlock) * (out_desc.GetLength(I1) / KPerBlock) * (out_desc.GetLength(I2) / (OutTileSizeH * YPerBlock)) * (out_desc.GetLength(I3) / (OutTileSizeW * XPerBlock)); dim3 block_dim(BlockSize); dim3 grid_dim(GridSize); printf("%s: BlockSize %u, GridSize %u \n", __func__, BlockSize, GridSize); for(unsigned i = 0; i < nrepeat; ++i) { const void* f = reinterpret_cast(gridwise_direct_convolution_2); T* in_dev_ptr = static_cast(in_device_buf.GetDeviceBuffer()); T* wei_dev_ptr = static_cast(wei_device_buf.GetDeviceBuffer()); T* out_dev_ptr = static_cast(out_device_buf.GetDeviceBuffer()); void* args[] = {&in_dev_ptr, &wei_dev_ptr, &out_dev_ptr}; float time = 0; launch_kernel(f, grid_dim, block_dim, args, time); printf("Elapsed time : %f ms\n", time); usleep(std::min(time * 1000, float(10000))); } out_device_buf.FromDevice(out.mData.data()); }