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QA: How do Revolution R Enterprise and RevoScaleR use multiple CPUs?

R is not inherently a multi-threaded application, so in normal circumstances it only uses one processor at a time. 

There are several options for parallel programming that provide value: 

1. Revolution R Enterprise will use all available processors for some common math operations, like matrix multiplication. (It is linked with multi-threaded math libraries which improve performance on multi-core Intel processors.) 

2. The RevoScaleR package, shipped with Revolution R Enterprise, offers parallel external memory algorithms and a very efficient data file format (.xdf). 

3. You can also write explicit parallel code using ParallelR. See CRAN Task View: High-Performance and Parallel Computing with R for a list of options: 

http://cran.r-project.org/web/views/HighPerformanceComputing.html 

4. The RevoScaleR package included with Revolution R Enterprise provides new tools for parallel and distributed computing with R that can scale out.   
Note This is a "FAST PUBLISH" article created directly from within the Microsoft support organization. The information contained herein is provided as-is in response to emerging issues. As a result of the speed in making it available, the materials may include typographical errors and may be revised at any time without notice. See Terms of Use for other considerations.
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Article ID: 3104264 - Last Review: 10/29/2015 08:21:00 - Revision: 1.0

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