AccelerEyes announced in December 2012 that it works with Mathworks on the GPU code and has discontinued its product Jacket for MATLAB:
http://blog.accelereyes.com/blog/2012/12/12/exciting-updates-from-accelereyes/
Unfortunately they do not sell Jacket licences anymore.
As far as I understand, the Jacket GPU Array solution based on ArrayFire was much faster than the gpuArray solution provided by MATLAB.
I started working with gpuArray, but I see that many functions are implemented poorly. For example a simple
myArray(:) = 0
is very slow. I have written some custom CUDA-Kernels, but the poorly-implemented standard MATLAB functionality adds a lot of overhead, even if working with gpuArrays consistently throughout the code. I fixed some issues by replacing MATLAB code with hand written CUDA code - but I do not want to reimplement the MATLAB standard functionality.
Another feature I am missing is sparse GPU matrices.
So my questions are:
How do is speed up the badly implemented default GPU implementations provided by MATLAB? In particular, how do I speed up sparse matrix operations in MATLAB using the GPU?