You need to use addprocs before the first @everywhere. I assume you actually did this, since otherwise you'd have received an error.
It seems that your variable A and v are stored on the master, not on the workers. Since they are inputs to do_stuff, they need to be copied there every time. Note that the whole array v is copied although only part of it is accessed. Maybe sending data to 4 processes simultaneously has an overhead, and is somehow much slower than sending the data one at a time. To check whether this is true, you can add a loop within do_stuff to execute the routine multiple times. This would increase the workload, but keep the communication overhead the same. If this is the case, then to remedy this, you would store A and v (better: only the necessary part of v) on all processes instead of copying them. -erik On Thu, Nov 27, 2014 at 10:20 AM, <[email protected]> wrote: > Hey everyone, > > I've been looking at parallel programming in julia and was getting some very > unexpected results and rather bad performance because of this. > Sadly I ran out of ideas of what could be going on, disproving all ideas I > had. Hence this post :) > > I was able to construct a similar (simpler) example which exhibits the same > behavior (attached file). > The example is a very naive and suboptimal implementation in many ways (the > actual code is much more optimal), but that's not the issue. > > The issue I'm trying to investigate is the big difference in worker time > when a single worker is active and when multiple are active. > > Ideas I disproved: > - julia processes pinned to a single core > - julia process uses multiple threads to do the work, and processes are > fighting for the cores > - not enough cores on the machine (there are plenty) > - htop nicely shows 4 julia processes working on different cores > - there is no communication at the application level stalling anyone > > All I'm left with now is that julia is doing some hidden synchronization > somewhere. > Any input is appreciated. Thanks in advance. > > Kind regards, > Tom -- Erik Schnetter <[email protected]> http://www.perimeterinstitute.ca/personal/eschnetter/
