From ripley at stats.ox.ac.uk  Tue Oct 24 08:57:42 2006
From: ripley at stats.ox.ac.uk (Prof Brian Ripley)
Date: Tue, 24 Oct 2006 07:57:42 +0100 (BST)
Subject: [Rd] Excessive network load
In-Reply-To: <005401c6f6b5$c556ee80$70160e8d@molgen.mpg.de>
References: <005401c6f6b5$c556ee80$70160e8d@molgen.mpg.de>
Message-ID: <Pine.LNX.4.64.0610240742040.31577@gannet.stats.ox.ac.uk>

You haven't even told us your OS!

The simple solution is to use a local copy of R.  It is probably the case 
that few of those 1500 packages are used, and certainly that few are used 
in each R session: you may also want to install locally any that are 
heavily used.

We found it advantageous to do this for Windows users of R (where the 
remote discs are mounted by SMB) quite a while ago, and more recently 
moved to local installation of R on Linux machines.  The issue was not 
network load but latency for interactive users: although R is heavily used 
here it is not a major component of our network load and we are rather 
protecting R users against other applications that are much more 
demanding.

On Mon, 23 Oct 2006, Claudio Lottaz wrote:

> Dear all,
>
> I wonder, if anybody experiences similar problems and if there are any 
> simple solutions to be suggested. We observe that R causes a lot of 
> network traffic and thus slows down the performance of the whole 
> network. When tracing the network traffic on the machine which serves 
> the R installation via NFS, we see thousands of requests at 
> initialization of R processes and regular calls, probably to shared 
> libraries. Is there a way to compile or run R such that it causes less 
> load on the network?
>
> Here is some information  on our installation:
> - We use a single installation of R (version 2.3.1) loaded over NFS
> - there are approximately 1500 packages installed using ~8GB of disk
> - We use R on a queuing system running up to 50 processes in parallel
>
> The load on the machine which serves the R installation frequently rises up to 5 or so although it is a dedicated machine.
> Any hints towards measures against network load are highly appreciated.
>
> Thanks,
> Claudio
>
>
>

-- 
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




[Rd] Excessive network load
Prof Brian Ripley