Regarding (2), I wonder if this information is too outdated or not relevant when scaled up to larger problems...
http://www.sciviews.org/benchmark/index.html --- Ramon Diaz-Uriarte <[EMAIL PROTECTED]> wrote: > Dear Lorenzo, > > I'll try not to repeat what other have answered before. > > On 4/5/07, Lorenzo Isella <[EMAIL PROTECTED]> wrote: > > The institute I work for is organizing an internal workshop for High > > Performance Computing (HPC). > (...) > > > (1)Institutions (not only academia) using R > > You can count my institution too. Several groups. (I can provide more > details off-list if you want). > > > (2)Hardware requirements, possibly benchmarks > > (3)R & clusters, R & multiple CPU machines, R performance on different > hardware. > > We do use R in commodity off-the shelf clusters; our two clusters are > running Debian GNU/Linux; both 32-bit machines ---Xeons--- and 64-bit > machines ---dual-core AMD Opterons. We use parallelization quite a > bit, with MPI (via Rmpi and papply packages mainly). One convenient > feature is that (once the lam universe is up and running) whether we > are using the 4 cores in a single box, or the max available 120, is > completeley transparent. Using R and MPI is, really, a piece of cake. > That said, there are things that I miss; in particular, oftentimes I > wish R were Erlang or Oz because of the straightforward fault-tolerant > distributed computing and the built-in abstractions for distribution > and concurrency. The issue of multithreading has come up several times > in this list and is something that some people miss. > > I am not sure how much R is used in the usual HPC realms. It is my > understanding that the "traditional HPC" is still dominated by things > such as HPF, and C with MPI, OpenMP, or UPC or Cilk. The usual answer > to "but R is too slow" is "but you can write Fortran or C code for the > bottlenecks and call it from R". I guess you could use, say, UPC in > that C that is linked to R, but I have no experience. And I think this > code can become a pain to write and maintain (specially if you want to > play around with what you try to parallelize, etc). My feeling (based > on no information or documentation whatsoever) is that how far R can > be stretched or extended into HPC is still an open question. > > > > (4)finally, a list of the advantages for using R over commercial > > statistical packages. The money-saving in itself is not a reason good > > enough and some people are scared by the lack of professional support, > > though this mailing list is simply wonderful. > > > > (In addition to all the already mentioned answers) > Complete source code availability. Being able to look at the C source > code for a few things has been invaluable for me. > And, of course, and extremely active, responsive, and vibrant > community that, among other things, has contributed packages and code > for an incredible range of problems. > > > Best, > > R. > > P.S. I'd be interested in hearing about the responses you get to your > presentation. > > > > Kind Regards > > > > Lorenzo Isella > > > > ______________________________________________ > > [email protected] mailing list > > 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. > > > > > -- > Ramon Diaz-Uriarte > Statistical Computing Team > Structural Biology and Biocomputing Programme > Spanish National Cancer Centre (CNIO) > http://ligarto.org/rdiaz > > ______________________________________________ > [email protected] mailing list > 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. > ____________________________________________________________________________________ TV dinner still cooling? ______________________________________________ [email protected] mailing list 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.
