[R] high RAM on Linux or Solaris platform

[Prof Brian Ripley]

On Wed, 31 Oct 2007, David Bickel wrote:

> 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
> others.

These days I think there is no difference.  (SuSE did much of the 
development for x86_64 Linux, and Debian was one of the later ones to 
support it.  But that's going back ca 4 years.)

Commercial products normally only support commercial distributions of 
Linux, but Matlab does run on many others.

I would find the overriding consideration to be the availability of local 
support.

>
> Best regards,
> David
>
>
> -----Original Message-----
> 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
> R
>>> processes in parallel, I would appreciate any responses to these
>>> questions:
>>>
>>> 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
> vs.
>>> Solaris)?
>>
>> Yes.
>>
>> It depends on whether R uses 64-bit or 32-bit pointers. For 64-bit R
> you
>> 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
> you
> 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
> several
> boxes with dual quad-core Xeons and lots of RAM.  (Not all for use with
> R,
> some Linux, some Windows.)  Core 2 Duos do, and are commonplace in quite
>
> low-end systems.
>
>
>>> 2. Does R have any built-in limitations of RAM available to a
> session?
>>> For example, could it make use of 16 GB in one session given the
> right
>>> 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,
> and
>> 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
> processor
>>> 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