ATLAS threaded 64 bit Opteron build for R: need -fPIC

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.

/