Hello Numenta! I'll start with a quick introduction: I'm a student at Aalto University, Finland, currently studying for B.Sc. in Systems Analysis (applied maths, statistics, decision theory and the like).
I remember seeing a discussion about porting the HTM algorithms to a GPU for performance boosts (and someone mentioning on the IRC channel that it will be hard, and I'm not here to prove otherwise) so I decided to give it a shot. In my free time I've been working on an OpenCL implementation of the Cortical Learning Algorithms as described in the whitepaper. The project is still in very early stages and I haven't any cool results to show, but I'm hoping it will serve at least as a source of inspiration to the community. I try to keep the code as simple as possible so that it is still possible to reason about the logic behind it. That being said I had to cut some corners in the process of porting the algorithm due to the limitations of SIMT computing and I haven't documented all those changes yet. One such change is that in the TP I never build a list of proposed changes to a segment, I just collapse the changes to a separate state and later decide whether to apply them or not. The code is available in GitHub: http://github.com/Jontte/CortiCL I'm a keen IRC user so should you prefer a more informal chat with me you will find me in the #nupic channel with the nickname Jontte. Best regards, Joonas Haapala
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