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).