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. > > >
