On Oct 25, 2012, at 7:42 PM, Ray DiGiacomo, Jr. wrote: > Hello Melanie, > > How much RAM is installed on your MacBook Pro compared to your colleague's > Linux machine? > > How big is your dataset in terms of rows and columns? > > I believe R can handle about 10M datapoints per GB of RAM. >
What exactly is that an estimate of? In R, 1GB of RAM will store ~134Mio datapoints when using numeric matrices/vectors and twice as many as integers or logicals. In practice, you will still need some room for computation on the data, though. Cheers, Simon > Note that datapoints = rows x columns > > Best Regards, > > Ray DiGiacomo, Jr. > Master R Trainer > President, Lion Data Systems LLC > President, The Orange County R User Group > Board Member, TDWI > [email protected] > (Mobile) 408-425-7851 > San Juan Capistrano, California > > Check out my one-on-one web-based R courses at liondatasystems.com/courses > > > > > > On Thu, Oct 25, 2012 at 4:16 PM, Melanie Courtot <[email protected]> wrote: > >> Hi, >> >> I am trying to run R on my MacBook Pro 2.4 GHz Intel core i5. I am trying >> to read a csv file, which works fine on my work colleague's machine (under >> linux) but causes my CPU to go up to 100% and makes the GUI unresponsive >> and hangs on the command line. Activity monitor indicates there is only one >> R thread running. >> >> I did see that by default R was using the BLAS library, which is >> single-threaded, and that there was an option to use vecLib instead. I did >> this, and >> ls -l /Library/Frameworks/R.framework/Resources/lib/libRblas.dylib >> does return >> /Library/Frameworks/R.framework/Resources/lib/libRblas.dylib -> >> libRblas.vecLib.dylib >> >> I however still see the same behavior: 100% CPU, single thread. >> >> I saw that some MacBook pro (Xeon Nehalem based) had a vecLib bug, so I >> built the ATLAS library and symlinked R to libtatlas.dylib (unfortunately >> the pre compiled binairies pointed to in a previous email on the list [1] >> were not available anymore. Building ATLAS was... fun ;)) I was able to get >> the shared libraries (using --shared in my config) but still see the same >> behavior when trying to run my code. I was unsure if I should link to >> libsatlas.dylib or libtatlas.dylib, so tried both (I guess the latter was >> the right one though) >> >> I tried building R from the source (specifying -arch x86_64 and >> --enable-BLAS-shlib to be able to switch libraries), but same behavior and >> it seems it is an identical version to the prepackaged one (I tried with >> BLAS, vecLib and ATLAS) >> >> R info: R version 2.15.1 (2012-06-22) -- "Roasted Marshmallows", Platform: >> x86_64-apple-darwin9.8.0/x86_64 (64-bit) >> >> Any help would be greatly appreciated. >> >> Thanks, >> Melanie >> >> >> [1] https://stat.ethz.ch/pipermail/r-sig-mac/2010-October/007817.html >> >> --- >> Mélanie Courtot >> MSFHR/PCIRN Ph.D. Candidate, >> BCCRC - Terry Fox Laboratory - 12th floor >> 675 West 10th Avenue >> Vancouver, BC >> V5Z 1L3, Canada >> >> _______________________________________________ >> R-SIG-Mac mailing list >> [email protected] >> https://stat.ethz.ch/mailman/listinfo/r-sig-mac >> > > [[alternative HTML version deleted]] > > _______________________________________________ > R-SIG-Mac mailing list > [email protected] > https://stat.ethz.ch/mailman/listinfo/r-sig-mac _______________________________________________ R-SIG-Mac mailing list [email protected] https://stat.ethz.ch/mailman/listinfo/r-sig-mac
