[R-sig-hpc] How to configure R to work with GPUs transparently

Norm Matloff matloff at cs.ucdavis.edu
Fri Mar 19 18:25:49 CET 2010

Though there is a lot of potential here, there are a lot of difficulties
as well.

For example, there is the issue of having R sense that one actually does
have a suitable GPU, and that CUDA (or OpenCL) is installed.  One could
have the innards of lm(), say, do this sensing, but it would mean a
significant delay.  As an alternative, this could be done when R starts
up, and then having R set some environment variable; I don't see
problems with this, but there could be some.

Next there are GPU configuration issues--numbers of rows and columns of
blocks, numbers of rows, columns and layers of threads per block, and so
on.  This would be highly dependent on which GPU device the user has,
the R function being called, and things like problem size (numbers of
observations and variables).

I think a big question is whether there is enough demand out there for
this to be done.  My own impression, possibly incorrect, is that the
vast majority of R users have little or no need for the power of GPUs.

By the way, if anyone is interested, I have an introduction to GPU
programming in my open-source textbook on parallel processing,


On Fri, Mar 19, 2010 at 11:55:01AM -0500, Spiers, Brad wrote:
> Hi,
>    I am trying to get R to work with an NVIDIA GPU transparently.  I
> know about gputools, but they require changing R scripts to include
> "gpu" before the relevant calls.  
>    According to the Cula Tools folks, R is actually a client of theirs,
> so there should be some way to get R to work with GPUs natively.  I
> seriously doubt that I am the first person to try this.  If someone has
> done this, could you please share how you have done so?  If you know
> that this does not work, could you please confirm?  Thanks.
> --Brad
> Bradford T. Spiers
> SVP; Sr. Architect
> Technology Innovation Portfolio
> Bank of America
> 222 Broadway, NYC, NY 10038, USA
> 	[[alternative HTML version deleted]]
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