From ral64 at cam.ac.uk  Wed May 18 14:27:15 2011
From: ral64 at cam.ac.uk (Robert Lowe)
Date: Wed, 18 May 2011 13:27:15 +0100
Subject: [Rd] Max likelihood using GPU
In-Reply-To: <1305709643520-3532034.post@n4.nabble.com>
References: <1305709643520-3532034.post@n4.nabble.com>
Message-ID: <3AE5646A-FF55-405F-A5AC-E2EECDC80C0A@cam.ac.uk>

Hi Oyvind,

I believe this is possible to implement. There is already some work ongoing in using the GPU in R and they use the CUDA toolkit as the reference you supplied do.

http://brainarray.mbni.med.umich.edu/Brainarray/rgpgpu/

Thanks,
Rob


On 18 May 2011, at 10:07, oyvfos wrote:

> Dear all,
> Probably many of you experience long computation times when estimating large
> number of parameters using maximum likelihood  with functions that reguire
> numerical methods such as integration or root-finding. Maximum likelihood is
> an example of paralellization that could sucessfully utilize GPU. The
> general algorithm is described here:
> http://openlab-mu-internal.web.cern.ch/openlab-mu-internal/03_Documents/4_Presentations/Slides/2010-list/CHEP-Maximum-likelihood-fits-on-GPUs.pdf.
> Is it possible to implement this algorithm in R ? 
> Kind regards, Oyvind Foshaug
> 
> --
> View this message in context: http://r.789695.n4.nabble.com/Max-likelihood-using-GPU-tp3532034p3532034.html
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> 
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[Rd] Max likelihood using GPU
Robert Lowe