OpenMP is a shared-memory parallelism API for C, C++, and Fortran. Add a #pragma omp directive before a loop or block to parallelize it across available cores. The compiler handles thread creation and synchronization; if it doesn't support OpenMP, directives are silently ignored and the program runs serially, making debugging easy.

The execution model is fork-join: a single thread forks into a worker team at #pragma omp parallel, they execute concurrently, then join back. Thread count defaults to the number of logical cores, configurable via OMP_NUM_THREADS=N at runtime or omp_set_num_threads(n) in code. Compile with -fopenmp and include <omp.h> for the omp_* runtime functions.

// compile: gcc -O2 -fopenmp -o sum sum.c
// run: OMP_NUM_THREADS=4 ./sum
// description: parallel reduction using a single pragma
 
#include <omp.h>
#include <stdio.h>
 
int main(void) {
    long n = 1000000000L, sum = 0;
    double t = omp_get_wtime();
    #pragma omp parallel for reduction(+:sum)
    for (long i = 0; i < n; i++)
        sum += i;
    printf("sum=%ld  time=%.2fs\n", sum, omp_get_wtime() - t);
    return 0;
}

On a 4-core machine this runs roughly 4× faster with -fopenmp than without. Amdahl's law limits speedup when part of the program is inherently serial; reducing overhead like false sharing and load imbalance matters more than just adding threads.

1. Data sharing
2. Parallel loops
3. Collapse
4. Reduction
5. Scheduling
6. SIMD
7. Tasks
8. Single
9. Master
10. Sections
11. Barrier
12. Nowait
13. Critical sections
14. Atomic
15. Flush
16. False sharing
17. Thread affinity
18. Time measurement
19. Overview