[R-SIG-Mac] daxpy performance with veclib

[Simon Urbanek]

On Oct 20, 2010, at 2:18 PM, Michael Spiegel wrote:

> Hi Mac Special Interest Group folks,
> 
> We've noticed some curious behavior of the veclib BLAS implementation
> in the development of the OpenMx library.  The daxpy implementation
> appears to be twice as slow in the veclib implementation as compared
> to the reference implementation.  


Yes, that is a known problem (see R-SIG-Mac archives). vecLib fails to use multiple cores on Nehalem-based Mac Pros. If you use ATLAS directly it will work just fine - that's what we recommend on Mac Pros.

Cheers,
Simon




> Attached is a test kernel that has
> been run under both implementations.  The kernel consists of repeated
> calls to daxpy with vectors of varying size.  In the output files, the
> first column is the dimension of the vector.  The 2nd-4th column
> report the runtime in seconds of the kernel; three identical trials
> per vector size.
> 
> It may be more appropriate to send this information upstream to the
> veclib persons.  However, I thought it would be of interest to Mac R
> folks, too.  For our own project, our workaround will be to create our
> own basic implementation of daxpy, and continue to link against the
> veclib BLAS library so we can get a speedup on dgemm and the other
> functions.
> 
> The benchmarks were executed on a Mac Pro with 2 Quad-Core Xeons @ 3
> GHz (MacPro2,1) running OS X 10.5.8.  It was tested with R 2.12.0 and
> the same behavior has been observed with R 2.10.1.
> 
> Thanks,
> --Michael
> <omxTest.c><daxpy.veclib.results><daxpy.refblas.results>_______________________________________________
> R-SIG-Mac mailing list
> R-SIG-Mac at stat.math.ethz.ch
> https://stat.ethz.ch/mailman/listinfo/r-sig-mac