The foreach, iterators and doMC packages
And you can get much better results using sqrt directly on the vector, as it is intended to be called. The sqrt function is so fast that it's crazy to call it in parallel the way my vignette shows. The overhead kills you. But I have this bad habit of using sqrt in my parallel programming examples. I actually put a footnote in the vignette saying you should never do what I just did, but I can see now that I wasn't nearly explicit enough. I should probably include a big disclaimer saying not to try this at home. I'm pretty sure that the next version of foreach will issue warnings if the tasks execute in less than a second. But I'll definitely fix the vignette. Sorry about that. - Steve
On Wed, Jul 15, 2009 at 12:54 PM, Mark Kimpel<mwkimpel at gmail.com> wrote:
I'm having trouble getting these packages to work as I believe they should. I have a new Debian Lenny box running on an Intel i7 with 12 GB of memory and wrote a test script to see how much performance increase I could achieve with foreach. For this purpose, I used code extracted from the vignette. Below is the code, the system.time output, and sessionInfo(). I should add that I've run this multiple times and always achieved similar results. These last were achieved after doing init 1 to get me into a strict terminal mode and avoid the GUI. As you can see, the results seem to be the opposite of what one would expect. The fastest time, by an order of magnitude, is achieved by a simple for loop, and %do% slightly outperforms %dopar% How can this be explained? Mark #################################### require(foreach) require(multicore) require(doMC) registerDoMC(cores=5) z <- 30000 for.each.do.time <- system.time( ? ? ? ? ? ?a <- foreach(i = 1:z, .combine = "c") %do% sqrt(i) ? ? ? ? ? ?) # for.each.do.par.time <- system.time( ? ? ? ? ? ?b <- foreach(i = 1:z, .combine = "c") %dopar% sqrt(i) ? ? ? ? ? ?) # c <- rep(0,z) loop.time <- system.time( ? ? ? ? ? ?for (i in 1:length(c)) ? ? ? ? ? ?c[i] <- sqrt(i) ? ? ? ? ? ?) # out <- rbind(unclass(for.each.do.time), unclass(for.each.do.par.time), unclass(loop.time)) out "user.self" ? ? "sys.self" ? ? ?"elapsed" ? ? ? "user.child" ? ?"sys.child" 25.713 ?0 ? ? ? 25.712 ?0 ? ? ? 0 25.918 ?0.016 ? 26.015 ?0.192 ? 0.192 0.207999999999998 ? ? ? 0 ? ? ? 0.206000000000003 ? ? ? 0 ? ? ? 0 # "R.version.platform" "x86_64-unknown-linux-gnu" "R.version.arch" "x86_64" "R.version.os" "linux-gnu" "R.version.system" "x86_64, linux-gnu" "R.version.status" "" "R.version.major" "2" "R.version.minor" "9.1" "R.version.year" "2009" "R.version.month" "06" "R.version.day" "26" "R.version.svn rev" "48839" "R.version.language" "R" "R.version.version.string" "R version 2.9.1 (2009-06-26)" "locale" "LC_CTYPE=en_US.UTF-8;LC_NUMERIC=C;LC_TIME=en_US.UTF-8;LC_COLLATE=en_US.UTF-8;LC_MONETARY=C;LC_MESSAGES=en_US.UTF-8;LC_PAPER=en_US.UTF-8;LC_NAME=C;LC_ADDRESS=C;LC_TELEPHONE=C;LC_MEASUREMENT=en_US.UTF-8;LC_IDENTIFICATION=C" "basePkgs1" "stats" "basePkgs2" "graphics" "basePkgs3" "grDevices" "basePkgs4" "datasets" "basePkgs5" "utils" "basePkgs6" "methods" "basePkgs7" "base" ------------------------------------------------------------ Mark W. Kimpel MD ?** Neuroinformatics ** Dept. of Psychiatry Indiana University School of Medicine 15032 Hunter Court, Westfield, IN ?46074 (317) 490-5129 Work, & Mobile & VoiceMail "The real problem is not whether machines think but whether men do." -- B. F. Skinner ****************************************************************** On Wed, Jul 1, 2009 at 10:56 PM, Steve Weston<steve at revolution-computing.com> wrote:
There have been several announcements of three new packages that I've recently uploaded to CRAN: foreach, iterators, and doMC. ?You can read one description on David Smith's blog, at: ? ?http://blog.revolution-computing.com or: ? ?http://bit.ly/tygLz You can also read the vignette that I wrote for foreach on a CRAN website. I would like to mention that one of the goals of the foreach package is to make it easy to write an R package that allows the end user to choose what parallel computing engine to use. ?That's useful because the user may already have and use a parallel computing system, and not want to install and maintain yet another one. ?(The foreach and iterators packages themselves are trivial to install, since they provide a framework for using parallel computing systems such as multicore and nws.) Currently, only the doMC "parallel backend" for multicore is publicly available on CRAN, but I'm hoping to get a chance to write and release other backend packages, to support MPI and shared memory, for example. I'd love to hear from R package authors on how to improve foreach so that it's a more attractive platform on which to develop parallel applications. ?Especially if you've had difficulty using parallel computing systems in the past. -- Steve Weston REvolution Computing One Century Tower | 265 Church Street, Suite 1006 New Haven, CT ?06510 P: 203-777-7442 x266 | www.revolution-computing.com
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Steve Weston REvolution Computing One Century Tower | 265 Church Street, Suite 1006 New Haven, CT 06510 P: 203-777-7442 x266 | www.revolution-computing.com