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? 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.
