How Can Array Reduction Be Achieved in OpenMP When It's Not Directly Supported?

Reducing on Arrays in OpenMP

OpenMP provides parallel execution capabilities for a vast range of applications. However, a common question arises regarding array reduction, which is not directly supported by OpenMP.

Alternative Solution

While native array reduction is not available, there are alternative methods to achieve similar functionality in C/C :

Method 1: Private Array Reduction with Critical Section

In this approach, each thread operates on a private copy of the array, accumulating its contributions. When all threads have completed, a critical section is employed to merge the individual array elements into the original array.

int S [10] = {0};
#pragma omp parallel
{
    int S_private[10] = {0};
    #pragma omp for
    for (int n=0 ; n<10 ; ++n ) {
        for (int m=0; m<=n; ++m){
            S_private[n] += A[m];
        }
    }
    #pragma omp critical
    {
        for(int n=0; n<10; ++n) {
            S[n] += S_private[n];
        }
    }
}

Method 2: Thread-Local Array Reduction

This method eliminates the critical section by creating an intermediate array with dimensions 10*nthreads. Threads fill this array in parallel and then merge it into the original array.

int S [10] = {0};
int *S_private;
#pragma omp parallel
{
    const int nthreads = omp_get_num_threads();
    const int ithread = omp_get_thread_num();

    #pragma omp single 
    {
        S_private = new int[10*nthreads];
        for(int i=0; i<(10*nthreads); i++) S_private[i] = 0;
    }
    #pragma omp for
    for (int n=0 ; n<10 ; ++n )
    {
        for (int m=0; m<=n; ++m){
            S_private[ithread*10+n] += A[m];
        }
    }
    #pragma omp for
    for(int i=0; i<10; i++) {
        for(int t=0; t<nthreads; t++) {
            S[i] += S_private[10*t + i];
        }
    }
}
delete[] S_private;

These approaches overcome the lack of native array reduction in OpenMP, allowing for efficient accumulation of array elements in parallel.

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