Opt*_*mus 2 c++ cuda fft dynamic-arrays cufft
我试图找到一个动态分配的数组的fft.使用输入数组从主机复制到设备cudaMemcpy2D.然后获取fft(cufftExecR2C)并将结果从设备复制回主机.
所以我最初的问题是如何在fft中使用音高信息.然后我在这里找到了答案 - CUFFT:如何计算投手指针的fft?
但不幸的是它不起作用.我得到的结果是垃圾值.以下是我的代码.
#define NRANK 2
#define BATCH 10
#include "cuda_runtime.h"
#include "device_launch_parameters.h"
#include <cufft.h>
#include <stdio.h>
#include <iomanip>
#include <iostream>
#include <vector>
using namespace std;
const size_t NX = 4;
const size_t NY = 6;
int main()
{
// Input array (static) - host side
float h_in_data_static[NX][NY] ={
{0.7943 , 0.6020 , 0.7482 , 0.9133 , 0.9961 , 0.9261},
{0.3112 , 0.2630 , 0.4505 , 0.1524 , 0.0782 , 0.1782},
{0.5285 , 0.6541 , 0.0838 , 0.8258 , 0.4427, 0.3842},
{0.1656 , 0.6892 , 0.2290 , 0.5383 , 0.1067, 0.1712}
};
// --------------------------------
// Input array (dynamic) - host side
float *h_in_data_dynamic = new float[NX*NY];
// Set the values
size_t h_ipitch;
for (int r = 0; r < NX; ++r) // this can be also done on GPU
{
for (int c = 0; c < NY; ++c)
{ h_in_data_dynamic[NY*r + c] = h_in_data_static[r][c]; }
}
// --------------------------------
// Output array - host side
float2 *h_out_data_temp = new float2[NX*(NY/2+1)] ;
// Input and Output array - device side
cufftHandle plan;
cufftReal *d_in_data;
cufftComplex * d_out_data;
int n[NRANK] = {NX, NY};
// Copy input array from Host to Device
size_t ipitch;
cudaError cudaStat1 = cudaMallocPitch((void**)&d_in_data,&ipitch,NY*sizeof(cufftReal),NX);
cout << cudaGetErrorString(cudaStat1) << endl;
cudaError cudaStat2 = cudaMemcpy2D(d_in_data,ipitch,h_in_data_dynamic,NY*sizeof(float),NY*sizeof(float),NX,cudaMemcpyHostToDevice);
cout << cudaGetErrorString(cudaStat2) << endl;
// Allocate memory for output array - device side
size_t opitch;
cudaError cudaStat3 = cudaMallocPitch((void**)&d_out_data,&opitch,(NY/2+1)*sizeof(cufftComplex),NX);
cout << cudaGetErrorString(cudaStat3) << endl;
// Performe the fft
int rank = 2; // 2D fft
int istride = 1, ostride = 1; // Stride lengths
int idist = 1, odist = 1; // Distance between batches
int inembed[] = {ipitch, NX}; // Input size with pitch
int onembed[] = {opitch, NX}; // Output size with pitch
int batch = 1;
cufftPlanMany(&plan, rank, n, inembed, istride, idist, onembed, ostride, odist, CUFFT_R2C, batch);
//cufftPlan2d(&plan, NX, NY , CUFFT_R2C);
cufftSetCompatibilityMode(plan, CUFFT_COMPATIBILITY_NATIVE);
cufftExecR2C(plan, d_in_data, d_out_data);
cudaThreadSynchronize();
// Copy d_in_data back from device to host
cudaError cudaStat4 = cudaMemcpy2D(h_out_data_temp,(NY/2+1)*sizeof(float2), d_out_data, opitch, (NY/2+1)*sizeof(cufftComplex), NX, cudaMemcpyDeviceToHost);
cout << cudaGetErrorString(cudaStat4) << endl;
// Print the results
for (int i = 0; i < NX; i++)
{
for (int j =0 ; j< NY/2 + 1; j++)
printf(" %f + %fi",h_out_data_temp[i*(NY/2+1) + j].x ,h_out_data_temp[i*(NY/2+1) + j].y);
printf("\n");
}
cudaFree(d_in_data);
return 0;
}
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我认为问题在于cufftPlanMany.我该如何解决这个问题?
您可能需要仔细研究文档的高级数据布局部分.
我认为上一个被链接的问题有些令人困惑,因为这个问题是以相反的顺序传递width和height参数,这是我对袖口2D计划所期望的.然而,答案然后模仿该顺序,因此它至少是一致的.
其次,你在前面的问题错过了那些在传递的"间距"参数inembed和onembed是不一样的,你会收到来自俯仰参数cudaMallocPitch操作.它们必须按输入和输出数据集中每个数据元素的字节数进行缩放.我实际上并不完全确定这是inembed和onembed参数的预期用途,但似乎有效.
当我调整您的代码以解释上述两个更改时,我似乎得到了有效的结果,至少它们似乎在合理的范围内.您现在已经发布了几个关于2D FFT的问题,您已经说过结果不正确.我不能在脑子里做这些2D FFT,所以我建议将来你指出你期望的数据.
这有我做的改变:
#define NRANK 2
#define BATCH 10
#include "cuda_runtime.h"
#include "device_launch_parameters.h"
#include <cufft.h>
#include <stdio.h>
#include <iomanip>
#include <iostream>
#include <vector>
using namespace std;
const size_t NX = 4;
const size_t NY = 6;
int main()
{
// Input array (static) - host side
float h_in_data_static[NX][NY] ={
{0.7943 , 0.6020 , 0.7482 , 0.9133 , 0.9961 , 0.9261},
{0.3112 , 0.2630 , 0.4505 , 0.1524 , 0.0782 , 0.1782},
{0.5285 , 0.6541 , 0.0838 , 0.8258 , 0.4427, 0.3842},
{0.1656 , 0.6892 , 0.2290 , 0.5383 , 0.1067, 0.1712}
};
// --------------------------------
// Input array (dynamic) - host side
float *h_in_data_dynamic = new float[NX*NY];
// Set the values
size_t h_ipitch;
for (int r = 0; r < NX; ++r) // this can be also done on GPU
{
for (int c = 0; c < NY; ++c)
{ h_in_data_dynamic[NY*r + c] = h_in_data_static[r][c]; }
}
// --------------------------------
int owidth = (NY/2)+1;
// Output array - host side
float2 *h_out_data_temp = new float2[NX*owidth] ;
// Input and Output array - device side
cufftHandle plan;
cufftReal *d_in_data;
cufftComplex * d_out_data;
int n[NRANK] = {NX, NY};
// Copy input array from Host to Device
size_t ipitch;
cudaError cudaStat1 = cudaMallocPitch((void**)&d_in_data,&ipitch,NY*sizeof(cufftReal),NX);
cout << cudaGetErrorString(cudaStat1) << endl;
cudaError cudaStat2 = cudaMemcpy2D(d_in_data,ipitch,h_in_data_dynamic,NY*sizeof(float),NY*sizeof(float),NX,cudaMemcpyHostToDevice);
cout << cudaGetErrorString(cudaStat2) << endl;
// Allocate memory for output array - device side
size_t opitch;
cudaError cudaStat3 = cudaMallocPitch((void**)&d_out_data,&opitch,owidth*sizeof(cufftComplex),NX);
cout << cudaGetErrorString(cudaStat3) << endl;
// Performe the fft
int rank = 2; // 2D fft
int istride = 1, ostride = 1; // Stride lengths
int idist = 1, odist = 1; // Distance between batches
int inembed[] = {NX, ipitch/sizeof(cufftReal)}; // Input size with pitch
int onembed[] = {NX, opitch/sizeof(cufftComplex)}; // Output size with pitch
int batch = 1;
if ((cufftPlanMany(&plan, rank, n, inembed, istride, idist, onembed, ostride, odist, CUFFT_R2C, batch)) != CUFFT_SUCCESS) cout<< "cufft error 1" << endl;
//cufftPlan2d(&plan, NX, NY , CUFFT_R2C);
if ((cufftSetCompatibilityMode(plan, CUFFT_COMPATIBILITY_NATIVE)) != CUFFT_SUCCESS) cout << "cufft error 2" << endl;
if ((cufftExecR2C(plan, d_in_data, d_out_data)) != CUFFT_SUCCESS) cout << "cufft error 3" << endl;
cudaDeviceSynchronize();
// Copy d_in_data back from device to host
cudaError cudaStat4 = cudaMemcpy2D(h_out_data_temp,owidth*sizeof(float2), d_out_data, opitch, owidth*sizeof(cufftComplex), NX, cudaMemcpyDeviceToHost);
cout << cudaGetErrorString(cudaStat4) << endl;
// Print the results
for (int i = 0; i < NX; i++)
{
for (int j =0 ; j< owidth; j++)
printf(" %f + %fi",h_out_data_temp[i*owidth + j].x ,h_out_data_temp[i*owidth + j].y);
printf("\n");
}
cudaFree(d_in_data);
return 0;
}
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