ParallelR speed enhancement under Windows OS

[Paolo Cavatore]

Why should I use ParallelR when RRO is already leveraging the multi-core processing? Would I still get relevant speed increase by using ParallelR over RRO under Windows OS?

[David Smith]

Only certain R functions take advantage of the multi-core capabilities of multi-threaded libraries. Using ParallelR is a way to take advantage of multiple cores for everything else (as long as you can express the problem as a loop). The "birthday" example from the webinar today is a good example: even though it was running on RRO, you still got a performance improvement by running the loop through foreach/doMC.

(If you missed the webinar, the replay will be available soon from: http://www.revolutionanalytics.com/webinars/introducing-revolution-r-open-enhanced-open-source-r-distribution-revolution-analytics )

# David Smith

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David M Smith <da...@revolutionanalytics.com>
Chief Community Officer, Revolution Analytics  http://blog.revolutionanalytics.com
Tel: +1 (650) 646-9523 (Chicago IL, USA)

Twitter: @revodavid

On Wed, Nov 12, 2014 at 4:34 PM, Paolo Cavatore <pcav...@gmail.com> wrote:

Why should I use ParallelR when RRO is already leveraging the multi-core processing? Would I still get relevant speed increase by using ParallelR over RRO under Windows OS?

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