该解决方案已在另一个答案中给出: https://***.com/a/19208070/678093

The solution has already been given in another answer: https://***.com/a/19208070/678093

对于您的示例，这意味着:

For your example, this means:

将输入分配为cufftComplex:

Allocate input as cufftComplex:

cufftComplex *deviceInputData;
gpuErrchk(cudaMalloc((void**)&deviceInputData, DATASIZE * sizeof(cufftComplex)));
cudaMemcpy(deviceInputData, hostInputData, DATASIZE * sizeof(cufftReal), cudaMemcpyHostToDevice);

就地转换:

cufftStatus = cufftExecR2C(handle,  (cufftReal *)deviceInputData, deviceInputData);
gpuErrchk(cudaMemcpy(hostOutputData, deviceInputData, (DATASIZE / 2 + 1) * sizeof(cufftComplex), cudaMemcpyDeviceToHost));

btw:MATLAB还包含fft()的GPU加速版本，也许这对您也可能有用:

btw: MATLAB also contains a GPU accelerated version of fft(), maybe this could be useful for you as well: http://de.mathworks.com/help/distcomp/run-built-in-functions-on-a-gpu.html#btjw5gk