out of stack space error ( stack overflow error)

Question

I'm trying to calculate a matrice multiplication of size N (square matrix) but I'm getting a stack overflow error(I'm new to Cuda ):

if I test the code for N < 300 everything is fine, but if I test it with N> 300 it does not work, and a stack overflow error was displayed but there is enough memory.in my graphics card GF 820M . if N = 300 then 300 * 300 * 4(size of float) = 360000 byte : necessary space in the device to allocate for an array of type float.and here it must allocate for 3 Table to do multiplication .therefore 360000 * 3 = 1080000 bytes and if I control the CudaMalloc nothing is displayed.

I inform you that my main goal is to test for N large enough.How do I solve that? thank you in advance for any help you might be able to provide.

#include <stdio.h>
#include<device_launch_parameters.h>
#include<cuda.h>
#include<time.h>
#include<cuda_runtime.h>
#include <math.h>

__global__ void MatrixMul( float *Md , float *Nd , float *Pd , const int WIDTH )
{   // calculate thread id
          unsigned  int row = blockIdx.y*blockDim.y+threadIdx.y;
          unsigned  int col = blockIdx.x*blockDim.x+threadIdx.x;
for (int k = 0 ; k<WIDTH ; k++ )
         { Pd[row*WIDTH + col]+= Md[row * WIDTH + k ] * Nd[ k * WIDTH + col] ;  }}


int main ()
{       const int i=64 ;
       cudaEvent_t start, stop;
        float time;
       cudaEventCreate(&start);
       cudaEventCreate(&stop);
       const int WIDTH =300;
       cudaError_t cudaStatus;

   float array1_h[WIDTH][WIDTH] ,array2_h[WIDTH][WIDTH] ,M_result_array_h[WIDTH][WIDTH];
   float *array1_d , *array2_d ,*M_result_array_d ; // device array



  // Allocate GPU buffers for 2 vectors (two input, one output) 

    cudaStatus = cudaMalloc((void **) &array1_d , WIDTH*WIDTH*sizeof (float));
    if (cudaStatus != cudaSuccess) {
        fprintf(stderr, "cudaMalloc failed!"); }  


    cudaStatus = cudaMalloc((void **) &array2_d , WIDTH*WIDTH*sizeof (float));
    if (cudaStatus != cudaSuccess) {
        fprintf(stderr, "cudaMalloc failed!"); }  




       for ( int i = 0 ; i<WIDTH ; i++ ) { 
           for (int j = 0 ; j<WIDTH ; j++ )
           { array1_h[i][j] = 1 ; array2_h[i][j] = 2 ; }}


  //copy host array to device array; cudaMemcpy ( dest , source , WIDTH , direction )



  cudaMemcpy ( array1_d , array1_h , WIDTH*WIDTH*sizeof (float) , cudaMemcpyHostToDevice ) ;

  cudaMemcpy ( array2_d , array2_h , WIDTH*WIDTH*sizeof (float) , cudaMemcpyHostToDevice ) ;



  //allocating memory for resultent device array

  cudaStatus = cudaMalloc((void **) &M_result_array_d , WIDTH*WIDTH*sizeof (float) ) ;
    if (cudaStatus != cudaSuccess) {
        fprintf(stderr, "cudaMalloc failed!"); }  

  //calling kernal

  dim3 dimBlock( i,i, 1 ) ;
  dim3 dimGrid ( ((WIDTH-1)/i) +1 , ((WIDTH-1)/i)+1 ,1 ) ;

  cudaEventRecord(start, 0);
MatrixMul <<<dimGrid,dimBlock>>> ( array1_d , array2_d ,M_result_array_d , WIDTH) ;
    cudaEventRecord(stop, 0);
   cudaEventSynchronize(stop);
   cudaEventElapsedTime(&time, start, stop);
   printf ("taille du probleme:%d Time for the kernel: %f \n",WIDTH,time);


  //copy back result_array_d to result_array_h

  cudaMemcpy(M_result_array_h , M_result_array_d , WIDTH*WIDTH*sizeof(float) , cudaMemcpyDeviceToHost) ;


  //printf the result array
  for (int i = 0 ; i<WIDTH ; i++ )
  { for (int j = 0 ; j < WIDTH ; j++ )
     {   printf ("%f   ",M_result_array_h[i][j] ) ; }
              printf ("\n") ; } 


    cudaFree(array1_d);
    cudaFree(array2_d);
    cudaFree(M_result_array_h);


  system("pause") ; }

For a simple program like this, you can define the matrixes as global so they aren't defined on the stack. — Anon Mail, Dec 06 '15 at 22:29

score 1 · Answer 1 · edited May 23 '17 at 12:07

The stack overflow problem is not CUDA related. These allocations:

float array1_h[WIDTH][WIDTH] ,array2_h[WIDTH][WIDTH] ,M_result_array_h[WIDTH][WIDTH];

are created by the compiler on the stack. The stack space is limited. (This is the host code, so the stack here has nothing to do with the GPU.)

One possible approach to fix this is to create dynamic allocations for these variables, which will be made on the heap, which doesn't have the same limits as the stack.

So one possible fix is to replace this:

float array1_h[WIDTH][WIDTH] ,array2_h[WIDTH][WIDTH] ,M_result_array_h[WIDTH][WIDTH];

with this:

typedef float ar_type[WIDTH];
ar_type *array1_h, *array2_h, *M_result_array_h;
array1_h = (ar_type *)malloc(WIDTH*WIDTH*sizeof(float));
array2_h = (ar_type *)malloc(WIDTH*WIDTH*sizeof(float));
M_result_array_h = (ar_type *)malloc(WIDTH*WIDTH*sizeof(float));

Also note that this:
```
const int i=64 ;
...
dim3 dimBlock( i,i, 1 ) ;
```
is not valid. You are requesting a 64x64 threadblock (4096 threads total) and this is not legal for any CUDA GPU. You can fix this particular issue by changing i to 32.
After fixing that, it seems that your kernel has no thread-check to prevent out-of-bounds threads from executing and generating out-of-bounds accesses. You can fix that by adding this thread-check immediately before the for-loop in your kernel:
```
if ((row < WIDTH) && (col < WIDTH))
```

Finally, this line has a typo:

cudaFree(M_result_array_h);

I think you meant:

cudaFree(M_result_array_d);

You can discover these other errors (2-4) if you add proper cuda error checking to your code, and/or run your code with cuda-memcheck.

thank you very much I correct the code everything goes well – Hamzaoui Rania Dec 07 '15 at 12:07 — Hamzaoui Rania, Dec 07 '15 at 12:07

score 0 · Answer 2 · answered Dec 06 '15 at 22:43

Use rtContextGetStackSize/rtContextSetStackSize to find out how large your stack is and set it larger if needed. Keep in mind that the memory on your graphic card is shared with other graphical processes and you can't use all of it.

Furthermore you can partition your matrix and compute a Partitioned Matrix Multiplication with a block-by-block algorithm, instead of the entire Matrix.

out of stack space error ( stack overflow error)

2 Answers2