https://github.com/amitmurthy/MessageUtils.jl could be useful for your own task distribution.
On Wed, Jun 4, 2014 at 9:39 PM, Kevin Squire <[email protected]> wrote: > It is the case currently that the array itself is divided up evenly. One > way to deal with this (in the back end) is work stealing, but that hasn't > been implemented in Julia yet. > > Cheers, > Kevin > > > On Wednesday, June 4, 2014, Jutho <[email protected]> wrote: > >> I probably already have an idea what's going on. How are the different >> tasks distributed over the different Julia processes? Is the for loop >> immediately cut into pieces where e.g. process 1 will handle the cases >> iter=1:10, process 2 handles the cases iter=11:20 and so on? For different >> values of the parameters, the execution time will be widely different (from >> fraction of a second to several minutes or even more). If some processes >> handle all the slow cases and other all the fast cases, then this explains >> the behaviour I am seeing. I guess I need to write my own task >> distribution, for which I will have to read the Manual section on parallel >> computing again. >> >> >>
