Parallelizing Independent Tasks Help
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Hi,
I have a model that I'm trying to parallelize. In this section, I run the same function four times on four independent sets, each time the function outputs three tables of reaction probabilities. I struggled using parfor to parallelize because it behaves strangely with indexing order and I don't understand it. Can anyone chime in with advice about how they would parallelize this task?
[HF,HA,HS] = reactions(H,1,Hprobs);
[OF,OA,OS] = reactions(O,16,Oprobs);
[U25F,U25A,U25S] = reactions(U25,235,U25probs);
[U28F,U28A,U28S] = reactions(U28,238,U28probs);
Thank you!
9 Comments
Walter Roberson
on 24 Jan 2018
We probably need to see the code for reactions() to get an idea of why there is a problem.
Nimrod Sadeh
on 24 Jan 2018
Walter Roberson
on 24 Jan 2018
Could you describe further what you mean by "it behaves strangely with indexing order" ?
Nimrod Sadeh
on 25 Jan 2018
Walter Roberson
on 25 Jan 2018
parfor i=1:4
temp = reaction(input(i,1:4));
output(i,1:3) = temp;
end
Nimrod Sadeh
on 25 Jan 2018
You've both missed the 's' in the function name reactions, but I'm assuming that's a typo in-comment only.
I think you're having curly-brace vs. parenthesis problems, and 1:3 in input, not 1:4:
input = { H, 1, Hprobs; ...
O, 16, Oprobs; ...
U25,235,U25probs; ...
U28,238,U28probs};
parfor i=1:4
[F{i},A{i},S{i}] = reactions(input{i,1:3});
end
If this works, I'll move it to an Answer for acceptance.
Nimrod Sadeh
on 25 Jan 2018
Greg
on 25 Jan 2018
If you're looking for general performance improvement (rather than specifically multi-threading), run the profiler. It will identify individual lines of code that are taking especially long to execute. You can then post a new (related) question, identifying those lines and we can try to help optimize.
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