How to collect data for each thread OpenMP

Question

I'm new to OpenMP and try to sort out the issue of collecting data from threads. I study the example of applying OpenMP on Monte-Carlo method (square of a circle inscribed into a square). I understood how the following code works:

unsigned pointsInside = 0;
#pragma omp parallel for num_threads(threadNum) shared(threadNum) reduction(+: pointsInside)
for (unsigned i = 0; i < threadNum; i++)  { ... }

Am I right that originally pointsInside is a variable but OpenMP represents it as an array and than the mantra reduction(+: pointsInside) sums over the elements of the "array"?

But the main question is how to collect information directly into an array or vector? I tried to declare array or vector and provide pointer or address into OpenMP via shared and collect information for each thread at corresponding index. But it works slower than the way with the variable and reduction . Such the approach with vector or array is needed for me for my current project. Thanks a lot!

UPD: When I said above that "it works slower" I meant comparison of two realizations of the Monte-Carlo method: 1) via shared and a vector/array, and 2) via a scalar variable and reduction . The first case is faster. My guess and question about it below.

I would like to rephrase my question more clear. I create a vector/array and provide it into OpenMP via shared . I want to collect data for each thread at corresponding index in vector/array. Under this approach I don't need any synchronization of access to the vector/array. Is it true that OpenMP enable synchronization by default when I use shared . If it is so, then how to disable it. Or may be another approaches exist. If it is not so, then how to share vector/array into the parallel part correctly and without synchronization of access.

I'd like to apply this technique for my project where I want to sort through different permutations in parallel part, collect each permutation and scalar result for it outside of the parallel part. Then sort the results and choose the best one.

Answer 1

A partial answer:

Am I right that originally pointsInside is a variable but OpenMP represents it as an array and than the mantra reduction(+: pointsInside) sums over the elements of the "array"?

I think it is better to think of pointsInside as a scalar. When the parallel region starts the run-time takes care of creating individual scalars, perhaps you might think of them as myPointsInside , one such scalar for each thread. When the parallel region finishes the run-time reduces the values of all the thread scalars onto the original scalar pointsInside . This is just about what OpenMP actually does behind the scenes.

As to the rest of your question:

Yes, you can perform reductions onto arrays - but this was only added to OpenMP, for C and C++ programs, in OpenMP 4.5 (I think). What goes on is much the same as for the scalar case. This Q&A provides some assistance - Is it possible to do a reduction on an array with openmp?

As to the speed, it's difficult to answer that without a much clearer understanding of what comparisons you are making. But it's very easy to write parallel reductions on arrays which incur a significant penalty in performance from the phenomenon of false sharing , about which you may wish to inform yourself.