Thrust+boost代码编译错误
Thrust+boost code compilation error
我遇到了无法解决的奇怪问题。它与升压+推力代码相关联。
代码：
#include <boost/config/compiler/nvcc.hpp>
#include <thrust/host_vector.h>
#include <thrust/device_vector.h>
#include <thrust/sort.h>
#include <thrust/copy.h>
#include <thrust/sequence.h>
#include <thrust/random.h>
#include <thrust/generate.h>
#include <thrust/detail/type_traits.h>
#include <cuda_runtime.h>
#include <cublas_v2.h>
#include <common/inc/helper_cuda.h>
#include <boost/numeric/ublas/matrix.hpp>
#include <boost/numeric/ublas/operation.hpp>
#include <boost/random/mersenne_twister.hpp>
#include <boost/random/uniform_int_distribution.hpp>
#include <boost/compute/system.hpp>
#include <boost/compute/command_queue.hpp>
#include <boost/compute/algorithm/generate.hpp>
#include <boost/compute/algorithm/generate_n.hpp>
#include <algorithm>
#include <time.h>
#include <limits.h>
#include <algorithm>
using namespace boost::numeric::ublas;
using namespace boost::random;
using namespace boost::compute;
int main(int argc, char **argv)
{
int N = 100000;
unbounded_array<float> lineMatrix1(N*N);
unbounded_array<float> lineMatrix2(N*N);
generate_n(lineMatrix1.begin(), N*N, []() { return (10 * rand() / RAND_MAX); });
generate_n(lineMatrix2.begin(), N*N, []() { return (10 * rand() / RAND_MAX); });
matrix<float> matrix1(N, N, lineMatrix1);
matrix<float> matrix2(N, N, lineMatrix2);
matrix<float> zeroMatrix(N, N, 0);
matrix<float> zeroMatrix2(N, N, 0);
//boost single core computation start
auto matrix3 = prod(matrix1, matrix2);
//boost single core computation finish
//thrust computation start
findCudaDevice(argc, (const char **)argv);
cublasHandle_t handle;
cublasCreate(&handle);
float alpha = 1.0f;
float beta = 0.0f;
auto result = cublasSgemm(handle, CUBLAS_OP_N, CUBLAS_OP_N, N, N, N, &alpha, matrix1.data().cbegin(), N, matrix2.data().cbegin(), N, &beta, zeroMatrix.data().begin(), N);
cudaDeviceSynchronize();
thrust::device_vector<float> deviceMatrix1(N*N);
thrust::device_vector<float> deviceMatrix2(N*N);
thrust::device_vector<float> deviceZeroMatrix(N*N, 0);
thrust::copy(matrix1.data().cbegin(), matrix1.data().cend(), deviceMatrix1.begin());
thrust::copy(matrix2.data().cbegin(), matrix2.data().cend(), deviceMatrix2.begin());
auto result2 = cublasSgemm(handle, CUBLAS_OP_N, CUBLAS_OP_N, N, N, N, &alpha, deviceMatrix1.data().get(), N, deviceMatrix2.data().get(), N, &beta, deviceZeroMatrix.data().get(), N);
cudaDeviceSynchronize();
thrust::copy(deviceZeroMatrix.cbegin(), deviceZeroMatrix.cend(), zeroMatrix2.data().begin());
std::cout << result << std::endl;
std::cout << result2 << std::endl;
//thrust computation finish
float eps = 0.00001;
int differCount1 = 0;
int differCount2 = 0;
for (int i = 0; i < matrix3.size1(); i++)
{
for (int j = 0; j < matrix3.size2(); j++)
{
if (std::abs(matrix3(i, j) != zeroMatrix(i, j)) > eps)
differCount1++;
if (std::abs(matrix3(i, j) != zeroMatrix2(i, j)) > eps)
differCount2++;
}
}
std::cout << differCount1 << std::endl;
std::cout << differCount2 << std::endl;
char c;
std::cin >> c;
return 0;
}
此文件的名称为 'myFirstMatrixTest.cu'。
所以，我有编译器错误：
MSB3721 exit from command ""C:\Program Files\NVIDIA GPU Computing
Toolkit\CUDA\v9.2\bin\nvcc.exe"
-gencode=arch=compute_30,code=\"sm_30,compute_30\" -gencode=arch=compute_35,code=\"sm_35,compute_35\" -gencode=arch=compute_37,code=\"sm_37,compute_37\" -gencode=arch=compute_50,code=\"sm_50,compute_50\" -gencode=arch=compute_52,code=\"sm_52,compute_52\" -gencode=arch=compute_60,code=\"sm_60,compute_60\" -gencode=arch=compute_61,code=\"sm_61,compute_61\" -gencode=arch=compute_70,code=\"sm_70,compute_70\" --use-local-env -ccbin "C:\Program Files (x86)\Microsoft Visual Studio17\Community\VC\Tools\MSVC.14.26428\bin\HostX86\x64" -x cu
-rdc=true -I./ -I../common/inc -I../../common/inc -I/common/inc -I../ -I./ -I"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v9.2/include" -I../../common/inc -I"C:\Program
Files\NVIDIA GPU Computing Toolkit\CUDA\v9.2\include" -G --keep-dir
x64\Debug -maxrregcount=0 --machine 64 --compile -cudart static
-Xcompiler "/wd 4819" -g -DWIN32 -DWIN32 -D_MBCS -D_MBCS -Xcompiler "/EHsc /W3 /nologo /Od /FS /Zi /RTC1 /MTd " -o
x64/Debug/MyFirstMatrixTest.cu.obj "C:\User Root\Repository\CUDA
Projects\MatrixMultiplicationThrust\MyFirstMatrixTest.cu"" with code
"2". MyFirstMatrixTest C:\Program Files (x86)\Microsoft Visual
Studio17\Community\Common7\IDE\VC\VCTargets\BuildCustomizations\CUDA
9.2.targets 707
还有这个：
Fatal Error C1012 unmatched parenthesis : missing character
")" MyFirstMatrixTest c:\local\boost\preprocessor\slot\detail\shared.hpp 27
为什么会出现这个错误？
谢谢。
您正在使用 lambdas - 将“--std=c++11”选项提供给 nvcc。
嗯，第一个问题是
int N = 100000;
所以 N^2 = 10,000,000,000...（永远不会适合 int）。
即 10G*4 字节（浮动）= 40 GBytes 的数据。
对我来说，这会引发内存异常。
我遇到的下一个问题是 unbounded_array 和 generate_n 的组合。只是没有用。但是由于您使用的是 Thrust，请使用 Thrust 类型和算法（我不确定为什么 Thrust 有自己的类型来替换 STL，但无论如何）。
我在 2015 模式下使用 Visual Studio 2017 v15.7（否则我得到不支持的错误）与 Cuda v9.2 和 Boost 1.67.0。
我修改了你的代码，直到它编译正确：
（注意随机发生器仿函数中的更正，它首先只生成整数并将它们转换为浮点数）
#include <boost/config/compiler/nvcc.hpp>
#include <thrust/host_vector.h>
#include <thrust/device_vector.h>
#include <thrust/copy.h>
#include <thrust/generate.h>
#include <thrust/inner_product.h>
#include <cuda_runtime.h>
#include <cublas_v2.h>
#pragma comment(lib,"cublas.lib")
#include <helper_cuda.h>
#include <boost/numeric/ublas/matrix.hpp>
//#include <boost/numeric/ublas/io.hpp>
using boost::numeric::ublas::matrix;
#include <random>
int main(int argc, char **argv)
{
constexpr size_t N = 100;
constexpr size_t NN = N * N;
thrust::host_vector<float> lineMatrix1; lineMatrix1.reserve(NN);
thrust::host_vector<float> lineMatrix2; lineMatrix2.reserve(NN);
{
std::random_device rd; //Will be used to obtain a seed for the random number engine
std::mt19937 gen(rd()); //Standard mersenne_twister_engine seeded with rd()
std::uniform_real_distribution<float> dis(0.0f, 10.0f);
auto genRnd = [&]() { return dis(gen); };
thrust::generate_n(std::back_inserter(lineMatrix1), NN, genRnd);
thrust::generate_n(std::back_inserter(lineMatrix2), NN, genRnd);
}
matrix<float> matrix1(N, N);
thrust::copy_n(std::cbegin(lineMatrix1), NN, std::begin(matrix1.begin1()));
//std::cout << "Matrix 1:\n" << matrix1 << std::endl;
matrix<float> matrix2(N, N);
thrust::copy_n(std::cbegin(lineMatrix2), NN, std::begin(matrix2.begin1()));
//std::cout << "Matrix 2:\n" << matrix2 << std::endl;
//auto matrix3 = prod(matrix1, matrix2);
auto matrix3 = trans(prod(trans(matrix1), trans(matrix2)));
//std::cout << "Matrix 3:\n" << matrix3 << std::endl;
thrust::host_vector<float> hostResult; hostResult.reserve(NN);
for (auto rowIt = matrix3.cbegin1(); rowIt != matrix3.cend1(); rowIt++)
for (const auto& element : rowIt)
hostResult.push_back(element);
std::cout << "Host Result:\n";
for (const auto& el : hostResult) std::cout << el << " ";
std::cout << std::endl;
//////boost single core computation finish
//////thrust computation start
findCudaDevice(argc, (const char **)argv);
cublasHandle_t handle;
cublasCreate(&handle);
const float alpha = 1.0f;
const float beta = 0.0f;
thrust::device_vector<float> deviceMatrix1; deviceMatrix1.reserve(NN);
thrust::copy_n(std::cbegin(lineMatrix1), NN, std::back_inserter(deviceMatrix1));
thrust::device_vector<float> deviceMatrix2; deviceMatrix2.reserve(NN);
thrust::copy_n(std::cbegin(lineMatrix2), NN, std::back_inserter(deviceMatrix2));
thrust::device_vector<float> deviceZeroMatrix(NN,0);
auto result2 = cublasSgemm(handle,
CUBLAS_OP_N, CUBLAS_OP_N, N, N, N,
&alpha,
deviceMatrix1.data().get(), N,
deviceMatrix2.data().get(), N,
&beta,
deviceZeroMatrix.data().get(), N);
cudaDeviceSynchronize();
cublasDestroy(handle);
thrust::host_vector<float> deviceResult; deviceResult.reserve(NN);
thrust::copy_n(std::cbegin(deviceZeroMatrix), NN, std::back_inserter(deviceResult));
std::cout << "Device Result:\n";
for (const auto& el : deviceResult) std::cout << el << " ";
std::cout << std::endl;
//////thrust computation finish
auto accError = thrust::inner_product(std::cbegin(hostResult), std::cend(hostResult), std::cbegin(deviceResult), 0.0f, std::plus<float>(),
[](auto val1, auto val2) { return std::abs(val1 - val2); });
std::cout << "Accumulated error: " << accError << std::endl;
std::cout << "Average error: " << accError/NN << std::endl;
std::cin.ignore();
return 0;
}
编辑：修复了代码。 ublas 矩阵存储的矩阵不同于向量，因此我不得不转置矩阵和结果。
此外，事实证明很难将 ublas 矩阵复制回向量。
edit2：编译参数
"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v9.2\bin\nvcc.exe" -gencode=arch=compute_30,code=\"sm_30,compute_30\" --use-local-env -ccbin "C:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\bin\x86_amd64" -x cu -I"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v9.2\include" -I"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v9.2\include" -G --keep-dir x64\Debug -maxrregcount=0 --machine 64 --compile -cudart static -g -DWIN32 -DWIN64 -D_DEBUG -D_CONSOLE -D_MBCS -Xcompiler "/EHsc /W3 /nologo /Od /FS /Zi /RTC1 /MDd " -o x64\Debug\kernel.cu.obj "C:\Cpp\Cuda\SoHelp2\kernel.cu"
我遇到了无法解决的奇怪问题。它与升压+推力代码相关联。
代码：
#include <boost/config/compiler/nvcc.hpp>
#include <thrust/host_vector.h>
#include <thrust/device_vector.h>
#include <thrust/sort.h>
#include <thrust/copy.h>
#include <thrust/sequence.h>
#include <thrust/random.h>
#include <thrust/generate.h>
#include <thrust/detail/type_traits.h>
#include <cuda_runtime.h>
#include <cublas_v2.h>
#include <common/inc/helper_cuda.h>
#include <boost/numeric/ublas/matrix.hpp>
#include <boost/numeric/ublas/operation.hpp>
#include <boost/random/mersenne_twister.hpp>
#include <boost/random/uniform_int_distribution.hpp>
#include <boost/compute/system.hpp>
#include <boost/compute/command_queue.hpp>
#include <boost/compute/algorithm/generate.hpp>
#include <boost/compute/algorithm/generate_n.hpp>
#include <algorithm>
#include <time.h>
#include <limits.h>
#include <algorithm>
using namespace boost::numeric::ublas;
using namespace boost::random;
using namespace boost::compute;
int main(int argc, char **argv)
{
int N = 100000;
unbounded_array<float> lineMatrix1(N*N);
unbounded_array<float> lineMatrix2(N*N);
generate_n(lineMatrix1.begin(), N*N, []() { return (10 * rand() / RAND_MAX); });
generate_n(lineMatrix2.begin(), N*N, []() { return (10 * rand() / RAND_MAX); });
matrix<float> matrix1(N, N, lineMatrix1);
matrix<float> matrix2(N, N, lineMatrix2);
matrix<float> zeroMatrix(N, N, 0);
matrix<float> zeroMatrix2(N, N, 0);
//boost single core computation start
auto matrix3 = prod(matrix1, matrix2);
//boost single core computation finish
//thrust computation start
findCudaDevice(argc, (const char **)argv);
cublasHandle_t handle;
cublasCreate(&handle);
float alpha = 1.0f;
float beta = 0.0f;
auto result = cublasSgemm(handle, CUBLAS_OP_N, CUBLAS_OP_N, N, N, N, &alpha, matrix1.data().cbegin(), N, matrix2.data().cbegin(), N, &beta, zeroMatrix.data().begin(), N);
cudaDeviceSynchronize();
thrust::device_vector<float> deviceMatrix1(N*N);
thrust::device_vector<float> deviceMatrix2(N*N);
thrust::device_vector<float> deviceZeroMatrix(N*N, 0);
thrust::copy(matrix1.data().cbegin(), matrix1.data().cend(), deviceMatrix1.begin());
thrust::copy(matrix2.data().cbegin(), matrix2.data().cend(), deviceMatrix2.begin());
auto result2 = cublasSgemm(handle, CUBLAS_OP_N, CUBLAS_OP_N, N, N, N, &alpha, deviceMatrix1.data().get(), N, deviceMatrix2.data().get(), N, &beta, deviceZeroMatrix.data().get(), N);
cudaDeviceSynchronize();
thrust::copy(deviceZeroMatrix.cbegin(), deviceZeroMatrix.cend(), zeroMatrix2.data().begin());
std::cout << result << std::endl;
std::cout << result2 << std::endl;
//thrust computation finish
float eps = 0.00001;
int differCount1 = 0;
int differCount2 = 0;
for (int i = 0; i < matrix3.size1(); i++)
{
for (int j = 0; j < matrix3.size2(); j++)
{
if (std::abs(matrix3(i, j) != zeroMatrix(i, j)) > eps)
differCount1++;
if (std::abs(matrix3(i, j) != zeroMatrix2(i, j)) > eps)
differCount2++;
}
}
std::cout << differCount1 << std::endl;
std::cout << differCount2 << std::endl;
char c;
std::cin >> c;
return 0;
}
此文件的名称为 'myFirstMatrixTest.cu'。
所以，我有编译器错误：
MSB3721 exit from command ""C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v9.2\bin\nvcc.exe" -gencode=arch=compute_30,code=\"sm_30,compute_30\" -gencode=arch=compute_35,code=\"sm_35,compute_35\" -gencode=arch=compute_37,code=\"sm_37,compute_37\" -gencode=arch=compute_50,code=\"sm_50,compute_50\" -gencode=arch=compute_52,code=\"sm_52,compute_52\" -gencode=arch=compute_60,code=\"sm_60,compute_60\" -gencode=arch=compute_61,code=\"sm_61,compute_61\" -gencode=arch=compute_70,code=\"sm_70,compute_70\" --use-local-env -ccbin "C:\Program Files (x86)\Microsoft Visual Studio17\Community\VC\Tools\MSVC.14.26428\bin\HostX86\x64" -x cu -rdc=true -I./ -I../common/inc -I../../common/inc -I/common/inc -I../ -I./ -I"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v9.2/include" -I../../common/inc -I"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v9.2\include" -G --keep-dir x64\Debug -maxrregcount=0 --machine 64 --compile -cudart static -Xcompiler "/wd 4819" -g -DWIN32 -DWIN32 -D_MBCS -D_MBCS -Xcompiler "/EHsc /W3 /nologo /Od /FS /Zi /RTC1 /MTd " -o x64/Debug/MyFirstMatrixTest.cu.obj "C:\User Root\Repository\CUDA Projects\MatrixMultiplicationThrust\MyFirstMatrixTest.cu"" with code "2". MyFirstMatrixTest C:\Program Files (x86)\Microsoft Visual Studio17\Community\Common7\IDE\VC\VCTargets\BuildCustomizations\CUDA 9.2.targets 707
还有这个：
Fatal Error C1012 unmatched parenthesis : missing character ")" MyFirstMatrixTest c:\local\boost\preprocessor\slot\detail\shared.hpp 27
为什么会出现这个错误？
谢谢。
您正在使用 lambdas - 将“--std=c++11”选项提供给 nvcc。
嗯，第一个问题是
int N = 100000;
所以 N^2 = 10,000,000,000...（永远不会适合 int）。
即 10G*4 字节（浮动）= 40 GBytes 的数据。
对我来说，这会引发内存异常。
我遇到的下一个问题是 unbounded_array 和 generate_n 的组合。只是没有用。但是由于您使用的是 Thrust，请使用 Thrust 类型和算法（我不确定为什么 Thrust 有自己的类型来替换 STL，但无论如何）。
我在 2015 模式下使用 Visual Studio 2017 v15.7（否则我得到不支持的错误）与 Cuda v9.2 和 Boost 1.67.0。
我修改了你的代码，直到它编译正确： （注意随机发生器仿函数中的更正，它首先只生成整数并将它们转换为浮点数）
#include <boost/config/compiler/nvcc.hpp>
#include <thrust/host_vector.h>
#include <thrust/device_vector.h>
#include <thrust/copy.h>
#include <thrust/generate.h>
#include <thrust/inner_product.h>
#include <cuda_runtime.h>
#include <cublas_v2.h>
#pragma comment(lib,"cublas.lib")
#include <helper_cuda.h>
#include <boost/numeric/ublas/matrix.hpp>
//#include <boost/numeric/ublas/io.hpp>
using boost::numeric::ublas::matrix;
#include <random>
int main(int argc, char **argv)
{
constexpr size_t N = 100;
constexpr size_t NN = N * N;
thrust::host_vector<float> lineMatrix1; lineMatrix1.reserve(NN);
thrust::host_vector<float> lineMatrix2; lineMatrix2.reserve(NN);
{
std::random_device rd; //Will be used to obtain a seed for the random number engine
std::mt19937 gen(rd()); //Standard mersenne_twister_engine seeded with rd()
std::uniform_real_distribution<float> dis(0.0f, 10.0f);
auto genRnd = [&]() { return dis(gen); };
thrust::generate_n(std::back_inserter(lineMatrix1), NN, genRnd);
thrust::generate_n(std::back_inserter(lineMatrix2), NN, genRnd);
}
matrix<float> matrix1(N, N);
thrust::copy_n(std::cbegin(lineMatrix1), NN, std::begin(matrix1.begin1()));
//std::cout << "Matrix 1:\n" << matrix1 << std::endl;
matrix<float> matrix2(N, N);
thrust::copy_n(std::cbegin(lineMatrix2), NN, std::begin(matrix2.begin1()));
//std::cout << "Matrix 2:\n" << matrix2 << std::endl;
//auto matrix3 = prod(matrix1, matrix2);
auto matrix3 = trans(prod(trans(matrix1), trans(matrix2)));
//std::cout << "Matrix 3:\n" << matrix3 << std::endl;
thrust::host_vector<float> hostResult; hostResult.reserve(NN);
for (auto rowIt = matrix3.cbegin1(); rowIt != matrix3.cend1(); rowIt++)
for (const auto& element : rowIt)
hostResult.push_back(element);
std::cout << "Host Result:\n";
for (const auto& el : hostResult) std::cout << el << " ";
std::cout << std::endl;
//////boost single core computation finish
//////thrust computation start
findCudaDevice(argc, (const char **)argv);
cublasHandle_t handle;
cublasCreate(&handle);
const float alpha = 1.0f;
const float beta = 0.0f;
thrust::device_vector<float> deviceMatrix1; deviceMatrix1.reserve(NN);
thrust::copy_n(std::cbegin(lineMatrix1), NN, std::back_inserter(deviceMatrix1));
thrust::device_vector<float> deviceMatrix2; deviceMatrix2.reserve(NN);
thrust::copy_n(std::cbegin(lineMatrix2), NN, std::back_inserter(deviceMatrix2));
thrust::device_vector<float> deviceZeroMatrix(NN,0);
auto result2 = cublasSgemm(handle,
CUBLAS_OP_N, CUBLAS_OP_N, N, N, N,
&alpha,
deviceMatrix1.data().get(), N,
deviceMatrix2.data().get(), N,
&beta,
deviceZeroMatrix.data().get(), N);
cudaDeviceSynchronize();
cublasDestroy(handle);
thrust::host_vector<float> deviceResult; deviceResult.reserve(NN);
thrust::copy_n(std::cbegin(deviceZeroMatrix), NN, std::back_inserter(deviceResult));
std::cout << "Device Result:\n";
for (const auto& el : deviceResult) std::cout << el << " ";
std::cout << std::endl;
//////thrust computation finish
auto accError = thrust::inner_product(std::cbegin(hostResult), std::cend(hostResult), std::cbegin(deviceResult), 0.0f, std::plus<float>(),
[](auto val1, auto val2) { return std::abs(val1 - val2); });
std::cout << "Accumulated error: " << accError << std::endl;
std::cout << "Average error: " << accError/NN << std::endl;
std::cin.ignore();
return 0;
}
编辑：修复了代码。 ublas 矩阵存储的矩阵不同于向量，因此我不得不转置矩阵和结果。 此外，事实证明很难将 ublas 矩阵复制回向量。
edit2：编译参数
"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v9.2\bin\nvcc.exe" -gencode=arch=compute_30,code=\"sm_30,compute_30\" --use-local-env -ccbin "C:\Program Files (x86)\Microsoft Visual Studio 14.0\VC\bin\x86_amd64" -x cu -I"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v9.2\include" -I"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v9.2\include" -G --keep-dir x64\Debug -maxrregcount=0 --machine 64 --compile -cudart static -g -DWIN32 -DWIN64 -D_DEBUG -D_CONSOLE -D_MBCS -Xcompiler "/EHsc /W3 /nologo /Od /FS /Zi /RTC1 /MDd " -o x64\Debug\kernel.cu.obj "C:\Cpp\Cuda\SoHelp2\kernel.cu"