multi_ray_trace is not working under MPI (mpi4py | OpenMPI 3.1.4, CentOS7.6) about pyvista HOT 4 OPEN

I don't have a good understanding of how embree works under the hood, but I don't believe it uses MPI.
Some questions that come to mind:

• Is there a good reason why you need to be running this ray trace code using MPI? I assume the example is concocted, since it really doesn't have any reason to be run with MPI.
• The code appears to work, and the warning is indeed just a warning. Can you just turn that warning off as it suggests?

from pyvista.

A little more explanation:

• Ray tracing itself does not need to be running under MPI, as you correctly pointed out.
  However, other parts of the simulation code I’m building are time-consuming, and I’m trying to apply MPI to those parts.

• The calculation results after this warning were quite different from the non-MPI single process calculation.

from pyvista.

Ok, so if the calculation is wrong then I can only assume the warning is for a good reason and you're getting memory corruption/errors/something. I've seen warnings like this before when using multiprocessing code across both Linux and macOS (which spawn subprocesses in different ways), and the ultimate solution was for me to write my code differently. Unfortunately sometimes different libraries don't play well together and there's not much you can do about that.

I don't really know anything about mpi4py, but here's some fumbly suggestions for you if you're feeling out of options:

• Play around with some test code and try and isolate exactly which part of your code is throwing the error.
• If the error is caused by embree (and if you don't actually have to do a lot of ray traces, so performance isn't an issue) then you could try doing the same thing with the VTK single ray trace function (available via pyvista), or even the rtree based ray tracing in trimesh.
• See if you can avoid the fork(), which may not be possible if you're stuck running via mpirun.
• Try and seperate what you're doing so the ray tracing can be run seperately from the MPI component.
• You say you're code is time consuming and so you're trying to apply MPI. Without knowing anything about what you're doing, I can only suggest to avoid MPI if you're not decomposing your problem in a way that specifically requires interprocess communication. Is there a different way you could speed up your code?

From what you've said, it seems to me like the error exists either in your code or in one of the dependencies, and there's probably nothing that can be changed in pyvista to fix it. Since you only seem to be able to reproduce it on an EOL OS on an old HPC, then I'm not convinced it would be worth the effort to try and fix anyway. Either way my opinion is this issue should probably be closed.

I'm happy for you to email me if you'd like to discuss your code a bit more specifically, can't promise I will be able to help though.

from pyvista.

I agree that it would be not worth the effort to fix and this issue should be closed.

I really thank you for your time and consideration.

from pyvista.