The nws package does run on windows and can split calculations between multiple R processes. I have not tried it with a single multiprocessor pc (don't have one), but have used it with multiple pc's. It looks like the muliprocessor pc would work pretty much with the defaults.
Hope this helps, -- Gregory (Greg) L. Snow Ph.D. Statistical Data Center Intermountain Healthcare [EMAIL PROTECTED] (801) 408-8111 > -----Original Message----- > From: [EMAIL PROTECTED] > [mailto:[EMAIL PROTECTED] On Behalf Of > [EMAIL PROTECTED] > Sent: Tuesday, March 06, 2007 8:33 AM > To: r-help@stat.math.ethz.ch > Subject: [R] How to utilise dual cores and multi-processors on WinXP > > Hello, > > I have a question that I was wondering if anyone had a fairly > straightforward answer to: what is the quickest and easiest > way to take advantage of the extra cores / processors that > are now commonplace on modern machines? And how do I do that > in Windows? > > I realise that this is a complex question that is not > answered easily, so let me refine it some more. The type of > scripts that I'm dealing with are well suited to > parallelisation - often they involve mapping out parameter > space by changing a single parameter and then re-running the > simulation 10 (or n times), and then brining all the results > back to gether at the end for analysis. If I can distribute > the runs over all the processors available in my machine, I'm > going to roughly halve the run speed. The question is, how to do this? > > I've looked at many of the packages in this area: rmpi, snow, > snowFT, rpvm, and taskPR - these all seem to have the > functionality that I want, but don't exist for windows. The > best solution is to switch to Linux, but unfortunately that's > not an option. > > Another option is to divide the task in half from the > beginning, spawn two "slave" instances of R (e.g. via Rcmd), > let them run, and then collate the results at the end. But > how exactly to do this and how to know when they're done? > > Can anyone recommend a nice solution? I'm sure that I'm not > the only one who'd love to double their computational speed... > > Cheers, > > Mark > > ______________________________________________ > R-help@stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.