From dmbates at gmail.com  Tue Jan 24 15:38:46 2006
From: dmbates at gmail.com (Douglas Bates)
Date: Tue, 24 Jan 2006 08:38:46 -0600
Subject: [Rd] Master's project to coerce linux nvidia drivers to run
	generalised linear models
In-Reply-To: <971536df0601231409g17c34b74sbfc3e4828add2050@mail.gmail.com>
References: <43D53B85.4060109@bic.mni.mcgill.ca>
	<971536df0601231409g17c34b74sbfc3e4828add2050@mail.gmail.com>
Message-ID: <40e66e0b0601240638l1c539e9dqa5ccedc8334d6968@mail.gmail.com>

On 1/23/06, Gabor Grothendieck <ggrothendieck at gmail.com> wrote:
> I wonder if it would make more sense to get a relatively
> low level package to run on it so that all packages that
> used that low level package would benefit.  The Matrix
> package and the functions runmean and sum.exact in
> package caTools are some things that come to mind.
> Others may have other ideas along these lines.

Martin and I are delighted to learn that the Matrix package is a
"relatively low-level" package :-)

We were of the opinion that the amount of code and design work that
went into it made it a little more sophisticated than that.

More seriously, the approach to speeding up model fitting that has
been most successful to date is to speed up the BLAS (Basic Linear
Algebra Subroutines), especially the Level-3 BLAS.  The bulk of the
computation in the Matrix package takes place in either Lapack (for
dense matrices) or CHOLMOD (for sparse matrices) code and those are
based on calls to the Levels 1, 2 and 3 BLAS.  The Atlas package and
K. Goto's BLAS are designed to obtain the highest level of performance
possible from the CPU on these routines.  I think the easiest way of
incorporating the power of the GPU into the model fitting process
would be to port the BLAS to the GPU.  I also imagine that someone
somewhere has already started on that.

>
> On 1/23/06, Oliver LYTTELTON <oliver at bic.mni.mcgill.ca> wrote:
> >
> >
> > Hi,
> >
> > I am working with a friend on a master's project. Our laboratory does a
> > lot of statistical analysis using the R stats package and we also have a
> > lot of under-utilised nvidia cards sitting in the back of our networked
> > linux machines. Our idea is to coerce the linux nvidia driver to run
> > some of our statistical analysis for us. Our first thought was to
> > specifically code up a version of glm() to run on the nvidia cards...
> >
> > Thinking that this might be of use to the broader community we thought
> > we might ask for feedback before starting?
> >
> > Any ideas...
> >
> > Thanks,
> >
> > Olly
> >
> > ______________________________________________
> > 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
>



[Rd] Master's project to coerce linux nvidia drivers to run generalised linear models
Douglas Bates