R on 64-bit Linux machine
Peter Dalgaard <p.dalgaard at biostat.ku.dk> writes:
Prof Brian Ripley <ripley at stats.ox.ac.uk> writes:
ATLAS, you need to build shared ATLAS libraries (rather than static). This requires some modifications to the configuation files for ATLAS. But my experience shows that R itself builds out of the box on these systems.
However, you will almost certainly get better performance out of the Goto BLAS implementations, and they are shared (and easy to use, much more so than ATLAS).
I actually have different experience in the multithreaded case, at least with my favourite "benchmark suite": inversion of a large matrix. I'd do some timings, but I have this ATLAS compile running just now...
Specifically, here's what I got: pd at linux:~/r-devel> echo 'set.seed(1);M<-matrix(rnorm(9e6),3e3);system.time(solve(M))' | BUILD/bin/R -q --vanilla
set.seed(1);M<-matrix(rnorm(9e6),3e3);system.time(solve(M))
[1] 218.00 1.27 219.62 0.00 0.00
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 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).
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