> In general no, these (and other R) functions are not parallelized. The usual
> strategy would be to write a script that operates on one file or other
> 'chunk' of data, and then use one of snow ('easiest'), multicore (best for
> multiple core on a linux computer), or Rmpi (computation distributed across
> clusters) to do a version of 'lapply' (e.g., mclapply, mpi.parLapply) that
> is distributed across cores / nodes.I'd just add that I think the foreach package w/ its various backends (eg. doMC for using multicore as its "parallelization strategy") is actually the easiest. But I guess that's a matter of taste :-) -steve -- Steve Lianoglou Graduate Student: Computational Systems Biology | Memorial Sloan-Kettering Cancer Center | Weill Medical College of Cornell University Contact Info: http://cbio.mskcc.org/~lianos/contact _______________________________________________ Bioc-sig-sequencing mailing list [email protected] https://stat.ethz.ch/mailman/listinfo/bioc-sig-sequencing
