[R] high RAM on Linux or Solaris platform
dbickel at uottawa.ca
Wed Oct 31 18:58:32 CET 2007
Dr. Lumley and Prof. Ripley,
Thank you very much for your helpful responses.
Have you found any particular distribution of Linux to work well with
64-bit R? For the cluster, I am currently considering Debian (since it
seems popular) and SUSE (since Matlab runs on it), but I remain open to
From: Prof Brian Ripley [mailto:ripley at stats.ox.ac.uk]
Sent: Tuesday, October 30, 2007 4:51 PM
To: Thomas Lumley
Cc: David Bickel; r-help at stat.math.ethz.ch
Subject: Re: [R] high RAM on Linux or Solaris platform
On Tue, 30 Oct 2007, Thomas Lumley wrote:
> On Tue, 30 Oct 2007, David Bickel wrote:
>> To help me make choices regarding a platform for running high-memory
>> processes in parallel, I would appreciate any responses to these
>> 1. Does the amount of RAM available to an R session depend on the
>> processor (Intel vs. Sun) or on the OS (various Linux distributions
> It depends on whether R uses 64-bit or 32-bit pointers. For 64-bit R
> need a 64-bit processor, an operating system that will run 64-bit
> programs, and a compiler that will produce them.
> I'm not sure what the current Intel offerings are, but you can compile
> and run 64-bit on AMD Opteron (Linux) and Sun (Solaris) systems.
That is both Sparc Solaris and x86_64 Solaris (although for the latter
seem to need to use the SunStudio compilers).
As far as I know all current desktop Intel processors run x86_64, and
Xeons seem to have a price-performance edge at the moment. We have
boxes with dual quad-core Xeons and lots of RAM. (Not all for use with
some Linux, some Windows.) Core 2 Duos do, and are commonplace in quite
>> 2. Does R have any built-in limitations of RAM available to a
>> For example, could it make use of 16 GB in one session given the
>> processor/OS platform?
> R does have built-in limitations even in a 64-bit system, but they are
> large. It is certainly possible to use more than 16Gb of memory.
> The main limit is that the length of a vector is stored in a C int,
> so is no more than 2^31-1, or about two billion. A numeric vector of
> that length would take up 16Gb on its own.
?"Memory-limits" documents them.
>> 3. Is there anything else I should consider before choosing a
>> and OS?
> I don't think there is anything else R-specific.
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
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