R on 64-bit Linux machine
Prof Brian Ripley <ripley at stats.ox.ac.uk> writes:
pd at linux:~/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
pd at linux:~/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 ~~~~~~~~~~ - (p.dalgaard at biostat.ku.dk) FAX: (+45) 35327907