That's our guess too. We're running some tests now on the code to see what's going on, and it's entirely possible the performance gains are a function of the problem size, so we're testing that too. Changes in R between 2.7.2 (upon which REvolution R is currently based) and 2.9.0 are also a confounding factor. (I'm assuming the timings reported were on 2.9, not 1.9 as stated.) I'll report back here when I have more details.
# David Smith On Tue, Apr 21, 2009 at 10:32 AM, Bert Gunter <gunter.ber...@gene.com> wrote: > A guess: Depends on the problem, the hardware, the matrix libraries,... > > e.g. in relatively small problems, Revolution's overhead may consume more > time and resources than the problem warrants. In others, you may see many > fold improvements. Very dangerous to generalize from an example or two (as I > recently experienced to my own chagrin). -- David M Smith <da...@revolution-computing.com> Director of Community, REvolution Computing www.revolution-computing.com Tel: +1 (206) 577-4778 x3203 (San Francisco, USA) Check out our upcoming events schedule at www.revolution-computing.com/events ______________________________________________ R-help@r-project.org 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.
