CUFFT库在CUDA 3中工作,但在CUDA 4中给出了运行时错误无效值

时间:2012-09-18 16:48:30

标签: matlab cuda mex

我已经在CUDA 3中成功使用了CUFFT库,但是相同的代码不能在CUDA 4中运行。使用CUDA 4时,我会在FFT执行时收到运行时错误(CUDA_INVALID_VALUE)。这是一个前向的实际到复杂的1D变换。我在CUFFT文档中看到的唯一一个在CUDA 3和CUDA 4之间发生变化的是增加了FFTW兼容模式。我将其设置为本机模式。

void mexFunction( int nlhs, mxArray *plhs[],
              int nrhs, const mxArray *prhs[])
{
int Nfft, Navg, iAvg, N, n1, n2, Npsd, size[2];

float *hReal;
float *pPxx;

float *dReal;
float *dAvg, *dSum, *dWindow;
float U;
long lAvg, lSum, lWindow;
cufftHandle            hPlan;
cufftComplex *dComplex;
cufftResult result;

int nBlocks, blockSize;

if (nrhs == 12)
{
Nfft =      mxGetScalar(prhs[0]);
blockSize = mxGetScalar(prhs[1]);
Navg =      mxGetScalar(prhs[2]);
iAvg =      mxGetScalar(prhs[3]);
U =         mxGetScalar(prhs[4]);
n1 =        mxGetScalar(prhs[5]);
n2 =        mxGetScalar(prhs[6]);
hPlan =     (cufftHandle)mxGetScalar(prhs[7]);
hReal =     (float *)mxGetData(prhs[8]);
lWindow =   (long)mxGetScalar(prhs[9]);
lAvg =      (long)mxGetScalar(prhs[10]);
lSum =      (long)mxGetScalar(prhs[11]);
}
else
    mexErrMsgTxt("fftcuda: Function requires 12 inputs");

// pointers to GPU arrays
dWindow = (float *)lWindow;
dAvg = (float *)lAvg;
dSum = (float *)lSum;

// size of output array
N = Nfft/2 + 1;
Npsd = n2 - n1 + 1;
size[0] = 1;
size[1] = Npsd;

/* Allocate working arrays on device */
cudaMalloc( (void**)&dReal,sizeof(float)*Nfft);
cudaMalloc( (void**)&dComplex,sizeof(cufftComplex)*N);

/* Copy input array to the device */
cudaMemcpy( (void*)dReal,(void*)hReal,sizeof(float)*Nfft,cudaMemcpyHostToDevice);

// setup for cuda functions
nBlocks = (int)(Nfft/blockSize);

/* multiply input array by window */
cudaMult <<< nBlocks, blockSize >>> (dReal,dWindow,dReal,Nfft);

/* Execute FFT on device */
     result = cufftExecR2C(hPlan, (cufftReal *)dReal, dComplex);

if (result == CUFFT_SETUP_FAILED)
    mexErrMsgTxt("CUFFT library failed to initialize.");
else if (result == CUFFT_INVALID_PLAN )
    mexErrMsgTxt("The hPlan parameter is not a valid handle.");
else if (result == CUFFT_INVALID_VALUE )
    mexErrMsgTxt("The idata or odata parameter is not valid.");
else if (result == CUFFT_EXEC_FAILED )
    mexErrMsgTxt("CUFFT failed to execute the transform on GPU.");

// setup for cuda functions
nBlocks = (int)(Npsd/blockSize) + (Npsd%blockSize);

/* Compute absolute value */
cudaAbs <<< nBlocks, blockSize >>> (&dComplex[n1-1],dReal,Npsd);

if (nlhs != 1)
    mexErrMsgTxt("fftcuda: Function requires 1 output: float pPxx");

plhs[0]=mxCreateNumericArray(2,size,mxSINGLE_CLASS,mxREAL);

pPxx = (float *)mxGetData(plhs[0]);

/* Copy result back to host */
cudaMemcpy( (void*)pPxx, (void*)dReal, sizeof(float)*Npsd,cudaMemcpyDeviceToHost);

/* free working arrays from gpu memory */
cudaFree((void*)dReal);
cudaFree((void*)dComplex);

return;
}

1 个答案:

答案 0 :(得分:1)

CUFFT库不仅仅有一个版本。由于CUFFT是CUDA工具包的一部分,因此每个新版本的CUDA工具包都会发布该库的更新版本。

如果您尝试使用较新版本的CUDA来使用较旧版本的库,那几乎可以肯定是您的问题。只需使用相同版本的CUFFT作为您的CUDA工具包,它应该可以工作。