From edd at debian.org  Tue Aug 24 14:27:24 2010
From: edd at debian.org (Dirk Eddelbuettel)
Date: Tue, 24 Aug 2010 07:27:24 -0500
Subject: [Rd] Speeding up matrix multiplies
In-Reply-To: <4C7370FE.30602@stat.umu.se>
References: <20100823233927.GA21529@cs.toronto.edu>
	<95C122CC-D17A-4007-ABDF-C77841E4000C@r-project.org>
	<20100824023958.GA10777@cs.toronto.edu>
	<AANLkTiktNDSMj+Rae+9VuazCGiuU9Hb4F-a1DPxGUW=x@mail.gmail.com>
	<4C7370FE.30602@stat.umu.se>
Message-ID: <19571.47788.483534.45503@max.nulle.part>


On 24 August 2010 at 09:13, G?ran Brostr?m wrote:
| 
| On 2010-08-24 05:37, Kasper Daniel Hansen wrote:
| > On Mon, Aug 23, 2010 at 10:39 PM, Radford Neal<radford at 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

 
| G?ran
| 
| >
| > 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 at r-project.org mailing list
| > https://stat.ethz.ch/mailman/listinfo/r-devel
| 
| ______________________________________________
| R-devel at r-project.org mailing list
| https://stat.ethz.ch/mailman/listinfo/r-devel

-- 
Dirk Eddelbuettel | edd at debian.org | http://dirk.eddelbuettel.com



[Rd] Speeding up matrix multiplies
Dirk Eddelbuettel