This is a very open ended question that depends very heavily on what you are trying to do and how you are doing it. Often times, the bottleneck operations that limit speed the most are not necessarily sped up by adding RAM. They also often require special setup to run multiple operations/iterations in parallel. Try some of the options at the High Performance Computing task view for specifics.
http://cran.cnr.berkeley.edu/web/views/ HTH, Jon On Fri, May 27, 2011 at 2:00 PM, Debs Majumdar <debs_st...@yahoo.com> wrote: > Hello, > > Are there some basic things one can do to speed up a R code? I am new to R > and currently going through the following situation. > > I have run a R code on two different machines. I have R 2.12 installed on > both. > > Desktop 1 is slightly older and has a dual core processor with 4gigs of > RAM. Desktop 2 is newer one and has a xeon processor W3505 with 12gigs of > RAM. Both run on Windows 7. > > I don't really see any significant speed up in the newer computer (Desktop > 2). In the older one the program took around 5hrs 15 mins and in the newer > one it took almost 4hrs 30mins. > > In the newer dekstop, R gives me the following: > >> memory.limit() > [1] 1024 >> memory.size() > [1] 20.03 > > Is something hampering me here? Do I need to increase the limit and size? > Can this change be made permanent? Or am I looking at the wrong place? > > I have never seen my R programs using much CPU or RAM when it runs? If this > is not something inherent to R, then I guess I need to write more effiecient > codes. > > Suggestions/solutions are welcome. > > Thanks, > > -Debs > > > ______________________________________________ > 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. > -- =============================================== Jon Daily Technician =============================================== #!/usr/bin/env outside # It's great, trust me. ______________________________________________ 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.
