What are the Alternatives to std::vector in C OpenMP Parallel For Loops?

C OpenMP Parallel For Loop: Alternatives to std::vector

std::vector is a versatile data structure commonly used in parallel for loops with OpenMP. However, there are situations where alternatives might be more suitable, particularly when prioritizing speed or encountering issues with resizing during the loop.

One option for a shared data structure is to use a custom reduction with OpenMP 4.0's #pragma omp declare reduction. This reduces the need for critical sections and simplifies parallel code.

Another alternative for preserving order is to employ static scheduling with ordered sections. This ensures that each thread writes to a specific portion of the vector in order, eliminating the need for merging later.

In scenarios where resizing is necessary, a method using pointer arrays for tracking thread-specific prefix sums can be adopted. This approach avoids the overhead of resizing on the critical path.

Here are code examples for these alternatives:

// Custom reduction
#pragma omp declare reduction (merge: std::vector<int>: omp_out.insert(omp_out.end(), omp_in.begin(), omp_in.end())

std::vector<int> vec;
#pragma omp parallel for reduction(merge: vec)
for (int i = 0; i <pre class="brush:php;toolbar:false">// Static scheduling with ordered sections
std::vector<int> vec;
#pragma omp parallel
{
    int ithread = omp_get_thread_num();
    int nthreads = omp_get_num_threads();
    #pragma omp single
    {
        prefix = new size_t[nthreads + 1];
        prefix[0] = 0;
    }
    std::vector<int> vec_private;
    #pragma omp for schedule(static) nowait
    for (int i = 0; i <p>Selecting the appropriate alternative for your specific case depends on the requirements and performance considerations. Experimentation andprofiling can help determine the most optimal solution.</p></int></int>

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