I am not up on the internals of R but there does seem some run for
parallelism. Are we talking about special hardware? or running this on
an Intel Box? If it is the second, then I am thinking threads would be
the way to go. Please consider the following
R statements:
for( i in 1:30 ) a[i] = f1(i)
Would it make sense to setup a separate thread for each call to f1? I
think it in most cases, the answer is no but on some machines and
depending on the running time of f1, it could be a big win. Also, does
the user have to change his code, or would R be
smart enough to do the work behind the scenes. I consider the second to
be significantly better than the first.
You may also want to look at the following URL
http://stackoverflow.com/questions/1395309/how-to-make-r-use-all-processors
Bob
On 3/27/2016 11:52 AM, PSATHAS NILOS-HRISTOS wrote:
Hello,
i am an undergraduate student on computer engineering and im
considering to do my thesis to an open source project and make
performance optimizations and/or add parallelism to it where possible
(or even better make use of GPU). Do you think that R-project is a
good candidate?
Thanks,
Psathas Neilos
______________________________________________
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.