[gdal-dev] CUDA PyCUDA and GDAL

[Seth Price]

I've been intending for a while to work on either CUDA or OpenCL with GDAL
& GRASS. I applied to do this for the Google Summer of  Code, but wasn't
accepted this past summer. I'll probably work on it someday just to make
sure my thesis work gets finished within budget.

However, I'm mostly interested in speeding up the resampling routines.
They should be able to get close to the theoretical maximum on CUDA. I
don't know about the routines which you mention without looking closer at
the code. For example, image reading is probably limited by the disk
speed, so it wouldn't be faster in CUDA. Translates are another operation
which doesn't involve much CPU time compared to disk time, so it would
also be difficult to speed it with CUDA. For these operations your best
option might be to replace your hard drive with a SSD.

I'm not familiar with image mosaics in GDAL, but I would guess that they
are heavy on the resampling when generating a quality final image. This is
something where each output pixel depends on the nearest ~16 input pixels.
It takes a lot of CPU time to process all those pixels, and it would
benefit from CUDA.

If you want, I could hunt down my GSoC application which would go into a
bit more detail.
~Seth

On Wed, November 18, 2009 2:46 pm, Shaun Kolomeitz wrote:
> I've heard a lot about the power of NVidia CUDA and am curious about
> ways in which we could leverage off this to increase the performance of
> 1) Image Mosaics 2) Translates and 3) Image Reading/rendering
> (especially highly compressed images).
> I also see that there is pyCUDA as well. Both of which I am unsure how
> (or if) you could use them to run (even portions of) GDAL ?
>
> If anyone has any pointers it would be nice to know.
>
> Many thanks,
> Shaun Kolomeitz
> Principal Project Officer
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