Hello Johannes,
These topics have been fairly well discussed on the helplist, so a
search will return you a lot more results.
Regarding memory, there are options besides simply increasing RAM
(although if you have the funds, by all means). Look at
http://crantastic.org/packages/ff and
http://crantastic.org/packages/bigmemory and some of the related
packages.
Regarding multi-core processors. R does not use multiple threads by
default, but there are many packages that can utilize multi-core
processors. Look at http://crantastic.org/packages/multicore and
also this article http://www.jstatsoft.org/v31/i01 discusses some of
the options there.
Regarding operating systems, I am not certain what you consider
'standard operating systems'. You would certainly want 64-bit.
Beyond that I know that some versions of Windows (e.g., the 'basic',
'starter' or 'home' lines) are often limited in their memory
usage
even for 64-bit. Microsoft gives the details here
http://msdn.microsoft.com/en-us/library/aa366778(VS.85).aspx
I would hazard the guess that as long as you purchase the computer
pre-made, the manufacturer will ensure that the OS, processor, and RAM
amounts, types, speeds, etc. are all compatible. A search for
'workstations' should turn up results about where you might shop for
an appropriate computer. There are many options available.
Just to reiterate, there is a lot more information available on each
of these topics in the archives, here is a link where you can easily
search them http://tolstoy.newcastle.edu.au/~rking/R/
Best regards,
Josh
On Sun, Jun 6, 2010 at 11:06 PM, Johannes Reichl
<reichl at energieinstitut-linz.at> wrote:> Hi all,
>
> I need to do massive simulations in the next two years. I estimated
> that I will need about 64GB memory, if I do not want to split up the
> calculations. Additionally I would like to have it as fast as possible.
>
>
> Can R handle multi-core processors and can all standard operating
> systems handle the same amount of memory and speed?
>
> Perhaps someone could point me to a webshop that sales such equipment
> that is suiteable for fast R computation.
>
> Thank you, Johannes
>
>
> Dr. Johannes Reichl
> Abteilung Energiewirtschaft
> Energieinstitut an der Johannes Kepler Universit?t Linz
> Altenberger Stra?e 69
> A-4040 Linz
> *****************************
> Tel.: +43-732-2468-5652
> Fax: +43-732-2468-5651
> Email: reichl at energieinstitut-linz.at
> Web: www.energieinstitut-linz.at
> ? ? ? ? www.energyefficiency.at
>
>
> ? ? ? ?[[alternative HTML version deleted]]
>
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
>
--
Joshua Wiley
Senior in Psychology
University of California, Riverside
http://www.joshuawiley.com/