single-threaded R, 100% CPU with BLAS, vecLib and ATLAS
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 rayd at liondatasystems.com (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 <mcourtot at gmail.com> 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 --- M?lanie Courtot MSFHR/PCIRN Ph.D. Candidate, BCCRC - Terry Fox Laboratory - 12th floor 675 West 10th Avenue Vancouver, BC V5Z 1L3, Canada
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