Of course, you would know best, so can you tell us if the help pages I pull using
help(Memory) is wrong? That help page says (2nd paragraph) "(On Windows the --max-mem-size option sets the maximum memory allocation: it has a minimum allowed value of 16M. This is intended to catch attempts to allocate excessive amounts of memory which may cause other processes to run out of resources. The default is the smaller of the amount of physical RAM in the machine and 1024Mb. See also memory.limit.) " Hugues -----Original Message----- From: Prof Brian Ripley [mailto:[EMAIL PROTECTED] Sent: Friday, February 02, 2007 3:05 AM To: Sicotte, Hugues Ph.D. Cc: Tristan Coram; R-help@stat.math.ethz.ch Subject: Re: [R] Affymetrix data analysis On Thu, 1 Feb 2007, Sicotte, Hugues Ph.D. wrote: > Tristan, > I have a soft spot for problems analyzing microarrays with R.. > > for the memory issue, there have been previous posts to this list.. > But here is the answer I gave a few weeks ago. > If you need more memory, you have to move to linux or recompile R for > windows yourself.. > .. But you'll still need a computer with more memory. > The long term solution, which we are implementing, is to rewrite the > normalization code so it doesn't > Need to load all those arrays at once. > > -- cut previous part of message-- > The defaults in R is to play nice and limit your allocation to half > the available RAM. Make sure you have a lot of disk swap space (at least > 1G with 2G of RAM) and you can set your memory limit to 2G for R. That just isn't true (R uses as much of the RAM as is reasonable, all for up to 1.5Gb installed). Please consult the rw-FAQ for the whole truth. > See help(memory.size) and use the memory.limit function [Please follow the advice you quote.] > Hugues > > > P.s. Someone let me use their 16Gig of RAM linux > And I was able to run R-64 bits with "top" showing 6Gigs of RAM > allocated (with suitable --max-mem-size command line parameters at > startup for R). There is no such 'command' for R under Linux. -- Brian D. Ripley, [EMAIL PROTECTED] Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UK Fax: +44 1865 272595 ______________________________________________ R-help@stat.math.ethz.ch 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.
