Hi, Sorry for sending such a late reply, and for being abit OT.
I've been trying to compile 64 bit ATLAS for numpy (http://numeric.scipy.org/ ), and so far this thread is the most useful one I could google up - thanks!. I encountered similiar problems, and so far could not get a .a linkable to numpy (comparing to your post - it seems I might have forgotten to add the -fPIC for the F77FLAGS or MMFLAGS). Also, I'm having trouble with the ATLAS lapack. To get a usable lib, one has to merge it with a full lapack implementation (as described in the ATLAS errata). However, I'm using RHEL4, and their installed liblapack.a seems to have been compiled without -fPIC, so the merged library is unlinkable to numpy's .so. Is there a way to use Redhat's installed liblapack.so? Few questions about your compiler flags: 1) Is there a reason to compile with -O rather than -O3? (did you try and encounter some problem, or found no major performance difference) 2) I see you use -mfpmath=387 - does this work better than sse2 (which seems to be the default)? How about the "sse,387" option - should I try that? Martin Maechler wrote: >>>>>/ "PD" == Peter Dalgaard <p.dalgaard at biostat.ku.dk >>>>><https://www.stat.math.ethz.ch/mailman/listinfo/r-devel>> />>>>>/ >>>>>> "PD" == Peter Dalgaard <p.dalgaard at biostat.ku.dk> >>>>>> on 26 Feb 2004 15:44:16 +0100 writes: > > PD> Douglas Bates <bates at stat.wisc.edu> 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. > >Here are somewhat repeatable "ATLAS for R" build instructions: > > 1. get ATLAS source; unpack > 2. make : use defaults and "express" installation > 3. Before "make install ...", edit the Make.<ARCHITECTURE> file: > add "-fPIC" to three places, namely F77FLAGS, CCFLAG0, and MMFLAGS: > which in case of the "threaded Opteron" architecture, leads to > the three new lines > F77FLAGS = -fPIC -fomit-frame-pointer -O -m64 > > CCFLAG0 = -fPIC -fomit-frame-pointer -O -mfpmath=387 -m64 > > MMFLAGS = -fPIC -fomit-frame-pointer -O -mfpmath=387 -m64 > in the file Make.Linux_HAMMER64SSE2_2 > > 4. make install arch=Linux_HAMMER64SSE2_2 > > 5. Sym.link the ATLAS libraries into /usr/local/lib: > > cd /usr/local/lib > ln -s <ATLAS_build_dir>/lib/Linux_HAMMER64SSE2_2/lib* . > > 6. (needed for runtime!): > Use environment variable LD_LIBRARY_PATH=/usr/local/lib > > >Note that I haven't built *.so (shared) libraries yet. / ______________________________________________ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
