simple parallel computing on single multicore machine
On Friday 01 December 2006 13:23, Millo Giovanni wrote:
Dear List, the advent of multicore machines in the consumer segment makes me wonder whether it would, at least in principle, be possible to divide a computational task into more slave R processes running on the different cores of the same processor, more or less in the way package SNOW would do on a cluster. I am thinking of simple 'embarassingly parallel' problems, just like inverting 1000 matrices, estimating 1000 models or the like. I have seen some talk here on making R multi-threaded and the like, but this is much simpler. I am just a curious useR, so don't bother if you don't have time, but maybe you can point me at some resource, or just say "this is nonsense"...
Dear Millo, I find the usage of papply (from the library with the same name), which itself uses Rmpi to be easy and ideal for those cases. The papply documentation shows clearly what you need to do to pass the required arguments to papply. And once you have your MPI universe up and running (with whichever number of slaves you specify) it just works. As well, I find debugging very simple: just start an MPI universe with only one node, which forces papply to run serially (non-parallel) so wrong arguments, missing libraries, etc, are easy to spot. Best, R.
Cheers
Giovanni
Giovanni Millo
Research Dept.,
Assicurazioni Generali SpA
Via Machiavelli 4,
34131 Trieste (Italy)
tel. +39 040 671184
fax +39 040 671160
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