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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?

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