I’m currently working with some mex-functions that runs CUDA code that is called from Matlab. Many that work with signal and image processing use Matlab every day and would benefit from the GPU power for filtering and other things. I’ve tested the Jacket software but I was not very impressed since it is very limited in for example convolution (their convn function could for example only use 3 x 3 x 3 filters).
I’ve just managed to pass on device pointers between different mex-files, such that the data does not need to be passed between the GPU and the CPU all the time, but only when a copy-function is called from Matlab. This would make the programming really easy from Matlab and at the same time take advantage of the full power of the GPU, the problem is otherwise that the performance is greatly decreased by copying the data back and forth.
Is there any interest of this kind of toolbox? I will probably do it anyway for myself, but if I know that others would use it I would put more work into making it more general and well documented. I would not charge any money for this toolbox, or maybe a small fee like 10 dollars.