Writing parallel R code can be difficult, particularly for code that is not "embarrassingly parallel". This experimental package automates the transformation of serial R code into more efficient parallel versions. It identifies task parallelism by statically analyzing entire scripts to detect dependencies between statements. It implements an extensible system for scheduling and generating new code. It includes a reference implementation of the 'List Scheduling' approach to the general task scheduling problem of scheduling statements on multiple processors.
|Maintainer||Clark Fitzgerald <firstname.lastname@example.org>|
|License||MIT + file LICENSE|
|Package repository||View on GitHub|
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