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High Performance Computing in R
Submitted by Ravishankar Rajagopalan (@vioravis) on Wednesday, 3 June 2015
This is a hands-on workshop focused on the high performance aspects of R programming. The attendees would get to learn how to identify the performance issues and address them through the use of various R packages. This workshop is targeted towards audience with a basic familiarity in R.
The following is the outline of the proposed workshop.
1.Understanding R’s slowness
2.Identifying bottlenecks through Profiling
3.Efficient coding practices for improving speed
4.Achieving speed through compiled codes (C++)
5.Overcoming memory limitations
6.Parallel Processing in R
The workshop will include a live demo on each of these topics followed by hands-on lab for the participants.
A basic level of programming familiarity with R.
The technology requirements along with a list of R packages to be installed would be provided a week before the workshop. The R scripts and the datasets would be uploaded to Github and shared with the participants.
Ravishankar Rajagopalan is Senior Principal Data Engineer in the Data Science Infrastructure (DSI) team at 7 Innovation Lab’s Data Sciences Group (DSG). As part of DSI, Ravi focusses on developing scalable analytics products. Prior to 7, he worked with GE Power and Water as part of advanced analytics team and with Mu Sigma.
Ravi has been using R for 10+ years and has conducted R trainings at 7, GE and Mu Sigma. He has also built analytics products through the use of R. He taught undergraduate/graduate level courses during his Ph.D. Ravi holds a Ph.D. in Applied Statistics from The Ohio State University.