[Rd] 64 Bit

[Prof Brian Ripley]

Please read the R FAQ, which does cover this.  You need to distinguish 
64-bit OSes from 64-bit hardware (`computers').

R builds on least for the `native' Unix on Alpha, Sparc, HPPA and MIPS
processors (for the last several years each), AIX on PowerPC, Linux on
ia64 (Itanium), x86_64 (aka AMD64 and EM64T etc) and most of these. In
most cases it runs under 32-bit and 64-bit versions of the OSes on those
64-bit hardware.

R does not run under (beta) 64-bit Windows on x86_64 and we have no plans
to port it there, but it does run under 32-bit Windows on that processor.  
I am sure it will run on several 64-bit operating systems on Apple
Macintosh's so-called G5 hardware -- I believe we have seen a report that
includes an in-progress version of MacOS 10.4 -- and also several 32-bit
ones.

If you want a prebuilt version you are out of luck except for Debian Linux 
on Alpha or ia64, from a quick glance.

Many of us, including several of the core team, use 64-bit Linux on x86_64
as our main computer-intensive resource.

Please using single spacing, not *quadruple* spacing and a reasonable line
length, and do not include HTML as the posting guide asks.

BDR

On Fri, 22 Oct 2004, Daniel Weicht wrote:

> Hello everybody!
> 
>  

[next para wrapped by BDR]

> We at the Max Planck Society of Molecular Plant Physiologie want to
> know, if there is R version available for a 64 bit computer. If yes for
> which processor an amd or for a 64 bit Mac
> 
>  
> 
> Thanks a lot
> 
>  
> 
> Daniel
> 
>  
> 
> ____________________________________________________
> 
>  
> 
> Daniel Weicht
> 
>  
> 
> Max Planck Institute of Molecular Plant Physiology
> 
>  
> 
>  Am Mühlenberg 1
> 
>  
> 
> 14476 Golm, Germany 
> 
>  
> 
> Phone +49 331 567 8277
> 
>  
> 
> e-mail weicht at mpimp-golm.mpg.de <mailto:weicht at mpimp-golm.mpg.de> 
> 
>  
> 
> __________________________________________________
> 
>  
> 
> 
> 	[[alternative HTML version deleted]]
> 
> ______________________________________________
> R-devel at stat.math.ethz.ch mailing list
> https://stat.ethz.ch/mailman/listinfo/r-devel
> 
> 

-- 
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