Prof Brian Ripley <[EMAIL PROTECTED]> writes: > > [EMAIL PROTECTED]:~/r-devel> echo > > 'set.seed(1);M<-matrix(rnorm(9e6),3e3);system.time(solve(M))' | > > BUILD-GOTO/bin/R -q --vanilla > >> set.seed(1);M<-matrix(rnorm(9e6),3e3);system.time(solve(M)) > > [1] 29.12 1.39 32.21 0.00 0.00 > >> > > [EMAIL PROTECTED]:~/r-devel> echo > > 'set.seed(1);M<-matrix(rnorm(9e6),3e3);system.time(solve(M))' | > > BUILD-ATLAS/bin/R -q --vanilla > >> set.seed(1);M<-matrix(rnorm(9e6),3e3);system.time(solve(M)) > > [1] 3.24 1.31 21.45 31.75 0.24 > >> > > > > So ATLAS is faster than GOTO by about 10 seconds. It is a bit odd that > > Not on total CPU time (it's slower by about the margin I would > expect), only on elapsed time.
True, but there's always a penalty on multithreading nontrivial code, so to minimize total time, use only one CPU... > > the GOTO timings don't seem to include any subprocess time but it > > should be the threaded library libgoto_opt64p-r0.93.so (I know; > > there's a 0.96 now, will upgrade). > > I get (on a dual Opteron 248 with 0.96-2) > > [1] 20.59 1.01 19.10 0.00 0.00 > > which note is using more than 100% CPU time. Are you sure you are using > multiple threads with Goto? Fairly sure... I got (dual Opteron 240, now also 0.96-2) [1] 29.21 1.50 30.97 0.00 0.00 so less than 100% but the timing ratio seems fairly consistent with the clock speeds (1.4 GHz vs. 2.2 GHz). -- O__ ---- Peter Dalgaard Blegdamsvej 3 c/ /'_ --- Dept. of Biostatistics 2200 Cph. N (*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918 ~~~~~~~~~~ - ([EMAIL PROTECTED]) FAX: (+45) 35327907 ______________________________________________ [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
