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Workshop on Distributed Computing in R

Guest_Blogger

icon_1068_1063.pngR is used by millions of data scientists. In the near future, these data scientists will have to rely on distributed computing to meet the computational demands of Big Data. Wouldn’t it be helpful if R provides simple ways to harness the power of multiple servers?

 

HP is hosting an R workshop January 26-27, 2015 where R users will brainstorm on this topic. The workshop is being organized by Indrajit Roy, Principal Researcher at HP Labs, and Michael Lawrence, R-core member at Genentech. A number of well-known R contributors, including members affiliated with universities, national labs, and the industry, are going to present their views at the workshop.

 

Here is a summary of the workshop goals, as stated on the workshop’s web page:

 

“As data sizes increase, so does the need to provide R users with tools to efficiently analyze large datasets. The goal of this workshop is to standardize the API for exposing distributed computing in R, learn from the experiences of attendees in using R for large scale analysis, and collaborate in open source. We want to encourage R contributors (including students) to implement parallel versions of their favorite algorithms. By standardizing the infrastructure for distributed computing, we will be able to increase the availability of parallel algorithms in R, and ensure that R is an appealing choice even for analysis on really large data.”

Read more about the workshop and its agenda by clicking here.

 

Get involved if you are interested in R and Big Data!

 

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