dear r-experts:
I need to speed up my monte-carlo simulations. my code is written in R (and
it was also the cause of my many questions here over the last few days). my
code is almost all matrix/vector algebra on panel data
sets---long-difference, fixed-effects, blundell-bond, etc.. the data set is
about 10MB, so 1GB per CPU core should be plenty for my operations, and
with $10/GB of DRAM, this is no longer a bottleneck. For my application,
parallelism is a given, since most of it is monte-carlo simulations. (I
guess the diametrically opposite need would be when one cannot parallelize,
in which case the recommendations would be quite different.)
My operating system will probably be ubuntu. (I also run a little of it on
an OSX Mac Pro I own.)
I want to use an Intel/AMD system with a prebuilt R executable. I do not
want to fiddle (too much) with building R myself, unless it is real easy
and makes a real speed difference. I wish I could ask R to load something
exotic like CUDA, but I presume that this is not yet ready for prime-time.
PS3 is probably silly, too. in fact, if I am not mistaken (and I may well
be), R pre-built does not even take advantage of SSE3 out-of-the-box.
software-wise, is there anything unusual that I should heed, or should I
just pick of R 2.8.1 from the CRAN archives and be done with it?
now, I also have to make some simple hardware decisions. Right now, a
dual-socket quad-core AMD opteron shanghai 2.3GHz system seems cheap.
$174/CPU + $70/motherboard. is there a system that dominates this in terms
of $/MFlops? (I presume the fact that core i7 has threads is irrelevant to
R.) I am not trying to ignite a flame-war---in fact, I don't care about any
other features that AMD or Intel or anything might have for this particular
computer. Other needs may warrant different choices.
Any other thoughts would be appreciated. Although you can just email them
to me, I presume that this question has enough interest to others that
posting it is ok.
regards,
/ivo welch
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