I'm finding myself in need of similar functionality lately. Has any progress been made on this front? In my case, since the large object b needs to be computed at run-time, I would prefer to simultaneously compute it on all workers at the beginning, then have these copies stick around for later reuse. In the Matlab version of the code I'm porting to Julia, I do this with persistent variables.
Thanks, --Peter On Thursday, December 13, 2012 2:04:12 AM UTC-8, Viral Shah wrote: > > Need to wrap up remote_call / remote_call_fetch in a few higher level > functions for such things. I'm going to get cracking on improving our > parallel support soon. > > -viral > > On Thursday, December 13, 2012 12:29:58 PM UTC+5:30, Miles Lubin wrote: >> >> Seemingly simple question that I haven't managed to figure out after >> reading the documentation and playing around: How can you broadcast an >> object from one process (say the main process) to all running processes? I >> come from an MPI background where this is a fundamental operation. >> >> To give an example, say I have a function f(a,b), where b is some large >> 100MB+ dataset/matrix/object, and I want to compute f(a,b) for a in some >> range and b fixed. It doesn't make sense to send a new copy of b with each >> call. Instead I'd like to broadcast b to each process and keep a persistent >> copy in each process to use during the pmap. What's the best and prettiest >> way to do this? >> >> Thanks, >> Miles >> >
