Commit dfa02139 authored by Chao Liu's avatar Chao Liu
Browse files

convolution: init cuda run

parent 49ceb0fe
#include <iostream>
#include <numeric>
#include <initializer_list>
#include "nvToolsExt.h"
#include "tensor.hpp"
#include "device_tensor.cuh"
#include "direct_convolution.cuh"
template <class T>
struct Generator
{
T value = 0;
template <class... Is>
T operator()(Is... is)
{
#if 0
return value;
#else
std::initializer_list<std::size_t> ls = {static_cast<std::size_t>(is)...};
return std::accumulate(ls.begin(), ls.end(), std::size_t(0));
#endif
}
};
template <typename T>
void host_convolution(const Tensor<T>& in,
const Tensor<T>& wei,
......@@ -37,24 +57,39 @@ void host_convolution(const Tensor<T>& in,
}
template <class T>
void device_convolution(const Tensor<T>& in, const Tensor<T>& wei, Tensor<T>& out)
void device_convolution(Tensor<T>& in, Tensor<T>& wei, Tensor<T>& out)
{
DeviceTensorDescriptor in_desc_device(in.mDesc);
DeviceTensorDescriptor wei_desc_device(wei.mDesc);
DeviceTensorDescriptor out_desc_device(out.mDesc);
DeviceTensorDescriptor<4> in_desc_device(in.mDesc);
DeviceTensorDescriptor<4> wei_desc_device(wei.mDesc);
DeviceTensorDescriptor<4> out_desc_device(out.mDesc);
printf("__func__: in_desc_device: %u %u %u %u\n",
in_desc_device.GetLength(0),
in_desc_device.GetLength(1),
in_desc_device.GetLength(2),
in_desc_device.GetLength(3));
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();
#if 1
in.GenerateTensorValue(Generator<float>{1}, num_thread);
wei.GenerateTensorValue(Generator<float>{1}, num_thread);
#endif
out.GenerateTensorValue(Generator<float>{0}, num_thread);
in_device_buf.ToDevice(in.mData.data());
wei_device_buf.ToDevice(wei.mData.data());
out_device_buf.ToDevice(out.mData.data());
dim3 block_dim(256, 1, 1);
dim3 block_dim(64, 1, 1);
dim3 grid_dim(1, 1, 1);
direct_convolution<T, 256>
gridwise_convolution<T, 3, 3, 4, 4, 2, 2, 1, 1, 32, 32, 1>
<<<grid_dim, block_dim>>>(in_desc_device,
static_cast<T*>(in_device_buf.GetDeviceBuffer()),
wei_desc_device,
......@@ -65,23 +100,20 @@ void device_convolution(const Tensor<T>& in, const Tensor<T>& wei, Tensor<T>& ou
out_device_buf.FromDevice(out.mData.data());
}
template <class T>
struct Generator
{
template <class... Is>
T operator()(Is... is)
{
return 1;
}
};
int main()
{
#if 0
Tensor<float> in({3, 16, 128, 128});
Tensor<float> in({3, 16, 130, 130});
Tensor<float> wei({4, 16, 3, 3});
Tensor<float> out_host({3, 4, 126, 126});
Tensor<float> out_host({3, 4, 128, 128});
#elif 0
Tensor<float> in({1, 1, 130, 130});
Tensor<float> wei({1, 1, 3, 3});
Tensor<float> out_host({1, 1, 128, 128});
#elif 1
Tensor<float> in({1, 1, 18, 18});
Tensor<float> wei({1, 1, 3, 3});
Tensor<float> out_host({1, 1, 16, 16});
#else
Tensor<float> in({1, 1, 4, 4});
Tensor<float> wei({1, 1, 3, 3});
......@@ -93,16 +125,16 @@ int main()
std::cout << __func__ << ": num_thread " << num_thread << std::endl;
in.GenerateTensorValue(Generator<float>{}, num_thread);
wei.GenerateTensorValue(Generator<float>{}, num_thread);
in.GenerateTensorValue(Generator<float>{1}, num_thread);
wei.GenerateTensorValue(Generator<float>{1}, num_thread);
host_convolution(in, wei, out_host, num_thread);
//host_convolution(in, wei, out_host, num_thread);
device_convolution(in, wei, out_device);
std::cout << __func__ << ": done" << std::endl;
LogRange(std::cout, in.mData, ",") << std::endl;
LogRange(std::cout, wei.mData, ",") << std::endl;
LogRange(std::cout, out_host.mData, ",") << std::endl;
//LogRange(std::cout, out_host.mData, ",") << std::endl;
LogRange(std::cout, out_device.mData, ",") << std::endl;
}
#pragma once
#include <algorithm>
#include "helper_cuda.h"
#include "tensor.hpp"
template <unsigned NDim>
struct DeviceTensorDescriptor
{
DeviceTensorDescriptor() = delete;
__host__ __device__ DeviceTensorDescriptor() = default;
__host__ DeviceTensorDescriptor(const TensorDescriptor& host_desc)
: mDataType(host_desc.GetDataType()), mDim(host_desc.GetDimension())
{
std::size_t data_sz = host_desc.GetDataType() == DataType_t::Float ? 4 : 2;
assert(NDim == host_desc.GetDimension());
std::copy(host_desc.GetLengths().begin(), host_desc.GetLengths().end(), mpLengths);
std::copy(host_desc.GetStrides().begin(), host_desc.GetStrides().end(), mpStrides);
}
checkCudaErrors(cudaMalloc(&mpLengths, data_sz * mDim));
checkCudaErrors(cudaMalloc(&mpStrides, data_sz * mDim));
__host__ __device__ unsigned GetLength(unsigned i) const { return mpLengths[i]; }
checkCudaErrors(cudaMemcpy(
mpLengths, host_desc.GetLengths().data(), data_sz * mDim, cudaMemcpyHostToDevice));
checkCudaErrors(cudaMemcpy(
mpStrides, host_desc.GetStrides().data(), data_sz * mDim, cudaMemcpyHostToDevice));
}
__host__ __device__ unsigned long GetStride(unsigned i) const { return mpStrides[i]; }
__host__ ~DeviceTensorDescriptor()
// this is ugly
__host__ __device__ unsigned long
Get1dIndex(unsigned n, unsigned c, unsigned h, unsigned w) const
{
#if 0
if(mpLengths != nullptr)
checkCudaErrors(cudaFree(mpLengths));
if(mpStrides != nullptr)
checkCudaErrors(cudaFree(mpStrides));
#endif
return n * mpStrides[0] + c * mpStrides[1] + h * mpStrides[2] + w * mpStrides[3];
}
DataType_t mDataType;
unsigned long mDim;
unsigned long* mpLengths = nullptr;
unsigned long* mpStrides = nullptr;
unsigned mpLengths[NDim];
unsigned long mpStrides[NDim];
};
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