[R-SIG-Mac] Is R more heavy on memory or processor?

[Steven McKinney]

I agree with Dan, memory will often be the limiting
factor.  I added RAM (16GB total) to my ppc and have
had a much more productive environment, both for
32 bit and 64 bit applications.

Even if a single R session cannot benefit from multiple
cores, if you can break your processes into parallel
pieces you can use your separate CPUs with cluster
software, or just run multiple R jobs manually.

I'd recommend maximizing your RAM quantity over
RAM speed.  Also, determine the speed gain.
Speed gains of 10-fold or more are noticeable,
speed gains of 2 to 3 fold rarely make much of a 
difference.

Steven McKinney, Ph.D.

Statistician
Molecular Oncology and Breast Cancer Program
British Columbia Cancer Research Centre

email: smckinney +at+ bccrc +dot+ ca

tel: 604-675-8000 x7561

BCCRC
Molecular Oncology
675 West 10th Ave, Floor 4
Vancouver B.C. 
V5Z 1L3
Canada




-----Original Message-----
From: r-sig-mac-bounces at stat.math.ethz.ch on behalf of Dan Putler
Sent: Tue 3/24/2009 12:08 PM
To: Booman, M
Cc: R-SIG-Mac
Subject: Re: [R-SIG-Mac] Is R more heavy on memory or processor?
 
Hi Marije,

Personally, I would be more concerned with memory than processor.
Running out of memory can be an unpleasant surprise. Base R uses a
single core, but Simon Urbanek's multicore package (the most recent
version of which, 0.1-3, is dated today) does allow you to use multiple
cores at once. I haven't used this package, so can't offer any personal
experience.

Dan
 
On Tue, 2009-03-24 at 19:55 +0100, Booman, M wrote:
> Dear all,
>  
> I am going to purchase a Power Mac (a new one, with Nehalem processor) for my R-based microarray analyses. I use mainly Bioconductor packages, and a typical dataset would consist of 50 microarrays with 40,000 datapoints each. To make the right choice of processor and memory, I have a few questions:
>  
> - would the current version of R benefit from the 8 cores in the new Intel Xeon Nehalem 8-core Mac Pro? So would an 8-core 2.26GHz machine be better than a 4-core 2.93GHz? Or can R only use one core (in which case the 4-core 2.93GHZ machine would be better)?
>  
> - If R does not benefot from multiple cores yet, is there anything known about whether Snow Leopard might make a difference in this?
>  
> - To determine if my first priority should be processor speed or RAM, on which does R rely more heavily?
>  
> - The new chipset has 3 memory channels (forgive me if I word this wrong, as you may have noticed I am no computer tech) so it can read 6Gb RAM faster than it can read 8Gb of RAM; so for a program that relies more on RAM speed than RAM quantity it is recommended to use 6Gb instead of 8 for better performance (or any multiple of 3). Which is more important for R, RAM speed or RAM quantity?
>  
> (I am not sure if it helps to know, but previously I used a Powermac G5 quadcore (sadly I forgot which processor speed but it was the standard G5 quadcore) with 4 Gb RAM for datasets of 30-40 microarrays of 18,000 datapoints each, and analysis was OK except for some memory errors in a script that used permutation analysis; but it wasn't very fast.)
>  
> Any recommendations are welcome!
>  
> Marije Booman
> 
> 
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-- 
Dan Putler
Sauder School of Business
University of British Columbia

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