Regarding LSTMs, yes. We're aiming to support all machine learning model architectures: do you have any particular models you're interested in that we should be prototyping with?
For CGRAs, we don't have any immediate plans to explicitly support them. What kind of use case do you have in mind? Generally, any platform that can implement a blob of generated RTL should be something we can work with quite easily.
That said, I am going to get a PYNQ-Z2 just to try this out! Btw, quick glance at the tutorial says Z1.. can I assume Z2 would be barely an inconvenience?
For commercialization, the core technology will always be free and open source, but we plan to offer a “pro” version with extra enterprise features under a dual license arrangement, similar to Gitlab. We are also working on a cloud service for running our tools in a hosted setup, in which you’ll be able to run a search across all possible Tensil architectures to automatically find the best FPGA for your model. I'd love to hear your feedback on these plans!
The broader point is that Tensil is extremely flexible, so you can try out lots of different accelerator configurations to find the one that works best for your ML model. Think of it as optimizing the hardware first, then the software if needed.
We're actually working on a tool to manage and automate this hardware architecture search - watch this space!