Riccardo Porreca
2019-May-06 09:42 UTC
[R] [R-pkgs] rTRNG: Advanced and Parallel Random Number Generation via TRNG
We are happy to announce the first CRAN release of rTRNG version 4.20-1. rTRNG is a package for advanced parallel Random Number Generation in R. It relies on TRNG (Tina?s Random Number Generator, <https://numbercrunch.de/trng/>), a state-of-the-art C++ pseudo-random number generator library for sequential and parallel Monte Carlo simulations. In particular, parallel random number generators provided by TRNG can be manipulated by jump and split operations. These allow to jump ahead by an arbitrary number of steps and to split a sequence into any desired sub-sequence(s), thus enabling techniques suitable to parallel algorithms, such as block-splitting and leapfrogging. The package provides the R user with access to the functionality of the underlying TRNG C++ library. It embeds TRNG sources and headers and makes them available to other projects combining R with C++. Beyond this, rTRNG exposes the creation, manipulation and use of pseudo-random streams to R, via Rcpp and RcppParallel. rTRNG on CRAN <https://cran.r-project.org/package=rTRNG> Public repository <https://github.com/miraisolutions/rTRNG#readme> More on the history behind rTRNG and its way to CRAN at <https://mirai-solutions.ch/news/2019/05/04/rTRNG-on-CRAN/> -- Riccardo Porreca Senior Solutions Consultant Mirai Solutions GmbH riccardo.porreca at mirai-solutions.com _______________________________________________ R-packages mailing list R-packages at r-project.org https://stat.ethz.ch/mailman/listinfo/r-packages