[R] Speed up R

[Prof Brian Ripley]

On Wed, 20 Jun 2007, Robert McFadden 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?

Yes, you can.  You will get very close to 2x speed up if you have enough 
(and fast enough) RAM.

> 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.

On a dual processor machine you need more to avoid any swapping.  Even my
2.5 year old laptop has 1Gb, and I'd want at least 2Gb in a dual processor 
machine given that spec.  My sysadmin suggests a minimum of 4Gb for 64-bit 
dual processors these days.

> 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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>

-- 
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