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device_direct_convolution_1.hpp 3.67 KB
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#pragma once
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#include <unistd.h>
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#include "device.hpp"
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#include "gridwise_direct_convolution_1.hip.hpp"
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template <class T, class InDesc, class WeiDesc, class OutDesc>
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void device_direct_convolution_1(InDesc,
                                 const Tensor<T>& in,
                                 WeiDesc,
                                 const Tensor<T>& wei,
                                 OutDesc,
                                 Tensor<T>& out,
                                 unsigned nrepeat)
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{
    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());
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    constexpr auto I0 = Number<0>{};
    constexpr auto I1 = Number<1>{};
    constexpr auto I2 = Number<2>{};
    constexpr auto I3 = Number<3>{};
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    constexpr auto in_desc  = InDesc{};
    constexpr auto wei_desc = WeiDesc{};
    constexpr auto out_desc = OutDesc{};
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#if 1
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    // 3x3, 34x34
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    constexpr unsigned NPerBlock  = 2;
    constexpr unsigned KPerBlock  = 16;
    constexpr unsigned CPerBlock  = 2;
    constexpr unsigned HoPerBlock = 4;
    constexpr unsigned WoPerBlock = 32;
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    constexpr unsigned NPerThread  = 2;
    constexpr unsigned KPerThread  = 4;
    constexpr unsigned CPerThread  = 2;
    constexpr unsigned HoPerThread = 2;
    constexpr unsigned WoPerThread = 2;
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    constexpr unsigned BlockSize = 128;
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#endif
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    constexpr unsigned GridSize =
        (out_desc.GetLength(I0) / NPerBlock) * (out_desc.GetLength(I1) / KPerBlock) *
        (out_desc.GetLength(I2) / HoPerBlock) * (out_desc.GetLength(I3) / WoPerBlock);
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    printf("%s: BlockSize %u, GridSize %u \n", __func__, BlockSize, GridSize);
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    for(unsigned i = 0; i < nrepeat; ++i)
    {
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        float time = launch_kernel(gridwise_direct_convolution_1<T,
                                                                 InDesc,
                                                                 WeiDesc,
                                                                 OutDesc,
                                                                 NPerBlock,
                                                                 KPerBlock,
                                                                 CPerBlock,
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                                                                 HoPerBlock,
                                                                 WoPerBlock,
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                                                                 NPerThread,
                                                                 KPerThread,
                                                                 CPerThread,
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                                                                 HoPerThread,
                                                                 WoPerThread,
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                                                                 BlockSize,
                                                                 GridSize>,
                                   dim3(GridSize),
                                   dim3(BlockSize),
                                   static_cast<T*>(in_device_buf.GetDeviceBuffer()),
                                   static_cast<T*>(wei_device_buf.GetDeviceBuffer()),
                                   static_cast<T*>(out_device_buf.GetDeviceBuffer()));
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        printf("Elapsed time : %f ms\n", time);
        usleep(std::min(time * 1000, float(10000)));
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    }
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    out_device_buf.FromDevice(out.mData.data());
}