【发布时间】:2017-11-09 21:40:09
【问题描述】:
我尝试做一个简单的 fft 并比较 MATLAB 和 CUDA 之间的结果。
MATLAB: 9 个数字 1-9 的向量
I = [1 2 3 4 5 6 7 8 9];
并使用此代码:
fft(I)
给出结果:
45.0000 + 0.0000i
-4.5000 +12.3636i
-4.5000 + 5.3629i
-4.5000 + 2.5981i
-4.5000 + 0.7935i
-4.5000 - 0.7935i
-4.5000 - 2.5981i
-4.5000 - 5.3629i
-4.5000 -12.3636i
还有CUDA代码:
int FFT_Test_Function() {
int n = 9;
double* in = new double[n];
Complex* out = new Complex[n];
for (int i = 0; i<n; i++)
{
in[i] = i + 1;
}
// Allocate the buffer
cufftDoubleReal *d_in;
cufftDoubleComplex *d_out;
unsigned int out_mem_size = sizeof(cufftDoubleComplex)*n;
unsigned int in_mem_size = sizeof(cufftDoubleReal)*n;
cudaMalloc((void **)&d_in, in_mem_size);
cudaMalloc((void **)&d_out, out_mem_size);
// Save time stamp
milliseconds timeStart = getCurrentTimeStamp();
cufftHandle plan;
cufftResult res = cufftPlan1d(&plan, n, CUFFT_D2Z, 1);
if (res != CUFFT_SUCCESS) { cout << "cufft plan error: " << res << endl; return 1; }
cudaCheckErrors("cuda malloc fail");
cudaMemcpy(d_in, in, in_mem_size, cudaMemcpyHostToDevice);
cudaCheckErrors("cuda memcpy H2D fail");
res = cufftExecD2Z(plan, d_in, d_out);
if (res != CUFFT_SUCCESS) { cout << "cufft exec error: " << res << endl; return 1; }
cudaMemcpy(out, d_out, out_mem_size, cudaMemcpyDeviceToHost);
cudaCheckErrors("cuda memcpy D2H fail");
milliseconds timeEnd = getCurrentTimeStamp();
milliseconds totalTime = timeEnd - timeStart;
std::cout << "Total time: " << totalTime.count() << std::endl;
return 0;
}
在这个 CUDA 代码中我得到了结果:
您可以看到 CUDA 给出了 4 个零(单元格 5-9)。
我错过了什么?
非常感谢您的关注!
【问题讨论】:
标签: matlab math cuda signal-processing fft