Hello dear R-help group (and David Smith from REvolution), I would like to perform parallel computing using R with Condor (hopefully using foreach or other recommended solutions, if available) for some "Embarrassingly parallel" problem. I will start by listing what I found so far, and then go on asking for help.
So far I found the a manual by Xianhong Xie from Rnews_2005-2 (see page 13) Talking about R and condor: http://cran.r-project.org/doc/Rnews/Rnews_2005-2.pdf I also found several references for R and condor in the task views of High Performance Computing<http://cran.r-project.org/web/views/HighPerformanceComputing.html> : http://cran.r-project.org/web/views/HighPerformanceComputing.html Stating that: "The GridR<http://cran.r-project.org/web/packages/GridR/index.html> package by Wegener et al. can be used in a grid computing environment via a web service, via ssh or via Condor or Globus." I then found a 2008 lecture slides on the subject here: http://www.statistik.uni-dortmund.de/useR-2008/tutorials/GridR.pdf And an articles showing it was already done: http://www.ecmlpkdd2008.org/files/pdf/workshops/ubiqkd/3.pdf (But without code examples to my dismay) What I wish from you is some guidance. Is there a more updated (formal) material on condor and R then Xianhong Xie article from 2005? Is GridR a good way of making the connection? Is using the foreach package relevant or useful here? I am not a UNIX person. I never ran R in "batch", and any "step by step" instructions (either by referring to links or explaining here) would be of great help. Thanks in advance, Tal ---------------------------------------------- My contact information: Tal Galili Phone number: 972-50-3373767 FaceBook: Tal Galili My Blogs: http://www.r-statistics.com/ http://www.talgalili.com http://www.biostatistics.co.il [[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.
