[R] Mathematica now working with Nvidia GPUs --> any plan for R?

Mose mose.andre at gmail.com
Wed Nov 19 08:25:48 CET 2008

GPU architecture is different enough from CPU architecture that you
don't need 10s of GPUs to see a performance benefit over today's, say,
8 core CPUs.  Lots of GPUs now give you a (relatively cheap)
"supercomputer" -- look up nVidia's Tesla marketing mumbo jumbo.  One
GPU still gives you a 'heckuva job'.

>From Wikipedia's GPU page, speaking on modern general purpose GPUs:


"Typically the performance advantage is only obtained by running the
single active program simultaneously on many example problems in
parallel using the GPU's SIMD architecture[11]. However, substantial
acceleration can also be obtained by not compiling the programs but
instead transferring them to the GPU and interpreting them there[12].
Acceleration can then be obtained by either interpreting multiple
programs simultaneously, simultaneously running multiple example
problems, or combinations of both. A modern GPU (e.g. 8800 GTX) can
readily simultaneously interpret hundreds of thousands of very small

The first sentence, you can imagine, applies to some a lot of matrix work.

There are BLAS libraries for some GPUs (e.g. CUDA BLAS).  You can
probably imagine having R use it.  Ahmed El Zein has a poster about
his presentation "Performance Evaluation of the NVIDIA GeForce 8800
GTX GPU for Machine Learning" that gives some more interesting info.


On Tue, Nov 18, 2008 at 10:56 PM, Prof Brian Ripley
<ripley at stats.ox.ac.uk> wrote:
> On Tue, 18 Nov 2008, Emmanuel Levy wrote:
>> Dear All,
>> I just read an announcement saying that Mathematica is launching a
>> version working with Nvidia GPUs. It is claimed that it'd make it
>> ~10-100x faster!
>> http://www.physorg.com/news146247669.html
> Well, lots of things are 'claimed' in marketing (and Wolfram is not shy to
> claim).  I think that you need lots of GPUs, as well as the right problem.
>> I was wondering if you are aware of any development going into this
>> direction with R?
> It seems so, as users have asked about using CUDA in R packages.
> Parallelization is not at all easy, but there is work on making R better
> able to use multi-core CPUs, which are expected to become far more common
> that tens of GPUs.
>> Thanks for sharing your thoughts,
>> Best wishes,
>> Emmanuel
> PS: R-devel is the list on which to discuss the development of R.
> --
> Brian D. Ripley,                  ripley at stats.ox.ac.uk
> Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
> University of Oxford,             Tel:  +44 1865 272861 (self)
> 1 South Parks Road,                     +44 1865 272866 (PA)
> Oxford OX1 3TG, UK                Fax:  +44 1865 272595
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