On Sat, 13 Nov 2004, Peter Dalgaard wrote:
Peter Dalgaard <[EMAIL PROTECTED]> writes:
Prof Brian Ripley <[EMAIL PROTECTED]> 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:
[EMAIL PROTECTED]:~/r-devel> echo 'set.seed(1);M<-matrix(rnorm(9e6),3e3);system.time(solve(M))' | BUILD/bin/R -q --vanillaset.seed(1);M<-matrix(rnorm(9e6),3e3);system.time(solve(M))[1] 218.00 1.27 219.62 0.00 0.00[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.
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?
I have never built a threaded ATLAS for that machine, as in our environment people are normally running multiple jobs and it is total CPU time that counts.
-- Brian D. Ripley, [EMAIL PROTECTED] Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UK Fax: +44 1865 272595
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