On 27 Feb 2004, Douglas Bates wrote: > Martin Maechler <[EMAIL PROTECTED]> writes: > > > >>>>> "PD" == Peter Dalgaard <[EMAIL PROTECTED]> > > >>>>> on 26 Feb 2004 15:44:16 +0100 writes: > > > > PD> Douglas Bates <[EMAIL PROTECTED]> writes: > > >> Have you tried configuring R with Goto's BLAS > > >> http://www.cs.utexas.edu/users/kgoto/ > > >> > > >> I haven't worked with Opteron or Athlon64 computers but I understand > > >> that Goto's BLAS are very effective on those machines. Furthermore > > >> Goto's BLAS are (only) available as .so libraries so you don't need to > > >> mess with creating the .so version. > > > > PD> I tried it, yes. Somewhat to my surprise, it seemed to be not quite as > > PD> fast as the threaded ATLAS, but I wasn't very systematic about the > > PD> benchmarking. > > > > PD> (and the Goto items have license issues, which get in the way for > > PD> binary distributions.) > > > > Thanks a lot, Peter, Brian, Doug, for your feedbacks! > > In the mean time, I have three running versions of R(-devel) on > > the 64-Opteron > > - "plain" > > - linked against threaded GOTO > > - linked against threaded (static) ATLAS (using -fPIC for compilation; > > "large" Rlapack) > > and I find that GOTO is faster than ATLAS > > consistently (between ~ 5-20%) for several tests > > (square matrices; %*% and solve). > > ATLAS is still an order of magnitude faster than "plain" for > > 3000x3000 matrices. > > Would you be willing to post a brief summary of comparative timings? > > I have thought at times that it may be worthwhile collecting > comparative timings for different combinations of > processor/OS/memory size and speed/ > on "typical" tasks in R. As with any benchmark the results will > artificial but they can be of some help when considering what hardware > to purchase. Bioconductor users may find it particularly helpful to > be able to evaluate how much they will need to pay to be able to > analyze large data sets reasonably quickly. > > One easily-obtained timing is at the end of > $RSRC/tests/Examples/base-Ex.Rout after 'make;make check'.
That one is I think rather too artificial, as it contains few even moderately large examples, and is dominated by a few atypical tasks. I tend to use the sum of the MASS scripts as an informal timing: ch06.R is also a pretty good indicator. I think you will find that BLAS differences are pretty small in real-life analyses, or at least I always have. -- 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 ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-devel
