On Fri, 2 Jun 2006, Roger D. Peng wrote: > Running on 64-bit per se does not make things faster. In fact, from my > experience it sometimes makes things slower. The advantage with 64-bit > is the extra address space for storing things in memory.
See the R-admin manual for some additional comments. Certainly until you use more than say 300Mb the extra overhead of 64-bit pointers is pure overhead. (At some point nearer the address space limit you do GC a lot more often on a 32-bit platform.) > Of course, today's 64-bit chips are all faster than recent 32-bit chips, > so you will get a speed improvement, but only because you're getting a > better chip. Not entirely true right now: some of the Pentium Core/Duo Core 32-bit chips are competitive. (Pentium M chips have often been very fast for their nomimal clock speeds.) > -roger > > Kerpel, John wrote: >> The benchmark report is good stuff - I've been wondering about these >> speed issues recently myself. >> >> Has anyone tried something similar on 64-bit Linux or other OS? I'm >> contemplating switching to 64-bit Linux if I'll get some dramatic cycle >> time improvements. Anyone have any experience with this? >> >> Best, >> >> John >> >> -----Original Message----- >> From: [EMAIL PROTECTED] >> [mailto:[EMAIL PROTECTED] On Behalf Of Liaw, Andy >> Sent: Friday, June 02, 2006 10:01 AM >> To: ivo welch; [email protected] >> Subject: Re: [R] speed? >> >> You (and your colleague) might want to have a look at >> http://www.sciviews.org/benchmark/. It's a bit dated, >> but still may be a good starting point. >> >> Some months ago some one asked about working on getting >> R to use the GPU for computation on the R-devel list. >> Don't know if anything came of it. >> >> Cheers, >> Andy >> >> From: ivo welch >>> dear R wizards: >>> >>> while extolling the virtues of R, one of my young >>> econometrics colleagues told me that he still wants to run ox >>> because [a] his code is written in it (good reason); [b] >>> because ox seems to be faster than R in most benchmarks (huh?). >>> >>> this got me to wonder. language speed can't matter much, so >>> it must be mostly the underlying matrix algebra by now. I >>> presume that nowadays most of the plain matrix operation >>> speed depends primarily on which hardware features the >>> library accesses. (The basic algorithms aren't so different, >>> so even though the algorithm may have mattered a long time >>> ago, they are probably pretty similar nowadays. hmmm...maybe >>> matrix inversion still is different, but multiplication and >>> adding should not be.) >>> >>> On x86 architecture, I believe there is a hierarchy in terms >>> of raw processing power: FPU < SSE* < GPU. >>> >>> is it even possible to use the GPU now for math processing >>> (linux or windows), and specifically in R? >>> >>> assuming I compile everything with the proper SSE flags and atlas, is >>> SSE* fully taken advantage of? >>> >>> regards, >>> >>> /ivo >>> >>> ______________________________________________ >>> [email protected] mailing list >>> https://stat.ethz.ch/mailman/listinfo/r-help >>> PLEASE do read the posting guide! >>> http://www.R-project.org/posting-guide.html >>> >>> >> >> ______________________________________________ >> [email protected] mailing list >> https://stat.ethz.ch/mailman/listinfo/r-help >> PLEASE do read the posting guide! >> http://www.R-project.org/posting-guide.html >> >> ______________________________________________ >> [email protected] mailing list >> https://stat.ethz.ch/mailman/listinfo/r-help >> PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html >> > > -- Brian D. Ripley, [EMAIL PROTECTED] Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UK Fax: +44 1865 272595 ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
