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

From: Mose <>
Date: Tue, 18 Nov 2008 23:25:48 -0800

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 programs."

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 <> 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,
>> Emmanuel
> PS: R-devel is the list on which to discuss the development of R.
> --
> Brian D. Ripley,
> Professor of Applied Statistics,
> University of Oxford, Tel: +44 1865 272861 (self)
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> mailing list PLEASE do read the posting guide and provide commented, minimal, self-contained, reproducible code. Received on Wed 19 Nov 2008 - 07:33:37 GMT

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