[R] R on 64-bit Linux machine
Liaw, Andy
andy_liaw at merck.com
Fri Nov 12 22:34:04 CET 2004
We've had good experience so far with the threaded Goto BLAS (on Opteron
244/248/250, SLES8).
Has anyone tried building R with supposedly more optimized compilers (PGI,
EKO, etc.)? If so, how do they stack up against GCC?
Best,
Andy
> From: Roger D. Peng
>
> I've built (and routinely use) 64 bit R on the following platforms:
>
> Red Hat Enterprise Linux AS release 3 (AMD Opteron 848)
> Fedora Core 2 x86_64 (AMD Athlon 64 3800+)
> SuSE SLES 8 (AMD Opteron 248)
>
> One problem that has come up is that if you want to link R
> with ATLAS,
> you need to build shared ATLAS libraries (rather than static). This
> requires some modifications to the configuation files for ATLAS. But
> my experience shows that R itself builds out of the box on
> these systems.
>
> -roger
>
> Vadim Ogranovich wrote:
> > Hi,
> >
> > We are planning to buy a 64-bit Linux machine which will
> mainly run R.
> > There was an interesting thread on 64-bits on r-help back
> in April that
> > basically confirmed that the 64-bit R is fine as long as
> the length of
> > an atomic object is less than 2^31 - 1.
> >
> > My specific question is on which 64-bit Linux distros (SUSE
> or RedHat)
> > and processors R is *known* to build out-of-box and run
> well. Ease of
> > maintenance is essential here. We have RedHat 7.3 on other (32-bit)
> > machines and would try not to proliferate the OS-s.
> >
> >
> > Your information will be highly appreciated,
> >
> > Thanks,
> > Vadim
> >
> > [[alternative HTML version deleted]]
> >
> > ______________________________________________
> > R-help at stat.math.ethz.ch mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide!
> http://www.R-project.org/posting-guide.html
> >
>
> --
> Roger D.
> Peng
> http://www.biostat.jhsph.edu/~rpeng/
>
> ______________________________________________
> R-help at stat.math.ethz.ch mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide!
> http://www.R-project.org/posting-guide.html
>
>
More information about the R-help
mailing list