[GRASS-dev] OpenCL Parallelization

Dylan Beaudette debeaudette at ucdavis.edu
Wed Sep 23 16:03:33 EDT 2009

On Wednesday 23 September 2009, Jeshua Lacock wrote:
> On Sep 15, 2009, at 7:52 AM, Jyothish Soman wrote:
> > Sorry to you all for not being active, I will love to help in this
> > effort. >From September 28 to december end, there is only GRASS
> > coding on the menu for me.
> >
> > Please do pass me any work in that time frame OPENCL or CUDA . I
> > will be happy to oblige.
> >
> > Also, I think there is scope for using GPU as a coprocessor and
> > splitting work between different processors on the same machine to
> > coexist.
> >
> > FYI, I am very much at ease with CUDA (NVidia GPU programming), than
> > any other form of parallelization methods. It is my field of research.
> Greetings,
> Here is a video of a rather impressive Manifold GIS CUDA demo
> performing a raster operation:
> http://www.manifold.net/video/nvidia_cuda_demo.wmv
> The operation is reduced from 60 seconds to 2 using 1 GPU - imagine if
> they had 4 GPUs! It would go from 60 seconds to nearly realtime....
> Best,

Interesting... But I wonder about a couple things. 

1. why would it take 60 seconds to compute a slope map from a 1400x1400 cell 

On a 3.2Ghz Xeon (5 year old machine), using a 2710x3306 cell raster, 
r.slope.aspect takes:

real    0m7.637s
user    0m6.984s
sys     0m0.508s

2. It looks like the map in the demo is Int16... Does CUDA-based math support 
double precision floating point calculations? Last time I checked it didn't. 

Other than those 2 points, I would love to see GPU-based acceleration in 

A thread from last year on this topic:

Hopefully things have improved since then!


Dylan Beaudette
Soil Resource Laboratory
University of California at Davis

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