I essentially already answer this question parallelizing-matrix-times-a-vector-by-columns-and-by-rows-with-openmp.
You have a race condition when you write to results[y]. To fix this, and still parallelize the inner loop, you have to make private versions of results[y], fill them in parallel, and then merge them in a critical section.
In the code below I assume you're using double, replace it with float or int or whatever datatype you're using (note that your inner loop goes over the first index of matrix[i][y] which is cache unfriendly).
#pragma omp parallel num_threads(4)
{
int y,i;
double* results_private = (double*)calloc(matrix_size, sizeof(double));
for(y = 0; y < matrix_size ; y++) {
#pragma omp for
for(i = 0; i < matrix_size; i++) {
results_private[y] += vector[i]*matrix[i][y];
}
}
#pragma omp critical
{
for(y=0; y
If this is homework assignment and you want to really impress your instructor then it's possible to do the merging without a critical section. See this link to get an idea on what to do fill-histograms-array-reduction-in-parallel-with-openmp-without-using-a-critic though I can't promise it will be faster.
