Parallel Programming Tools for 'Rcpp'

High level functions for parallel programming with 'Rcpp'. For example, the 'parallelFor()' function can be used to convert the work of a standard serial "for" loop into a parallel one and the 'parallelReduce()' function can be used for accumulating aggregate or other values.


  • Add support for Rtools 3.3 w/ GCC 4.9
  • Add support for TBB on Solaris
  • Fix failure to compile on OS X Snow Leopard R toolchain
  • Add const and non-const operator[] for RMatrix class
  • Add tbbmalloc library
  • Correctly pass clang to TBB configure when R is using clang
  • Support for TBB on Windows
  • Update to TBB 4.3 (fixes clang compilation error in platform.h)
  • Forward CXX to TBB Makefile
  • Initial release

Reference manual

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4.3.20 by Kevin Ushey, 8 months ago,

Browse source code at

Authors: JJ Allaire [aut], Romain Francois [aut, cph], Kevin Ushey [aut, cre], Gregory Vandenbrouck [aut], Marcus Geelnard [aut, cph] (TinyThread library,, RStudio [cph], Intel [aut, cph] (Intel TBB library,, Microsoft [cph]

Documentation:   PDF Manual  

Task views: High-Performance and Parallel Computing with R

GPL-2 license

Suggests Rcpp, RUnit, knitr, rmarkdown

Linking to BH

System requirements: GNU make, Windows: cmd.exe and cscript.exe, Solaris: g++ is required

Imported by Cyclops, FLSSS, GERGM, MultiBD, SpatMCA, SpatPCA, dbmss, lamW, markovchain, microclass, patternplot, qualpalr, quanteda, rPref, roll, skm, text2vec.

Depended on by StMoSim, gaston.

See at CRAN