[R] About performance of R

[Jeff Newmiller]

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.
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Sent from my phone. Please excuse my brevity.

On May 27, 2015 8:00:03 AM PDT, Suman <suman12029 at 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
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