MATLAB Answers

How to convert complex float to complex integer in MEX gateway function?

1 view (last 30 days)
Hi,
I'm trying to write a MEX gateway function (in CUDA) to add two complex integer arrays given by Matlab. Currently, the following code works fine for 2 complex float arrays. Could you please let me know how should i change the code to be able to read complex integer from Matlab? it should be about the way i define prhs!!
#include <cuda_runtime.h>
#include "device_launch_parameters.h"
#include <stdio.h>
#include "cuda.h"
#include <iostream>
#include <mex.h>
#include "gpu/mxGPUArray.h"
#include "matrix.h"
#include <thrust/complex.h>
#include <string.h>
//#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);
// }
//}
//
typedef thrust::complex<float> fcomp;
__device__ void atAddComplex(fcomp* a, fcomp b) {
float* x = (float*)a; /* cast x pointer to the real part */
float* y = x + 1; /* cast the y pointer to the following mem. address (imaginary part) */
//use atomicAdd for double variables
atomicAdd(x, b.real());
atomicAdd(y, b.imag());
}
__global__ void add(fcomp * Device_DataRes, fcomp * Device_Data1, fcomp * Device_Data2, int N) {
int TID = threadIdx.y * blockDim.x + threadIdx.x;
int BlockOFFset = blockDim.x * blockDim.y * blockIdx.x;
int GID_RowBased = BlockOFFset + TID;
if (GID_RowBased < N) {
//Device_DataRes[GID_RowBased] = Device_Data1[GID_RowBased] + Device_Data2[GID_RowBased];
//Device_Data1[GID_RowBased] = Device_Data1[GID_RowBased] + Device_Data2[GID_RowBased];
atAddComplex(&Device_Data1[GID_RowBased], Device_Data2[GID_RowBased]);
// atomicAdd(&Device_Data1[GID_RowBased], Device_Data2[GID_RowBased]);
}
}
void mexFunction(int nlhs, mxArray* plhs[],
int nrhs, const mxArray* prhs[]) {
mxInitGPU();
int N = 1000;
int ArrayByteSize = sizeof(fcomp) * N;
fcomp* Device_Data1;
fcomp* Device_Data2;
fcomp* DataRes;
fcomp* Device_DataRes;
mxComplexSingle* Data1 = mxGetComplexSingles(prhs[0]);
mxComplexSingle* Data2 = mxGetComplexSingles(prhs[1]);
(cudaMalloc((void**)&Device_Data1, ArrayByteSize));
(cudaMemcpy(Device_Data1, Data1, ArrayByteSize, cud SoaMemcpyHostToDevice));
(cudaMalloc((void**)&Device_Data2, ArrayByteSize));
(cudaMemcpy(Device_Data2, Data2, ArrayByteSize, cudaMemcpyHostToDevice));
plhs[0] = mxCreateNumericMatrix(N, 1, mxSINGLE_CLASS, mxCOMPLEX);
DataRes = static_cast<fcomp*> (mxGetData(plhs[0]));
(cudaMalloc((void**)&Device_DataRes, ArrayByteSize));
dim3 block(1024);
int GridX = (N / block.x + 1);
dim3 grid(GridX);//SystemSetup.NumberOfTransmitter
add << <grid, block >> > (Device_DataRes, Device_Data1, Device_Data2, N);
(cudaMemcpy(DataRes, Device_Data1, ArrayByteSize, cudaMemcpyDeviceToHost));
cudaFree(Device_Data1);
cudaFree(Device_Data2);
cudaFree(Device_DataRes);
//mxGPUDestroyGPUArray(MediumX);
}

Accepted Answer

James Tursa
James Tursa on 22 Jun 2021
Edited: James Tursa on 22 Jun 2021
I would guess you can just use the appropriate data types. E.g.,
mxComplexInt32* Data1 = mxGetComplexInt32s(prhs[0]);
mxComplexInt32* Data2 = mxGetComplexInt32s(prhs[1]);
etc.
Or, if you wanted to get at the pointers more directly since you will be casting them anyway, then just
int* Data1 = (int *) mxGetData(prhs[0]);
int* Data2 = (int *) mxGetData(prhs[1]);
etc.
This all assumes the R2018a+ interleaved complex data model of MATLAB of course.

More Answers (0)

Products


Release

R2021a

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by