Thank you, Mario. On Wed, Jun 16, 2010 at 14:51, Mario Valle <mva...@cscs.ch> wrote: > > > On 15-Jun-10 17:07, Sergey Goriatchev wrote: >> >> Hello, >> >> I am reading "Using The foreach Package" document and I have tried the >> following: >> >> --------------------------------------------------------------------- >> >>> sessionInfo() >> >> R version 2.10.1 (2009-12-14) >> i386-pc-mingw32 >> >> locale: >> [1] LC_COLLATE=German_Switzerland.1252 >> LC_CTYPE=German_Switzerland.1252 >> LC_MONETARY=German_Switzerland.1252 LC_NUMERIC=C >> LC_TIME=German_Switzerland.1252 >> >> attached base packages: >> [1] stats graphics grDevices utils datasets methods base >> >> other attached packages: >> [1] foreach_1.3.0 codetools_0.2-2 iterators_1.0.3 >> >> >>> x<- numeric(10000) >>> system.time(for(i in 1:10000) x[i]<- sqrt(i)) >> >> user system elapsed >> 0.03 0.00 0.03 >>> >>> system.time(system.time(x<- foreach(i=1:10000, .combine="c") %do% >>> sqrt(i))) >> >> user system elapsed >> 7.14 0.00 7.14 >>> >>> system.time(system.time(x<- foreach(i=1:10000, .combine="c") %dopar% >>> sqrt(i))) >> >> user system elapsed >> 7.19 0.00 7.19 >> Warning message: >> executing %dopar% sequentially: no parallel backend registered >> >> ------------------------------------------------------------------------ >> >> Not only is the sequential foreach much slower than the simple >> for-loop (as least in this particular instance), but I am not quite >> sure how to make foreach run parallel. Where would I get this parallel >> backend? > > Use doMPI and run R through mpirun (for example run on 8 cores): > > mpirun -np 8 R --slave -f your-script.r > > Hope it helps > mario > > > > I looked at doMC and doRedis, but these do not run on >> >> Windows, as far as I understand. And doSNOW is something to use when >> you have a cluster, while I have a simple dual-core PC. >> >> It is not really clear for how to make parallel computing work. Please, >> help. >> >> Regards, >> Sergey >> >> ______________________________________________ >> R-help@r-project.org 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. > > -- > Ing. Mario Valle > Data Analysis and Visualization Group | > http://www.cscs.ch/~mvalle > Swiss National Supercomputing Centre (CSCS) | Tel: +41 (91) 610.82.60 > v. Cantonale Galleria 2, 6928 Manno, Switzerland | Fax: +41 (91) 610.82.82 >
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