[R-SIG-Mac] Is R more heavy on memory or processor?
dan.putler at sauder.ubc.ca
Tue Mar 24 20:08:46 CET 2009
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
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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