CUDA-在gpu上生成数组并使用内核对其进行修改

Question

in this code im generating 1D array of floats on a gpu using CUDA. The numbers are between 0 and 1. For my purpose i need them to be between -1 and 1 so i have made simple kernel to multiply each element by 2 and then substract 1 from it. However something is going wrong here. When i print my original array into .bmp i get this http://i.imgur.com/IS5dvSq.png (typical noise pattern). But when i try to modify that array with my kernel i get blank black picture http://imgur.com/cwTVPTG . The program is executable but in the debug i get this:

First-chance exception at 0x75f0c41f in Midpoint_CUDA_Alpha.exe: Microsoft C++ exception: cudaError_enum at memory location 0x003cfacc..

First-chance exception at 0x75f0c41f in Midpoint_CUDA_Alpha.exe: Microsoft C++ exception: cudaError_enum at memory location 0x003cfb08..

First-chance exception at 0x75f0c41f in Midpoint_CUDA_Alpha.exe: Microsoft C++ exception: [rethrow] at memory location 0x00000000..

i would be thankfull for any help or even little hint in this matter. Thanks ! (edited)

#include <device_functions.h>
#include <time.h>
#include <stdio.h>
#include <stdlib.h>
#include "stdafx.h"
#include "EasyBMP.h"
#include <curand.h> //curand.lib must be added in project propetties > linker > input
#include "device_launch_parameters.h"

float *heightMap_cpu;
float *randomArray_gpu;
int randCount = 0;
int rozmer = 513;

void createRandoms(int size){
    curandGenerator_t generator;
    cudaMalloc((void**)&randomArray_gpu, size*size*sizeof(float));
    curandCreateGenerator(&generator,CURAND_RNG_PSEUDO_XORWOW);
    curandSetPseudoRandomGeneratorSeed(generator,(int)time(NULL));
    curandGenerateUniform(generator,randomArray_gpu,size*size);
}

__global__ void polarizeRandoms(int size, float *randomArray_gpu){
    int index = threadIdx.x + blockDim.x * blockIdx.x;
    if(index<size*size){
        randomArray_gpu[index] = randomArray_gpu[index]*2.0f - 1.0f;
    }
}

//helper fucnction for getting address in 1D using 2D coords
int ad(int x,int y){
    return x*rozmer+y;
}

void printBmp(){
    BMP AnImage;
    AnImage.SetSize(rozmer,rozmer);
    AnImage.SetBitDepth(24);
    int i,j;
    for(i=0;i<=rozmer-1;i++){
        for(j=0;j<=rozmer-1;j++){
            AnImage(i,j)->Red = (int)((heightMap_cpu[ad(i,j)]*127)+128);
            AnImage(i,j)->Green = (int)((heightMap_cpu[ad(i,j)]*127)+128);
            AnImage(i,j)->Blue = (int)((heightMap_cpu[ad(i,j)]*127)+128);
            AnImage(i,j)->Alpha = 0;
        }
    }
    AnImage.WriteToFile("HeightMap.bmp");
}

int main(){
    createRandoms(rozmer);
    polarizeRandoms<<<((rozmer*rozmer)/1024)+1,1024>>>(rozmer,randomArray_gpu);
    heightMap_cpu = (float*)malloc((rozmer*rozmer)*sizeof(float));
    cudaMemcpy(heightMap_cpu,randomArray_gpu,rozmer*rozmer*sizeof(float),cudaMemcpyDeviceToHost);
    printBmp();

    //cleanup
    cudaFree(randomArray_gpu);
    free(heightMap_cpu);
    return 0;
}

Answer 1

This is wrong:

cudaMalloc((void**)&randomArray_gpu, size*size*sizeof(float));

We don't use cudaMalloc with __device__ variables. If you do proper cuda error checking I'm pretty sure that line will throw an error.

If you really want to use a __device__ pointer this way, you need to create a separate normal pointer, cudaMalloc that, then copy the pointer value to the device pointer using cudaMemcpyToSymbol :

float *my_dev_pointer;
cudaMalloc((void**)&my_dev_pointer, size*size*sizeof(float));
cudaMemcpyToSymbol(randomArray_gpu, &my_dev_pointer, sizeof(float *));

Whenever you are having trouble with your CUDA programs, you should do proper cuda error checking. It will likely focus your attention on what is wrong.

And, yes, kernels can access __device__ variables without the variable being passed explicitly as a parameter to the kernel.

The programming guide covers the proper usage of __device__ variables and the api functions that should be used to access them from the host.