May 14, 2009 · 7:00 PM
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Many people use R as a desktop application, limited to the resources of the machine on which it runs. For datasets larger than RAM, or for computationally intensive operations this can be quite limiting. There are a number of approaches used to break through the barriers imposed by running R on a single machine. The High Performance Computing view on CRAN provides an overview of some of these techniques: http://cran.r-project...
- Shane Conway - Best practices for efficient code in R
- John Myles White - Using R in a clustered environment with SNOW / Rmpi
- David Rosenberg - HadoopStreaming package
- Steve Weston - REvolution Computing's foreach and iterator optimized code.