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Re: Sharing big data across parfor or spmd
Posted:
Dec 11, 2012 1:41 PM
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"Chuck37 " <chuck3737@yahooremovethis.com> wrote in message
news:ka7ss4$4f6$1@newscl01ah.mathworks.com...
> I have a big piece of never changing data that I'd like to be used by all
> the workers in a parallel setting. Since I'm only working with local
> workers, I don't understand why I have to eat the huge latency associated
> with transferring the data to workers each time the parfor loop is called.
> Can someone explain?
>
> I tried to use spmd to send data once at the beginning and have it stay
> there, but the data is kind of big (~2 GB going to 10 workers), and I got
> "error during serialization" anyway. Is there a solution to this problem
> with local workers where they can all access the data from the same
> memory? Accesses are infrequent, so simultaneous access shouldn't cause a
> big slowdown.
>
> Any ideas would be great.
>
> My setup is something like this by the way:
>
> M = big data;
> for x = 1:m
> stuff
> parfor y = 1:n
> a(y) = function(M,a(y));
> end
> stuff
> end
>
> Parfor is presently worse than 'for' because of the overhead from sending
> M every time.
Can you use PARFOR for the loop over x instead of the loop over y?
--
Steve Lord
slord@mathworks.com
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