Hello,
Does openMM simulations can be run on multiple nodes in computing cluster? I mean, on multiple nodes with multiple cores. With openMPI or something like that.
Massive parallelization
- Peter Eastman
- Posts: 2564
- Joined: Thu Aug 09, 2007 1:25 pm
Re: Massive parallelization
A single simulation can only be run on a single node. Of course, there are other ways of taking advantage of multiple nodes that are often more efficient. For example, you could do replica exchange (a different replica on each node), or run many independent simulations to get better sampling.
Peter
Peter
- George Pantelopulos
- Posts: 64
- Joined: Mon Jun 01, 2015 2:15 pm
Re: Massive parallelization
This is something I am also curious about - running one replica per node would be fine for some replica exchange ideas I've been playing with recently. How would someone go about running REMD over many nodes with OpenMM? How would the implementation have to be built?
Thanks you for any info,
George
Thanks you for any info,
George
- Peter Eastman
- Posts: 2564
- Joined: Thu Aug 09, 2007 1:25 pm
- George Pantelopulos
- Posts: 64
- Joined: Mon Jun 01, 2015 2:15 pm
Re: Massive parallelization
Yes, I know of John Chodera's repex and yank - I mean if I were to want to do this myself. How would someone set different replicas to run on specific nodes?
- Jason Swails
- Posts: 47
- Joined: Mon Jan 07, 2013 5:11 pm
Re: Massive parallelization
I would use MPI, personally. But that's precisely what John Chodera's library does.
So I guess the best answer I can think of is to do what repex does. Which is to say, just use repex (or implement the same thing in C++ if you want to do that and can reproduce the rest of the required machinery from the app layer in C++). The code is free to look at, use, modify, and reuse.
So I guess the best answer I can think of is to do what repex does. Which is to say, just use repex (or implement the same thing in C++ if you want to do that and can reproduce the rest of the required machinery from the app layer in C++). The code is free to look at, use, modify, and reuse.
- George Pantelopulos
- Posts: 64
- Joined: Mon Jun 01, 2015 2:15 pm
Re: Massive parallelization
Ah, OK, I will just go scour his code, then. Thanks for the advice.