Look at the nws package, I have had success using it to parallelize simulations using a couple of computers that were not being used at the time. I don't have a multicore machine, but the examples in the package make it look like using it for multicore would be even easier.
This is on windows 2000 machines with cygwin installed. 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 Millo Giovanni Sent: Friday, December 01, 2006 5:24 AM To: r-help@stat.math.ethz.ch Subject: [R] simple parallel computing on single multicore machine Dear List, the advent of multicore machines in the consumer segment makes me wonder whether it would, at least in principle, be possible to divide a computational task into more slave R processes running on the different cores of the same processor, more or less in the way package SNOW would do on a cluster. I am thinking of simple 'embarassingly parallel' problems, just like inverting 1000 matrices, estimating 1000 models or the like. I have seen some talk here on making R multi-threaded and the like, but this is much simpler. I am just a curious useR, so don't bother if you don't have time, but maybe you can point me at some resource, or just say "this is nonsense"... Cheers Giovanni Giovanni Millo Research Dept., Assicurazioni Generali SpA Via Machiavelli 4, 34131 Trieste (Italy) tel. +39 040 671184 fax +39 040 671160 Ai sensi del D.Lgs. 196/2003 si precisa che le informazioni ...{{dropped}} ______________________________________________ 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.
