a) Base R already includes the "parallel" package. Deciding to use more than
one processor for a particular computation is a very high level decision that
can require knowledge of computing time cost, importance of other tasks on the
system, and interdependence of computation results. It is not a decision that R
should automatically make.
b) Most performance issues with R arise due to users choosing inefficient
algorithms. Inserting parallelism inside existing algorithms will not fix that.
---------------------------------------------------------------------------
Jeff Newmiller The ..... ..... Go Live...
DCN:<jdnew...@dcn.davis.ca.us> Basics: ##.#. ##.#. Live Go...
Live: OO#.. Dead: OO#.. Playing
Research Engineer (Solar/Batteries O.O#. #.O#. with
/Software/Embedded Controllers) .OO#. .OO#. rocks...1k
---------------------------------------------------------------------------
Sent from my phone. Please excuse my brevity.
On May 27, 2015 8:00:03 AM PDT, Suman <suman12...@yahoo.co.uk> wrote:
>Hi there,
>
>Now that R has grown up with a vibrant community. It's no 1 statistical
>package used by scientists. It's graphics capabilities are amazing.
>Now it's time to provide native support in "R core" for distributed and
>parallel computing for high performance in massive datasets.
>And may be base R functions should be replaced with best R packages
>like data.table, dplyr, reader for fast and efficient operations.
>
>
>Thanks
>
>Sent from my iPad
>______________________________________________
>R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
>https://stat.ethz.ch/mailman/listinfo/r-help
>PLEASE do read the posting guide
>http://www.R-project.org/posting-guide.html
>and provide commented, minimal, self-contained, reproducible code.
______________________________________________
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
