我正在尝试将所有CUDA代码放到单独的test.cu文件中,并使用test.h文件从main.cpp文件中调用它。但是当我尝试从设备获取数据时,我总是在ExampleSeparate.exe中遇到错误“0x0F277552(nvcuda.dll)的未处理异常:0xC0000005:访问冲突写入位置0x04A8D000。”
请告诉我代码有什么问题?我将内核代码和代码的主要部分分成不同的文件我做错了什么?最好的方法是什么?
我知道如何在OpenCL中执行此操作,但无法在CUDA中进行管理。
的main.cpp
printf("My CUDA example.\n");
int iWidth, iHeight, iBpp, cycles_max = 100;
vector<unsigned char> pDataIn;
vector<unsigned char> pDataOut;
unsigned int SizeIn, SizeOut;
unsigned char *devDatOut, *devDatIn, *PInData, *POutData, *DatIn, *DatOut;
int error1 = LoadBmpFile(L"3840x2160.bmp", iWidth, iHeight, iBpp, pDataIn);
if (error1 != 0 || pDataIn.size() == 0 || iBpp != 32)
{
printf("error load input file!\n");
}
pDataOut.resize(pDataIn.size()/4);
//Для CUDA
SizeIn = pDataIn.size();
SizeOut = pDataOut.size();
PInData = pDataIn.data();
POutData = pDataOut.data();
//Для CPU
DatIn = pDataIn.data();
DatOut = pDataOut.data();
my_cuda((uchar4*)PInData, POutData, SizeIn, SizeOut);
return 0;
test.h
void my_cuda(uchar4* PInData, unsigned char *POutData, unsigned int SizeIn, unsigned int SizeOut);
test.cu
#define gpuErrchk(ans) { gpuAssert((ans), __FILE__, __LINE__); }
inline void gpuAssert(cudaError_t code, const char *file, int line, bool abort=true)
{
if (code != cudaSuccess)
{
fprintf(stderr,"GPUassert: %s %s %d\n", cudaGetErrorString(code), file, line);
if (abort) exit(code);
}
}
void my_cuda(uchar4* PInData, unsigned char *POutData, unsigned int SizeIn, unsigned int SizeOut){
uchar4 *devDatIn;
unsigned char *devDatOut;
printf("Allocate memory on device\n");
gpuErrchk(cudaMalloc((void**)&devDatIn, SizeIn * sizeof(uchar4)));
gpuErrchk(cudaMalloc((void**)&devDatOut, SizeOut * sizeof(unsigned char)));
printf("Copy data on device\n");
gpuErrchk(cudaMemcpy(devDatIn, PInData, SizeIn * sizeof(uchar4), cudaMemcpyHostToDevice));
gpuErrchk(cudaMemcpy(devDatOut, POutData, SizeOut * sizeof(unsigned char), cudaMemcpyHostToDevice));
dim3 blocks(8100, 1, 1);
dim3 threads(1024, 1, 1);
addMatrix<<<blocks, threads>>>(devDatIn, devDatOut);
gpuErrchk(cudaMemcpy(POutData, devDatOut, SizeOut * sizeof(unsigned char), cudaMemcpyDeviceToHost));
cudaFree(devDatOut);
cudaFree(devDatIn);
_getch();
}
答案 0 :(得分:3)
在这行代码中:
SizeIn = pDataIn.size();
你的pDataIn
是一个足够大的<unsigned char>
向量,可以处理每像素4个字节的3840x2160图像。所以SizeIn
应该是3840x2160x4。
然后将矢量数据分配给unsigned char
指针:
PInData = pDataIn.data();
然后你将指针投射到uchar4
,同时传递旧 SizeIn
字节:
my_cuda((uchar4*)PInData, POutData, SizeIn, SizeOut);
在my_cuda
功能中,为4倍太大的设备存储分配大小:
gpuErrchk(cudaMalloc((void**)&devDatIn, SizeIn * sizeof(uchar4)));
然后你尝试从主机到设备复制4次过多的数据:
gpuErrchk(cudaMemcpy(devDatIn, PInData, SizeIn * sizeof(uchar4), cudaMemcpyHostToDevice));
这条线几乎肯定会在主机上出现故障。
解决方案可能很简单:
SizeIn = pDataIn.size()/4;
这是一个基于您展示的代码的完整工作示例,演示了seg错误和修复:
$ cat t1135.cu
#include <stdio.h>
#include <vector>
using namespace std;
#define gpuErrchk(ans) { gpuAssert((ans), __FILE__, __LINE__); }
inline void gpuAssert(cudaError_t code, const char *file, int line, bool abort=true)
{
if (code != cudaSuccess)
{
fprintf(stderr,"GPUassert: %s %s %d\n", cudaGetErrorString(code), file, line);
if (abort) exit(code);
}
}
void my_cuda(uchar4* PInData, unsigned char *POutData, unsigned int SizeIn, unsigned int SizeOut){
uchar4 *devDatIn;
unsigned char *devDatOut;
printf("Allocate memory on device\n");
gpuErrchk(cudaMalloc((void**)&devDatIn, SizeIn * sizeof(uchar4)));
gpuErrchk(cudaMalloc((void**)&devDatOut, SizeOut * sizeof(unsigned char)));
printf("Copy data on device\n");
gpuErrchk(cudaMemcpy(devDatIn, PInData, SizeIn * sizeof(uchar4), cudaMemcpyHostToDevice));
gpuErrchk(cudaMemcpy(devDatOut, POutData, SizeOut * sizeof(unsigned char), cudaMemcpyHostToDevice));
dim3 blocks(8100, 1, 1);
dim3 threads(1024, 1, 1);
//addMatrix<<<blocks, threads>>>(devDatIn, devDatOut);
gpuErrchk(cudaMemcpy(POutData, devDatOut, SizeOut * sizeof(unsigned char), cudaMemcpyDeviceToHost));
cudaFree(devDatOut);
cudaFree(devDatIn);
}
int main(){
printf("My CUDA example.\n");
vector<unsigned char> pDataIn(3840*2160*4);
vector<unsigned char> pDataOut;
unsigned int SizeIn, SizeOut;
unsigned char *PInData, *POutData;
pDataOut.resize(pDataIn.size()/4);
//... CUDA
#ifdef FIX
SizeIn = pDataIn.size()/4;
#else
SizeIn = pDataIn.size();
#endif
SizeOut = pDataOut.size();
PInData = pDataIn.data();
POutData = pDataOut.data();
my_cuda((uchar4*)PInData, POutData, SizeIn, SizeOut);
return 0;
}
$ nvcc -o t1135 t1135.cu
$ ./t1135
My CUDA example.
Allocate memory on device
Copy data on device
Segmentation fault (core dumped)
$ nvcc -DFIX -o t1135 t1135.cu
$ ./t1135
My CUDA example.
Allocate memory on device
Copy data on device
$