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device_direct_convolution_2.cuh 3.5 KB
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#pragma once
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#include "gridwise_direct_convolution_2.cuh"
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template <class T, class InDesc, class WeiDesc, class OutDesc>
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void device_direct_convolution_2(
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    InDesc, const Tensor<T>& in, WeiDesc, const Tensor<T>& wei, OutDesc, Tensor<T>& out)
{
    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 = Index<0>{};
    constexpr auto I1 = Index<1>{};
    constexpr auto I2 = Index<2>{};
    constexpr auto I3 = Index<3>{};

    constexpr auto in_desc          = InDesc{};
    constexpr auto wei_desc         = WeiDesc{};
    constexpr auto out_desc         = OutDesc{};
    constexpr unsigned OutTileSizeH = 2;
    constexpr unsigned OutTileSizeW = 2;
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    constexpr unsigned NPerBlock    = 2;
    constexpr unsigned KPerBlock    = 32;
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    constexpr unsigned CPerBlock    = 2;
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    constexpr unsigned YPerBlock    = 1;
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    constexpr unsigned XPerBlock    = 16;
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    constexpr unsigned NPerThread = 2;
    constexpr unsigned KPerThread = 4;
    constexpr unsigned CPerThread = 2;
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    constexpr unsigned NBlockOpLen0 = 1;
    constexpr unsigned NBlockOpLen1 = 1;
    constexpr unsigned NBlockOpLen2 = 4;
    constexpr unsigned NBlockOpLen3 = 32;

    constexpr unsigned BlockSize = 128;

    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);

    cudaEvent_t start, stop;
    float elapsedTime;

    cudaEventCreate(&start);
    cudaEventRecord(start, 0);

    gridwise_convolution<T,
                         InDesc,
                         WeiDesc,
                         OutDesc,
                         OutTileSizeH,
                         OutTileSizeW,
                         NPerBlock,
                         KPerBlock,
                         CPerBlock,
                         YPerBlock,
                         XPerBlock,
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                         NPerThread,
                         KPerThread,
                         CPerThread,
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                         NBlockOpLen0,
                         NBlockOpLen1,
                         NBlockOpLen2,
                         NBlockOpLen3,
                         BlockSize,
                         GridSize>
        <<<grid_dim, block_dim>>>(InDesc{},
                                  static_cast<T*>(in_device_buf.GetDeviceBuffer()),
                                  WeiDesc{},
                                  static_cast<T*>(wei_device_buf.GetDeviceBuffer()),
                                  OutDesc{},
                                  static_cast<T*>(out_device_buf.GetDeviceBuffer()));

    cudaEventCreate(&stop);
    cudaEventRecord(stop, 0);
    cudaEventSynchronize(stop);

    cudaEventElapsedTime(&elapsedTime, start, stop);
    printf("Elapsed time : %f ms\n", elapsedTime);

    checkCudaErrors(cudaGetLastError());
    out_device_buf.FromDevice(out.mData.data());
}