[R] CPU Usage with R 2.1.0 in Windows
davidr at rhotrading.com
Wed Jul 20 16:05:52 CEST 2005
If you set the affinity of the R process to processor 0, you can run another (R or other) process with affinity set to processor 1 and get 100% usage.
Most applications can't take advantage of hyperthreading (or multiprocessors), since they have to be specially written to do so.
It seems that parts of Windows are single threaded, though, so, for example, starting up another instance of Excel when one is already using all of a 'processor' can take a very long time, but if the processes are already started, you can take advantage of the gross parallelism.
David L. Reiner
> -----Original Message-----
> From: r-help-bounces at stat.math.ethz.ch [mailto:r-help-
> bounces at stat.math.ethz.ch] On Behalf Of Prof Brian Ripley
> Sent: Wednesday, July 20, 2005 3:12 AM
> To: Lukasz Komsta
> Cc: Greene, Michael; 'R-help at lists.R-project.org'
> Subject: Re: [R] CPU Usage with R 2.1.0 in Windows
> It probably is not a problem to leave hyperthreading on: we found little
> performance difference on a P4 either way.
> The Windows task manager is misleading, as `50%' is about as much as a
> P4-class processor with hyperthreading can actually deliver.
> On Tue, 19 Jul 2005, Lukasz Komsta wrote:
> > Dnia 2005-07-19 20:28, Uÿÿytkownik Greene, Michael napisaÿÿ:
> >> Hi,> > I'm using a fairly simple HP Compaq desktop PC running Windows
> 2K. When> running a large process in R, the process "RGUI.exe" will never
> exceed 50%> of the CPU usage.
> > If you have hyperthreading, R catches only one virtual processor
> (fromtwo available), being not able to exceed half of total power (100%
> ofone only). If you want to use full power, you should turn
> hyperthreadingoff, if your BIOS supports such option.
> > Regards,
> > -- Lukasz KomstaDepartment of Medicinal ChemistryMedical University of
> Lublin6 Chodzki, 20-093 Lublin, PolandFax +48 81 7425165
> > ______________________________________________R-help at stat.math.ethz.ch
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> Brian D. Ripley, ripley at stats.ox.ac.uk
> Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
> University of Oxford, Tel: +44 1865 272861 (self)
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