My last post was way back in August and I'm writing this one really just to keep the blog alive, so to speak. So far I haven't been able to get GPULib 1.0 going on my system, so I have no idea if the programs on my website will still run under 1.0. I'm getting help from Tech-X and haven't given up hope.
Anyway, I'm very keen to apply CUDA (via GPULib) to the kind of nonlinear algorithms (kernel methods) I've described previously. These algorithms involve two steps: training and generalization. In remote sensing applications, the training data set can be kept fairly small (order 10^3), but generalization invariably means processing all the pixel vectors in an image, typically of the order 10^6-10^8. Since generalization can be safely done in single precision and involves manipulation of large matrices, it is a natural task for the GPU.
Friday, 12 December 2008
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2 comments:
I hope your problems have been resolved with the 1.0.6 release.
Please make sure that you're using the correct version of CUDA and the right drivers. (and we will try to be specific which drivers to use for the pre-built libraries)
Peter
Indeed they have, Peter. GPULib is now up and running again. My next objective is to learn the new function syntax and write subroutines to unify the training/generalization phases in my ENVI/IDL extensions.
Mort
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