if I look at your output, the single thread is using almost 100% of
the two cpus (3:49 real, 5:49 user or something close to that). for
the two thread case it is close to the same with the user now
something like 6:15. I would like to see what the contribution of
each of the processes are. put some proc. time calls in the R script
to see what it is using.
Sent from my iPhone
On Sep 5, 2009, at 7:21, Peter Juhasz <peter.juhas...@gmail.com> wrote:
Dear R experts,
please excuse me for writing to the mailing list without subscribing.
I have a somewhat urgent problem that relates to R.
I have to process large amounts of data with R - I'm in an
international collaboration and the data processing protocol is fixed,
that is a specific set of R commands has to be used.
I wrote a perl program that manages creation of data subsets from my
database and feeds these subsets to an R process via pipes.
This worked all right, however, I wanted to speed things up by
exploiting the fact that I have a dual-core machine. So I rewrote my
perl driver program to use two threads, each starting its own R
instance, getting data off a queue and feeding it to its R process.
This also worked, except that I noticed something very peculiar: the
processing time was almost exactly the same for both cases. I did some
tests to look at this, and it seems that R needs twice the time to do
the exact same thing if there are two instances of it running.
I don't understand how is this possible. Maybe there is an issue of
thread-safety with the R backend, meaning that the two R *interpreter*
instances are talking to the same backend that's capable of processing
only one thing at a time?
Technical details: OS was Ubuntu 9.04 running on a Core2Dou E7300, and
the R version used was the default one from the Ubuntu repository.
Please see http://www.perlmonks.org/?node_id=792460 for an extended
discussion of the problem, and especially
http://www.perlmonks.org/?node_id=793506 for excerpts of output and
actual code.
Thanks for your answers in advance:
Péter Juhász
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and provide commented, minimal, self-contained, reproducible code.