- Simple Parallel Statistical Computing in R
- Download the Paper Forward to a colleague
- 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