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Parallel programming: defining tasks

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Daniel Jaló
Daniel Jaló on 10 Feb 2013
Hi.
I made a simple function, compute(m,n), that calculates the number of primes between m and n. I used this function to test the performance improvement when using parfor and spmd against a simple for cycle. I used the following cycle to test it:
A = [3 480000 830000 1100000];
NumPrimes = 0;
t = tic;
for n = 1:3
NumPrimes = NumPrimes + compute(A(n),A(n+1));
end
toc(t)
As expected using parfor, or rewriting the cycle with spmd, gave me better results than with the serial for cycle.
Now comes the problem. I tried to run a job, defining each task such that each worker would take care of a different subset of numbers. Lab 1 would compute the number of primes from 3 to 480000, Lab 2 from 480000 to 830000, etc... To do it I wrote the following code:
job = createJob('configuration','local','FileDependencies',{'compute.m'});
A = [3 480000 830000 1100000];
NumPrimes = 0;
t = tic;
for n=1:3
createTask(job,@compute,1,{A(n),A(n+1)})
end
submit(job)
wait(job)
out = getAllOutputArguments(job);
NumPrimes = sum([out{:}]);
toc(t)
When I run this code there are 2 possible outcomes: If I have 3 labs (matlabpool open 3) the code will run but it will take about 3x the time it takes with a serial code. If I have 4 labs it will run forever, until I eventually cancel it.
My doubts are: - Why isn't my code speeding up in relation to the serial version? - When I use the function createTask can't I decide which Lab takes care of the task or is it assigned by order? - Can I have more tasks than workers? If so how will they take care of the tasks? Each lab will take care of one of the first 4 tasks, and when they complete them move on to the next uncomplete task?
If anyone could clear my mind I'd really appreciate. Thanks!

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Answers (1)

Thomas Ibbotson
Thomas Ibbotson on 11 Feb 2013
Hi Daniel,
Thanks, Tom

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