rng shuffle in parallel computing
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Hello everyone,
I am running a code on our parallel computing cluster which depends on some subfunction (select.m) and includes a for loop with 20 iterations, where select is called in every iteration. Select depends on a random number. I don`t want to use the same random number in every iteration and have therefore included rng('shuffle') on top of select.m. I have also saved the random numbers generated. If I include rng ('shuffle') I get different numbers (exactly what I want), if I don`t I only get two different "random" numbers. The Matlab help however says: When parallel processing, rng('shuffle') should not be used to set the random number stream on different workers to ensure independent streams since it seeds the random number generator based on the current time.
Honestly, I don`t quite understand what`s the problem with that. Secondly. I also ran every iteration in a real parallel way (calling the script 20 times). However, when I only use the default settings, I get the same "random" number here everytime.
My questions would be: What`s the problem with rng ('shuffle') in my first and second approach and what else could I do to get random numbers in both scenarios?
Best,
Laurie
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