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aboria / Aboria

Enables computations over a set of particles in N-dimensional space
https://aboria.github.io/Aboria
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MPI Parallelization? #45

Open muhammadhasyim opened 4 years ago

muhammadhasyim commented 4 years ago

Dear @martinjrobins,

Thank you for developing Aboria! I've thoroughly enjoyed using this library for analyzing molecular dynamics data in my work. One of the things that I've been curious about is if you are thinking about developing Aboria to support MPI parallelization.

I suppose this is a "bizarre" request because it doesn't quite fit the goal of Aboria. After all, it's a lightweight header-only library and GPU parallelization is supported externally through Thrust). A lot of my work requires normal mode analysis and numerical linear algebra on a dataset derived from particle simulations. The libraries I've been using to efficiently perform these calculations (PETSc and SLEPc) for large systems is parallelized using MPI.

Of course, I can implement Aboria on an MPI+OpenMP program (that's what I've been doing actually) but in terms of memory management, I feel that this is relatively awkward. For instance, it would be great if the memory on particle data can be distributed.

Anyways, I apologize if this is a weird request/question. But I hope you may consider my thoughts as possible future features on Aboria!

All the best,

Muhammad

martinjrobins commented 4 years ago

hi @muhammadhasyim, thanks for getting in touch regarding Aboria and glad its been helping with your work! :) I don't have any plans of adding MPI parallelization at this current time, but it is certainly something that would be useful to add, and I'd be happy if anyone else wanted to give it a try!

In terms of how it could be done, most of the spatial data structures and particle container are based on having an underlying vector type, with associated algorithms (e.g. transform, accumulate, scan etc) that operate on that vector. That is how it swaps between using std::vector and thrust::device_vector. So the challenge would be to find/implement an MPI distributed vector that satisfies the std::vector api, and implement the required distributed algorithms. I think HPX were heading in this direction the last time I looked (https://github.com/STEllAR-GROUP/hpx), but not sure how far they got.

muhammadhasyim commented 4 years ago

Hi @martinjrobins, thanks for the reply!

The HPX project is very interesting. This is the first time I've heard about it actually and I'm very impressed with what they have. The only other project that may serve our MPI parallelization purpose is DASH (https://github.com/dash-project/dash) which I discovered a few months ago through this paper (https://arxiv.org/pdf/1610.01482.pdf). On the surface, DASH is smaller in scope but perhaps it'll fit our purpose better(?). Anyways, if either library has some vector type with all the algorithms needed, then I'm perfectly fine with using either of them to implement the MPI distributed vector.

I'll stick with what I have for now. I am planning to start up a new project for some Monte Carlo simulations so perhaps I'll think about this topic again when I get there.