Hi Brian,
Well, good question. It sounds like we are approaching critical mass;
and certainly, I think we are justified in attempting to learn the
fastest and best way to approach fast-computation with limited memory
bandwidth. To that end, I'm thinking about a couple things --
1. Separating our arrays into two chunks; fast and slow. We already
have a namespace for array generation -- this would suggest that we
can write an abstraction module that will help us to separate arrays
that need to be long lived and *fast* from arrays that are okay to be
slow (only a few operations) and that will be short-lived.
2. Moving projections and other heavy, already C-based, operations
onto the GPU. Or at least, duplicating our procedures in both. The
advantage of doing projections on the GPU happen to be that, in
theory, we should become completely IO limited. The projections are
already integer based; furthermore, 32-bit integers gets us
surprisingly far. The lightcone, for instance, can be fully addressed
in GPU-space.
3. Ray-tracing and post-processing rad transfer, even optically thin.
Right now, field generation can take some time -- but by constructing
special (for instance) X-ray fields, we can move 100% of the
computation onto the GPU and speed it up substantially, so that again
the projection is the dominant portion of the computation, rather than
the interpolation.
I've spoken with Sam Skillman and a couple other people, and this idea
seems to get them a bit jazzed up, so perhaps it's something worth
exploring, particularly as Lincoln is coming online (or already is?)
and can be used as a deployment and runtime platform.
-Matt
On Thu, Jul 16, 2009 at 10:07 AM, Brian O'Shea
Hi Matt,
1. <hand up> 2. <hand up>
Additionally, several nodes of Spur (the viz machine at TACC) have Nvidia GPU boards and NCSA's Tesla system has several as well. Those ought to be able to use PyCUDA.
What's on your mind, Matt?
--Brian
On Thu, Jul 16, 2009 at 9:55 AM, Matthew Turk
wrote: Hi guys,
Can I get a show-of-hands --
1. How many of you have access to GPUs that support CUDA?
2. How many of you have installed or CAN install PyCUDA?
Thanks!
-Matt _______________________________________________ Yt-dev mailing list Yt-dev@lists.spacepope.org http://lists.spacepope.org/listinfo.cgi/yt-dev-spacepope.org
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