Robust SPMD-like structure
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I'm interested in running some subroutine on different sets of data in parallel. Sometimes, a dataset will cause errors in the subroutine, but most of the time it does not. Is there a way to salvage the valid results from all of the datasets without errors? SPMD documentation says that it will stop all workers upon encountering an error in one.
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Walter Roberson
on 7 Jan 2016
Put in your own try/catch
You might also want to look at parfeval()
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