I think you are looking for shared arrays?
http://docs.julialang.org/en/latest/manual/parallel-computing/#id2
On Tuesday, December 1, 2015 at 2:55:59 PM UTC-5, Pieterjan Robbe wrote:
>
> does the @everywhere macro allocate extra memory to make local copies of a
> matrix for every processor?
>
No, not really. SharedArrays do only support bitstypes. I have an application
where the function to be executed in parallel depends on some fixed data (some
constants, a dict, some arrays, etc.) I would like to replace my @parallel for
loop by @everywhere (because of the reuse of my cholesky
