Parallelism (was Re: [R] Re: R-1.1.0 is released : GUI)
thomas at biostat.washington.edu
Mon Jun 19 19:33:05 CEST 2000
On 17 Jun 2000, Peter Dalgaard BSA wrote:
> There are many levels of parallelism, not all of which are equally
> easy to exploit. At the coarsest level, each machine does essentially
> its own thing in a separate process. This is very easy to implement
> and quite useful for e.g. simulations. For a somewhat more elaborate
> version of this there is the Condor project at Wisconsin which allows
> processes to be moved around between different CPUs - R has been tested
> on this but I don't know how far they've got.
For Linux there is also MOSIX, which works very nicely for load balancing
on a cluster of PCs. As most of my computationally intensive work is
simulation or bootstrapping it parallelises very nicely by doing eg 5 lots
of 200 runs rather than one lot of 1000.
> At the finest level there's a potential for very highly optimized
> algorithms for specific purposes like matrix inversion, sorting, and
> differential equation solving. Even though they have been known to be
> theoretically possible for ages, actual implementations seem to be
> slow in coming.
There are some sparse matrix implementations out there, which may be
linkable to R. I have used the single-processor version of the Aztec
sparse matrix library with R and I think it would be possible to use the
Assistant Professor, Biostatistics
University of Washington, Seattle
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