Difference between revisions of "CUDA by example/chapter 4"
From Teknologisk videncenter
m |
m (→CUDA threaded example) |
||
Line 45: | Line 45: | ||
// allocate the memory on the GPU | // allocate the memory on the GPU | ||
− | + | cudaMalloc( (void**)&dev_a, N * sizeof(int) ); | |
− | + | cudaMalloc( (void**)&dev_b, N * sizeof(int) ); | |
− | + | cudaMalloc( (void**)&dev_c, N * sizeof(int) ); | |
// fill the arrays 'a' and 'b' on the CPU | // fill the arrays 'a' and 'b' on the CPU | ||
Line 56: | Line 56: | ||
// copy the arrays 'a' and 'b' to the GPU | // copy the arrays 'a' and 'b' to the GPU | ||
− | + | cudaMemcpy( dev_a, a, N * sizeof(int), | |
− | cudaMemcpyHostToDevice | + | cudaMemcpyHostToDevice ); |
− | + | cudaMemcpy( dev_b, b, N * sizeof(int), | |
− | cudaMemcpyHostToDevice | + | cudaMemcpyHostToDevice ); |
add<<<N,1>>>( dev_a, dev_b, dev_c ); | add<<<N,1>>>( dev_a, dev_b, dev_c ); | ||
// copy the array 'c' back from the GPU to the CPU | // copy the array 'c' back from the GPU to the CPU | ||
− | + | cudaMemcpy( c, dev_c, N * sizeof(int), | |
− | cudaMemcpyDeviceToHost | + | cudaMemcpyDeviceToHost ); |
// display the results | // display the results | ||
Line 73: | Line 73: | ||
// free the memory allocated on the GPU | // free the memory allocated on the GPU | ||
− | + | cudaFree( dev_a ); | |
− | + | cudaFree( dev_b ); | |
− | + | cudaFree( dev_c ); | |
return 0; | return 0; | ||
} | } | ||
</source> | </source> |
Revision as of 09:30, 5 December 2010
Normal single threaded programming
#define N 10
void add( int *a, int *b, int *c ) {
int tid = 0; // this is CPU zero, so we start at zero
while (tid < N) {
c[tid] = a[tid] + b[tid];
tid += 1; // we have one CPU, so we increment by one
}
}
int main( void ) {
int a[N], b[N], c[N];
// fill the arrays 'a' and 'b' on the CPU
for (int i=0; i<N; i++) {
a[i] = -i;
b[i] = i * i;
}
add( a, b, c );
// display the results
for (int i=0; i<N; i++) {
printf( "%d + %d = %d\n", a[i], b[i], c[i] );
}
return 0;
}
CUDA threaded example
#define N 10
__global__ void add( int *a, int *b, int *c ) {
int tid = blockIdx.x; // this thread handles the data at its thread id
if (tid < N)
c[tid] = a[tid] + b[tid];
}
int main( void ) {
int a[N], b[N], c[N];
int *dev_a, *dev_b, *dev_c;
// allocate the memory on the GPU
cudaMalloc( (void**)&dev_a, N * sizeof(int) );
cudaMalloc( (void**)&dev_b, N * sizeof(int) );
cudaMalloc( (void**)&dev_c, N * sizeof(int) );
// fill the arrays 'a' and 'b' on the CPU
for (int i=0; i<N; i++) {
a[i] = -i;
b[i] = i * i;
}
// copy the arrays 'a' and 'b' to the GPU
cudaMemcpy( dev_a, a, N * sizeof(int),
cudaMemcpyHostToDevice );
cudaMemcpy( dev_b, b, N * sizeof(int),
cudaMemcpyHostToDevice );
add<<<N,1>>>( dev_a, dev_b, dev_c );
// copy the array 'c' back from the GPU to the CPU
cudaMemcpy( c, dev_c, N * sizeof(int),
cudaMemcpyDeviceToHost );
// display the results
for (int i=0; i<N; i++) {
printf( "%d + %d = %d\n", a[i], b[i], c[i] );
}
// free the memory allocated on the GPU
cudaFree( dev_a );
cudaFree( dev_b );
cudaFree( dev_c );
return 0;
}