我对CUDA上的Matrix乘法感到震惊.得到的乘积矩阵始终为零.我已经阅读了一些示例代码,例如cuda中的矩阵乘法来解决我的问题,但都是徒劳的.
除了0的不稳定结果之外,"宽度"(下面的代码)的最大大小甚至不是512.我无法调试问题所在.也许我们可以在StackOverflow上讨论它.
我指的是"编程大规模并行处理器"
#include<cuda.h>
#include<stdio.h>
int main(void) {
void MatrixMultiplication(float *, float *, float *, int);
const int Width = 5;
float M[Width*Width], N[Width*Width], P[Width*Width];
for(int i = 0; i < (Width*Width) ; i++) {
M[i] = 5;
N[i] = 5;
P[i] = 0;
}
MatrixMultiplication(M, N, P, Width);
for(int i = 0; i < (Width*Width) ; i++) {
printf("%d \n", P[i]);
}
int quit;
scanf("%d",&quit);
return 0;
}
//Matrix multiplication kernel - thread specification
__global__ void MatrixMulKernel(float *Md, float *Nd, float *Pd, int Width) {
//2D Thread ID
int tx = threadIdx.x;
int ty = threadIdx.y;
//Pvalue stores the Pd element that is computed by the thread
float Pvalue = 0;
for(int k = 0; k < Width ; ++k) {
float Mdelement = Md[ty*Width + k];
float Ndelement = Nd[k*Width + tx];
Pvalue += (Mdelement*Ndelement);
}
Pd[ty*Width + tx] = Pvalue;
}
void MatrixMultiplication(float *M, float *N, float *P, int Width) {
int size = Width*Width*sizeof(float);
float *Md, *Nd, *Pd;
//Transfer M and N to device memory
cudaMalloc((void**)&Md, size);
cudaMemcpy(Md,M,size,cudaMemcpyHostToDevice);
cudaMalloc((void**)&Nd, size);
cudaMemcpy(Nd,N,size,cudaMemcpyHostToDevice);
//Allocate P on the device
cudaMalloc((void**)&Pd,size);
//Setup the execution configuration
dim3 dimBlock(Width,Width);
dim3 dimGrid(1,1);
//Launch the device computation threads!
MatrixMulKernel<<<dimGrid,dimBlock>>>(Md,Nd,Pd,Width);
//Transfer P from device to host
cudaMemcpy(P,Pd,size,cudaMemcpyDeviceToHost);
//Free device matrices
cudaFree(Md);
cudaFree(Nd);
cudaFree(Pd);
}
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我知道出了什么问题了。我们来分析一下:
第一点:寻求消除单调的“零值”
如前所述,您必须替换 printf("%d \n", P[i]);
为 printf("%f \n", P[i]);
第 2 点:为什么程序失败并显示 Width 512 值?
实际上,即使是很小的值(例如 23)也会失败。为什么?因为 23*23 > 512(迄今为止 GPU 每个块可以拥有的最大线程数!)