[R] which operating system + computer specifications lead to the best performance for R?
jwiley.psych at gmail.com
Sun Jan 23 03:56:13 CET 2011
On Sat, Jan 22, 2011 at 6:37 PM, Santosh Srinivas
<santosh.srinivas at gmail.com> wrote:
> Hi Marc,
> I've exactly the same question and it looks like most of the heavy users
> from the threads I've followed use Unix/Linux/Mac.
> Some threads have given rationale for a 64bit system due to memory benefits
> but there seems to be not much buy-in from the guys here (so I'd give that a
> pass). The CRAN page also isn't very excited about 64bit for now.
Really? Perhaps I do not understand what you meant, but doesn't most
HPC work take > (2^32) bytes of memory?
> As David mentioned, Dirk's work seems to be hungry from speed and I closely
> (try to) follow his work.
> >From his blog, he uses a "Debian Linux system" and that is what I've set up
> for myself. This obviously may just be a matter of coincidence.
> (But, saves me a lot of time trying to figure out issues related to the
> other OS's. Also, many authors of the packages that I use really don't have
> the time or inclination to make is Windoze friendly.)
> My 2p in transition.
> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On
> Behalf Of David Winsemius
> Sent: 22 January 2011 21:02
> To: Marc Jekel
> Cc: r-help at r-project.org Help
> Subject: Re: [R] which operating system + computer specifications lead to
> the best performance for R?
> On Jan 22, 2011, at 10:03 AM, Sascha Vieweg wrote:
>> On 11-01-22 14:56, Marc Jekel wrote:
>>> I have the opportunity to buy a new computer for my simulations in
>>> R. My goal is to get the execution of R code as fast as possible. I
>>> know that the number of cores and the working memory capacity are
>>> crucial for computer performance but maybe someone has experience/
>>> knowledge which comp specifications are especially crucial
>>> (especially in relation to R). Is there any knowledge on the
>>> performance of R for different operating systems (Linux, Win, Mac
>>> etc.) resp. is performance dependent on the operating system at
>>> all? Even small differences in performance (i.e., speed of
>>> calculations) matter for me (quite large datasets + repeated
>>> calculations etc.).
>> Not really a recommendation, just my considerations: That depends on
>> your budget, Mac Pro (5k$ in the U.S.) would probably serve your
>> needs for a long time ;-). I am running R 2.12.0 on a MacBook Pro,
>> 2.4 Dual Core with (only) 2G ram, together with (paid) TextMate as
>> editor, and Sweave. 2G ram is few! And I noted remarkable
>> improvements whan I was lucky to use a MBP Intel Core i5 for a
>> couple of days. Whatever processor and memory, I like the easy
>> interplay between R and the Unix environment (things like passing
>> shell commands from R to my system or other interpreters), easy
>> graphics etc.
> I also use a MacPro (circa early 1998) R 2.12.1 with 24 GB and still
> find it generally very capable for a dataset of 5.5 MM rows and about
> 150 variables using the survival and rms packages. I seem to remember
> a price of 4KUS$ but I didn't write that check. I haven't succeeded in
> getting the multi-processor applications to work, however, and my
> guess is that Linux boxes (and Linux users) may be more likely to
> offer paths to success if that is an expectation. I am mostly
> interested in having adequate memory space for one core anyway, as
> most of the packages I use don't seem to be set up for parallel
> It may depend on what development system you use and which packages
> you expect to install. I know there are people with the StatET-
> equipped systems out there but I have never been able to get a working
> setup on my Mac. Too many moving parts and the gears don't seem to
> mesh out of the box. Same with GTK2+ and its R friends.
> This would be better posted on the HPC mailing list anyway:
> You might want to search with "Dirk Eddelbuettel" in your search
> string, since he seems to share your "need for speed" and has
> championed various approaches to High Performance Computing with R:
> David Winsemius, MD
> West Hartford, CT
Ph.D. Student, Health Psychology
University of California, Los Angeles
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