Parallelizing Independent Tasks Help

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 Commenti

We probably need to see the code for reactions() to get an idea of why there is a problem.
function [F,A,S] = reactions(in,isotope,p)
% separate by activity of choice
if isempty(in); F = []; A = []; S = []; return; end
N = size(in,1);
switch isotope
case 1 % hydrogen no fission
absorbed = rand(N,1) <= p(in(:,1),2);
F = [];
try
A = in(absorbed,:);
catch ME
if strcmp(ME.identifier,'MATLAB:badsubscript')
A = [];
else
throw(ME);
end
end
try
S = in(~absorbed,:);
catch ME
if strcmp(ME.identifier,'MATLAB:badsubscript')
S = [];
else
throw(ME);
end
end
case 16 % oxygen no fission
[F,A,S] = reactions(in,1,p);
case 235 % U235 - fission likely!
fissioned = rand(N,1) <= p(in(:,1),1);
try
F = in(fissioned,:);
catch ME
if strcmp(ME.identifier,'MATLAB:badsubscript')
F = [];
else
throw(ME);
end
end
try
p = p(:,2:3)./sum(p(:,2:3),2);
N = size(in(~fissioned),1);
in = in(~fissioned,:);
absorbed = rand(N,1) <= p(in(:,1),1);
catch ME
if strcmp(ME.identifier,'MATLAB:badsubscript')
A = []; S = []; return;
else
throw(ME);
end
end
try
A = in(absorbed,:);
catch ME
if strcmp(ME.identifier,'MATLAB:badsubscript')
A = [];
else
throw(ME);
end
end
try
S = in(~absorbed,:);
catch ME
if strcmp(ME.identifier,'MATLAB:badsubscript')
S = [];
else
throw(ME)
end
end
case 238
[F,A,S] = reactions(in,235,p);
otherwise
msgID = 'reactions:WrongType';
msg = 'enter the isotope number for one of the r. components';
ex = MException(msgID,msg);
throw(ex);
end
% r = {F,A,S};
end
Could you describe further what you mean by "it behaves strangely with indexing order" ?
Sure. I've tried putting the inputs and outputs in two separate cell arrays, and run essentially
parfor i=1:4
output(i,1:3) = reaction(input(i,1:4));
end
but MATLAB marks that as an error (valid indices are restricted in parfor loops).
parfor i=1:4
temp = reaction(input(i,1:4));
output(i,1:3) = temp;
end
That gives me a
The variable output in a parfor cannot be classified
error.
Greg
Greg il 25 Gen 2018
Modificato: Greg il 25 Gen 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.
You're right on all counts, Greg. The code works, too. Thanks for your answer - please post it so I can accept. Thank you Walter, too.
I ran the speed test on the data, and it seems the old method is about 4 times faster than the parfor loop, so I'll probably stick to that. But thanks for the help.
Greg
Greg il 25 Gen 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.

Accedi per commentare.

 Risposta accettata

Greg
Greg il 25 Gen 2018
Per the comments, 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

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