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What is the proper way to parallelize a multi-dimensional embarrassingly parallel loop in OpenMP? The number of dimensions is known at compile-time, but which dimensions will be large is not. Any of them may be one, two, or a million. Surely I don't want N omp parallel 's for an N-dimensional loop... Thoughts: The problem is conceptually simple. Only the outermost 'large' loop needs to be parallelized, but the loop dimensions are unknown at compile-time and may change. Will dynamically setting omp_set_num_threads(1) and #pragma omp for schedule(static, huge_number) make certain loop parallelizations a no-op? Will this have undesired side-effects/overhead? Feels like a kludge. The OpenMP Specification (2.10, A.38, A.39) tells the difference between conforming and non-conforming nested parallelism, but doesn't suggest the best approach to this problem. Re-ordering the loops is possible but may result in a lot of cache-misses. Unrolling is possible but non-trivial. Is there another way? Here's what I'd like to parallelize: for(i0=0; i0<n[0]; i0++) { for(i1=0; i1<n[1]; i1++) { ... for(iN=0; iN<n[N]; iN++) { <embarrasingly parallel operations> } ... } } Thanks!

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