Theano has the infrastructure in place for OpenCL, but not all 'operations' are implemented, which (for any decent calculation) means that it's a no-go [1]. Un

Theano has the infrastructure in place for OpenCL, but not all 'operations' are implemented, which (for any decent calculation) means that it's a no-go [1]. Unfortunately, the focus at the Montreal lab that has a huge influence on its development seems to be (a) 'blocks' for a high-level DNN environment (which is very cool) and (b) CUDA-to-the-max (which is understandable, given Nvidia actively seeds research labs with freeby cards, and -- as evidenced by the article -- is putting a lot of effort into supporting deep learning). rant start: It's a shame that OpenCL doesn't get more love. Just the other day there was a cool Clojure GPU project (based on OpenCL) announced on HN. One of the comments was 'will you be building this for CUDA too?'. Rather than pressure open source writers to support closed systems, it would be better to pressure Nvidia to provide up-to-date OpenCL drivers. Newer Nvidia cards are at OpenCL 1.2. And the (somewhat old) OpenCL drivers are always there in an Nvidia install. But does Nvidia ever talk about that : No. It's entirely in Nvidia's interest to encourage everyone to talk CUDA-only. But on a GFLOPs/$ basis, and for the cause of Free, CUDA isn't the right way to go. rant end. [1] https://github.com/Theano/Theano/issues/2936 https://github.com/Theano/Theano/issues/2936