I am trying to do some math calculations in parallel and sequential processing to see the difference.

How can I print from a loop with OpenMP parallel execution? I am hoping to avoid critical code or similar which (I hear) can really slow down the execution.

Basically I have a parallel loop that has a couple inherently serial variables that I pre-calculate. However I want to be able to set off a given iteration of the for loop once it’s serial variables are calculated.
Essentially I want something like this:

I am running a simulation of random events happening in accordance with a given set of probabilities, until n events are hit, and repeating for as many iterations as desired. When I run this sequentially, it finishes a small test set of 24 iterations in 5 seconds. When I set a higher number of threads (16), the time involved becomes 55 seconds. I made these comparisons using time bash -c "...".

I want to implement a function to voxelize the triangular mesh model. Since I need to traverse each triangle, I want to use Openmp for parallelization acceleration. When the number of triangles is large, using Openmp is effective, but when the number of triangles is small, the cost of enabling Openmp is too high. Therefore, I want to dynamically choose whether to use Openmp based on the number of triangles, how to implement it in the code, and whether it can be achieved without a simple if else, because the two parts of the code are almost identical, Openmp only has two additional instructions, so I avoid duplicate code.

I’m working on a C program that applies a linear transformation to a 3D point cloud using a transformation matrix T. Each point is a row in an n×3 matrix, and T is a 3×3 matrix. My goal is to update the point cloud in place, but I’m encountering issues with dependencies during the parallel update. I want to avoid allocating an additional matrix for the results due to memory constraints.

#pragma omp parallel num_threads(min_thread) shared(count)
{