Simple Parallel Statistical Computing in R
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Abstract:
Theoretically, many modern statistical procedures are trivial to parallelize. However, practical deployment of a parallelized implementation which is robust and reliably runs on different computational cluster configurations and environments is far from trivial. We present a framework for the R statistical computing language that provides a simple yet powerful programming interface to a computational cluster. This interface allows the development of R functions that distribute independent computations across the nodes of the computational cluster. The resulting framework allows statisticians to obtain significant speed-ups for some computations at little additional development cost. The particular implementation can be deployed in heterogeneous computing environments.
Subject Area:
Computational Biology/Bioinformatics, Computation
Suggested Citation:
Anthony Rossini, Luke Tierney, and Na Li, "Simple Parallel Statistical Computing in R" (March 5, 2003). UW Biostatistics Working Paper Series. Working Paper 193.
http://www.bepress.com/uwbiostat/paper193