[R] 64 bit R slower than 32 bit R on Sun Sparc Solaris?

[Jason Liao]

Thank you very much, Profs. Ripley and Peng! It corrected a big
misconception in my mind. 

By the way, does the Sun Forte 7 compiler produce faster R than the GCC
3.4.1 compiler (which we use)?

Jason

--- Prof Brian Ripley <ripley at stats.ox.ac.uk> wrote:

> On Tue, 7 Sep 2004, Roger D. Peng wrote:
> 
> > Are you using an optimized BLAS for both builds?  That's one
> > possibility.  Also, 64-bit builds use up more memory initially
> since the
> > pointers are bigger.  I've tried both 64-bit and 32-bit builds on
> > Sparc/Solaris and haven't seen any slowdown.
> 
> It uses more memory at all times and so gc() takes longer.  There
> *is* a
> slowdown, for example 90 vs 80 secs for a run of R-devel's stats-Ex.R
> (for
> either Sun's Forte 7 or gcc 3.4.1 compilers).  But `25-30% slower' is
> unexpected and needs investigation.
> 
> The only difference between 32-bit and 64-bit versions of R on
> Solaris 
> will be the size of the pointers and (probably) less efficient PIC
> code.
> There is no reason to expect a performance boost with 64-bit
> applications: 
> they have to do more work and are only worthwhile if you need the
> address 
> space (in memory or also on disc as 64-bit applications use large
> files 
> natively).
> 
> 
> > Jason Liao wrote:
> > 
> > > Hello, everyone! I guess no one is still using R on Sun Sparc
> these
> > > days. But our department has a (pretty new) two-CPU Sun server.
> We
> > > recently compiled R as a 64 bit application and expected a
> performance
> > > boost. But it runs 25-30% slower than the 32 bit version of R.
> Anyone
> > > knows why this is so? Thanks!
> 
> -- 
> Brian D. Ripley,                  ripley at stats.ox.ac.uk
> 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
> 
> 


=====
Jason Liao, http://www.geocities.com/jg_liao
Dept. of Biostatistics, http://www2.umdnj.edu/bmtrxweb
University of Medicine and Dentistry of New Jersey
phone 732-235-5429, School of Public Health office
phone 732-235-8611, Cancer Institute of New Jersey office
moble phone 908-720-4205