On 24 August 2010 at 09:13, Göran Broström wrote: | | On 2010-08-24 05:37, Kasper Daniel Hansen wrote: | > On Mon, Aug 23, 2010 at 10:39 PM, Radford Neal<radf...@cs.toronto.edu> wrote: | >>> On Aug 23, 2010, at 7:39 PM, Radford Neal wrote: | >> | >>>> In particular, all matrix x vector and vector x matrix products will | >>>> in this version be done in the matprod routine, not the Fortran routine. | >>>> And this is the right thing to do, since the time for the ISNAN check | >>>> before calling the Fortan routine will be comparable to the time for | >>>> the matrix multiply. So avoiding it will be desirable unless the Fortran | >>>> routine is really, really faster than the C code in matprod. | >>> | >>> It is, many times in fact, if you use threaded BLAS on a multi-core machine | >>> and large matrices. | >> | >> Well, it can't get any faster than taking zero time. And even in that | >> case, using the C code in matprod will slow the program down (compared | >> to the existing version of R) by only about a factor of two. | >> | >>>> Of course, the real solution is to change the Fortran routine (which | >>>> seems to be in src/extra/blas/blas.f, and isn't all that complicated) | >>> | >>> Nope - it can be external and BLAS standard doesn't handle NAs. | >> | >> OK. I see the problem if people can link in their own version of BLAS. | >> I wonder if there is any way of telling whether they did that? Presumably | >> many people will use the BLAS routine supplied with R, which could be | >> made safe for NAs. | > | > Radford: this is highly platform dependent. For example, all OS X | > users use a multithreaded BLAS supplied by Apple. And I believe a | > multithreaded BLAS is used by Revolution R (all platforms). Allowing | > a plugin BLAS is (in my opinion) an essential advantage of R and is | > used by many people who care about high performance. | | How do I best achieve this on Ubuntu (10.04)?
i) General answer: See Appendix 3.1 of the R Admin + Inst manual. ii) More specific answer: On Ubuntu, you get the 'revolution-mkl' package which gets you the otherwise commercial Intel MKL for free. iii) Even more specific answer: You get Goto BLAS via the gotoblas2-helper package by Ei-ji Nakama who also detailed how to use it on a recent r-sig-hpc post. Hth, Dirk | Göran | | > | > Note that the BLAS version can be swapped after R has been compiled, | > so even if there is a way to tell what BLAS you are using (and I don't | > know if there is), it has to be a run-time check. | > | > Kasper | > | > ______________________________________________ | > R-devel@r-project.org mailing list | > https://stat.ethz.ch/mailman/listinfo/r-devel | | ______________________________________________ | R-devel@r-project.org mailing list | https://stat.ethz.ch/mailman/listinfo/r-devel -- Dirk Eddelbuettel | e...@debian.org | http://dirk.eddelbuettel.com ______________________________________________ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel