Distributed computing
My inclination would be to, whenever possible, replace the core scalar libraries with compatible parallel versions (lapack -> scalapack), rather than make it an add-on package. If the R client code is general enough, and the make file can automatically find the parallel version, then its a simple matter of compiling with the parallel libs. (Don't know if this is possible at run-time.) No rewriting (high level) R code at all. I tried to contact the plapack folks here at UT about integrating with R, but it appears the project is no longer active. Tim
On Tue, 2004-03-23 at 13:32, A.J. Rossini wrote:
gte810u@mail.gatech.edu writes:
does anyone know if there exists an effort to bring some kind of distributed computing to R? The most simple functionality I'm after is to be able to explicitly perform a task on a computing server. Sorry if this is a non-informed newbie question...
As an alternate to the PVM/MPI interfaces mentioned by other people, I am working on a (very soon to be released) project for using the ScaLAPACK library [1] through a simple R interface. If the tasks that you want run an a computing server are simple (LAPACK) functions (solve, svd, etc) and not whole R scripts, then this be useful.
A number of folks have commented on having this in progress (esp a group at Vanderbilt). It's intriguing, but how did you plan on replacing the standard system-level library calls? (or did you just provide new interfaces at the user (R command) level?) best, -tony
Timothy H. Keitt Section of Integrative Biology University of Texas at Austin http://www.keittlab.org/