From sgiannerini at gmail.com  Tue Mar  7 14:39:13 2006
From: sgiannerini at gmail.com (Simone Giannerini)
Date: Tue, 7 Mar 2006 14:39:13 +0100
Subject: [Rd] Running R on dual/quad Opteron machines
In-Reply-To: <Pine.LNX.4.64.0603070907380.12003@gannet.stats.ox.ac.uk>
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	<C031F78E.7745%sdavis2@mail.nih.gov>
	<3c12769c0603070059kfa51d68h8c2da372beecef29@mail.gmail.com>
	<Pine.LNX.4.64.0603070907380.12003@gannet.stats.ox.ac.uk>
Message-ID: <3c12769c0603070539o42fdff4cucab46ba85531bca1@mail.gmail.com>

Dear prof. Ripley,

many thanks for the clarification, now I have good elements for
managing the purchase.

kind regards,

Simone Giannerini

On 3/7/06, Prof Brian Ripley <ripley at stats.ox.ac.uk> wrote:
> On Tue, 7 Mar 2006, Simone Giannerini wrote:
>
> > Ok thanks, I am wondering whether running multiple instances of R
> > would be possible without problems in presence of compiled code
> > (shared libraries).
> > Intuitively, while there can be multiple instances of R, all of them
> > would be using the same library, but I am just guessing, I might do a
> > check on this.
>
> That's what the `shared library' means.  The common parts (e.g. code and
> static data) are shared, but the data areas are not.
>
> Different processes run in different address spaces, and modern OSes are
> careful only to give a user process write access to its own address space.
>
> Many of us have servers running multiple copies of R at almost all times.
> I typically run R tests with four copies running on a dual-CPU Opteron,
> that being about the minimum number needed to get 100% CPU usage since I/O
> is also being done.
>
> >
> > Ciao
> >
> > Simone
> >
> >>
> >> And let me couch my earlier statements on snow/Rmpi by saying that we use
> >> these tools on a relatively large beowulf cluster (~200 nodes), which is
> >> somewhat different than a single box with 2-4 processors, so it is may not
> >> be worth the trouble outside of a cluster environment.  For example, we have
> >> not moved to using Rmpi/snow on our dual-processor G5s because the speed
> >> gain just isn't worth the extra installation trouble, etc.
> >>
> >> Sean
>
> --
> 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
>


--
______________________________________________________

Simone Giannerini
Dipartimento di Scienze Statistiche "Paolo Fortunati"
Universita' di Bologna
Via delle belle arti 41 - 40126  Bologna,  ITALY
Tel: +39 051 2098248  Fax: +39 051 232153
E-mail: giannerini at stat.unibo.it



[Rd] Running R on dual/quad Opteron machines
Simone Giannerini