You're probably being killed by the overhead of parallelization which is, in this case, far more than actual computation time. I've not dug through foreach() in a while, but I think this winds up spawning many many subprocesses which isn't cheap in Windows.
MW On Mon, Jan 21, 2013 at 3:59 PM, Andre Zege <az...@yahoo.com> wrote: > I started to look at ways to improve times of certain very parallel tasks and > thought that foreach should be a valid candidate to do the job. > So, i opened foreach tutorial by Steve Weston and started timing examples > from it. First example from tutorial is > > >>system.time(for(i in 1:100000) sqrt(i)) > > user system elapsed > 0.06 0.00 0.06 >> system.time(foreach(i=1:100000) %do% sqrt(i)) > user system elapsed > 102.37 0.21 103.38 > > Hmm, 1700 time slower? > > second example is >> system.time(x <- exp(1:1000000)) > user system elapsed > 0.34 0.03 0.42 >>system.time(x <- foreach(i=1:1000000, .combine='c') %do% exp(i)) > > > I stopped it at 958 seconds, didn't have enough patience -- it basically > seems that foreach slows down this one down naive by more than 2000 times. > I must be doing something very wrong. Am i supposed to set some environment > variables before it works properly? I am running 64bit R on win7 dual core > 2.27GHZ CPUs and 4GB memory laptop. > [[alternative HTML version deleted]] > > > ______________________________________________ > 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. > ______________________________________________ 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.
