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High Performance Computing with R

  • 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.

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  • jake

    a good meetup.

    seems that there was interest in asking/answering R-related questions (e.g. david's question of a vectorized solution for finding a run of consecutive numbers in a list).

    perhaps people would be interested in leaving 15 minutes open for questions/brain teasers/etc, as a forum for q&a?

    May 15, 2009

  • Andy L.

    Thanks to Josh and Drew for organizing this. The talks are informative.

    May 15, 2009

  • A former member
    A former member

    As someone with no knowledge of parallel computing in R prior to the meeting, I felt it was immensely helpful. I am inspired to go out and try to introduce this to my company!

    May 15, 2009

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