[R] Speed up R

[Matthew Keller]

Robert,

I'm not exactly an expert, but here's what I think. If you have only
786 MB of RAM on your machine and you are using ~500 of it in a
session of R, that could slow things down considerably because your
machine is trying to find free blocks of memory that haven't been used
yet. I would buy additional RAM.

As for Mike Prager's point about the type of hard drive being
important, I'm not sure this is right (someone correct me if I'm
misunderstanding). R stores and accesses objects through RAM - they
aren't stored and accessed on the hard drive except when reading and
writing. So hard drive type probably won't make much difference to
speed in R.

Matt

On 6/20/07, Robert McFadden <robert-mcfadden at o2.pl> wrote:
>
> > -----Original Message-----
> > From: Prof Brian Ripley [mailto:ripley at stats.ox.ac.uk]
> > The advantage of dual processors is that you can use the
> > machine for several things at once, including multiple R
> > jobs.  For example, when I am doing package checking I am
> > typically checking 4 packages at once on a dual processor
> > machine to get continuous high utilization.
>
> I would like to thank very much everybody taking part in discussion.
> Does an answer above suggest that I can open two R console and do
> simulations simultaneously? If so, all simulations take more or less 1/2
> times - or much less then doing it in turn?
>
> During our discussion one mentioned that RAM is important. But in my
> computing I do not use up more then 500 MB. I have 786 MB it means
> (probably) that I have enough.
> Am I right?
>
> Best,
> Rob
>
>
>
> > I have little doubt that a Pentium 4 would be much slower
> > than the others.
> >
> > I've just bought an Intel Core 2 Duo E6600 primarily to run
> > 64-bit Linux, but it also has Vista 64 and XP (32-bit) on it.
> >  I don't think the differences between the current dual-core
> > chips are really enough to worry about: they will all look
> > slow in less than a year.
> >
> > --
> > 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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>


-- 
Matthew C Keller
Postdoctoral Fellow
Virginia Institute for Psychiatric and Behavioral Genetics