On Wed, 20 Jun 2007, Robert McFadden wrote: > >> -----Original Message----- >> From: Prof Brian Ripley [mailto:[EMAIL PROTECTED] >> The advantage of dual processors is that you can use the >> machine for several things at once, including multiple R >> jobs. For example, when I am doing package checking I am >> typically checking 4 packages at once on a dual processor >> machine to get continuous high utilization. > > I would like to thank very much everybody taking part in discussion. > Does an answer above suggest that I can open two R console and do > simulations simultaneously? If so, all simulations take more or less 1/2 > times - or much less then doing it in turn?
Yes, you can. You will get very close to 2x speed up if you have enough (and fast enough) RAM. > During our discussion one mentioned that RAM is important. But in my > computing I do not use up more then 500 MB. I have 786 MB it means > (probably) that I have enough. On a dual processor machine you need more to avoid any swapping. Even my 2.5 year old laptop has 1Gb, and I'd want at least 2Gb in a dual processor machine given that spec. My sysadmin suggests a minimum of 4Gb for 64-bit dual processors these days. > Am I right? > > Best, > Rob > > > >> I have little doubt that a Pentium 4 would be much slower >> than the others. >> >> I've just bought an Intel Core 2 Duo E6600 primarily to run >> 64-bit Linux, but it also has Vista 64 and XP (32-bit) on it. >> I don't think the differences between the current dual-core >> chips are really enough to worry about: they will all look >> slow in less than a year. >> >> -- >> 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 > > ______________________________________________ > R-help@stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > -- 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 ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.