Why is this simple parallel program much slower than the non-parallel version?

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Andy Yancy
Andy Yancy 2014-2-4
评论： Andy Yancy 2014-2-6
I have a very simple script that calls the built-in genetic algorithm function:
function test1(gen)
options = gaoptimset('UseParallel', 'always', 'Vectorized', 'off');
tic;
x = ga(@dejong5fcn, 2, [], [], [], [], [], [], [], options);
toc
end
First, I ran test1 without starting matlabpool. As expected, it runs fine but uses only one CPU core as observed with Windows Resource Monitor. It takes 4.2 seconds to run 20020 fitness evaluations. Then, I started the parallel engine with: "start matlabpool local 4" and then performed an otherwise identical run of test1. It runs and uses all four CPU cores, but takes about 90.7 seconds to perform 20020 fitness evaluations.
What am I not understanding about parallelism in Matlab R2012a (on Windows 7 64 bit)? Thanks for any help.

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Walter Roberson
Walter Roberson 2014-2-4
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Walter Roberson
Walter Roberson 2014-2-6
Pr-allocation. When you use parfor(), MATLAB automatically pre-allocates for the outputs. If you have not pre-allocated in your code, the serial version could spend most of its time finding new memory and copying the results into it.

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