Is R more heavy on memory or processor?
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 De inhoud van dit bericht is vertrouwelijk en alleen bestemd voor de geadresseerde(n). Anderen dan de geadresseerde(n) mogen geen gebruik maken van dit bericht, het niet openbaar maken of op enige wijze verspreiden of vermenigvuldigen. Het UMCG kan niet aansprakelijk gesteld worden voor een incomplete aankomst of vertraging van dit verzonden bericht. The contents of this message are confidential and only intended for the eyes of the addressee(s). Others than the addressee(s) are not allowed to use this message, to make it public or to distribute or multiply this message in any way. The UMCG cannot be held responsible for incomplete reception or delay of this transferred message. [[alternative HTML version deleted]]
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Dan Putler Sauder School of Business University of British Columbia _______________________________________________ R-SIG-Mac mailing list R-SIG-Mac at stat.math.ethz.ch https://stat.ethz.ch/mailman/listinfo/r-sig-mac