why does (ga + parallel + global variables + sub2ind) fail?

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When optimizing with ga and parallel computing, a sub2ind call using globals fails (subscript vectors must be of same size), but when doing it in serial, it doesn't fail. Why?

Accepted Answer

Matt J
Matt J on 9 Sep 2016
Probably because of the dangers of using global variables.
Walter Roberson
Walter Roberson on 11 Sep 2016
Note that the above discussion is only for serial computing. The considerations are a bit different for parallel computing, where each worker must have a copy of the data because they are different processes.
Matt J
Matt J on 11 Sep 2016
Edited: Matt J on 11 Sep 2016
The discussion still applies to parallel computing if we're not talking about the one-time cost of broadcasting constant data to the workers. The OP seems to think that arguments passed to the fitness function will be copied "again and again" each time the fitness function is called. That is not true, even on parallel workers

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More Answers (2)

Walter Roberson
Walter Roberson on 10 Sep 2016
Global variables are never copied to parallel workers.
You might be able to take advantage of parallel.pool.Constant or of parfevalOnAll() to initialize the variable on all of the workers.
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Walter Roberson
Walter Roberson on 11 Sep 2016
If you have especially large shared data, you could also use the File Exchange contribution https://www.mathworks.com/matlabcentral/fileexchange/28572-sharedmatrix to use shared memory. This will only work if the compute nodes are on the same host, though

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Jochen Schuettler
Jochen Schuettler on 12 Sep 2016
Thanks to everyone!


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