[R] Mathematica now working with Nvidia GPUs --> any plan for R?
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. However, substantial
acceleration can also be obtained by not compiling the programs but
instead transferring them to the GPU and interpreting them there.
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!
> 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,
> 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)
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