Coral is a great project, especially if you are using a completely vanilla off-the-shelf model. However if you've ever tried compiling a custom ML model for it, you know how finicky it can be. There are lots of ways that you can accidentally make it impossible for Coral to run your model, and it can be difficult to figure out what went wrong.

With Tensil, you circumvent that problem by changing the hardware to make it work for your model. If you have made modifications to an off-the-shelf model or have trained your own one from scratch, it might be a better option from the point of view of ease-of-use and even performance.

Ah, thanks for that clarification. I see that your tutorial is using the Avnet Ultra96 V2 dev board. Do you have anything that would work with a Raspberry Pi? Maybe some kind of FPGA addon board? Or do you feel that the Raspberry Pi isn't a good starting point for developing a real commercial product?

This is a great idea, we're looking at boards that could be used in combination with a Raspberry Pi. The reason we haven't investigated this so far is that most of the dev boards we've tested with have an ARM core embedded in the FPGA fabric, so the additional CPU the Raspberry Pi would provide wasn't necessary.

Looks like pynq-z2 has header pins which connect with raspberry pi. https://www.tulembedded.com/FPGA/ProductsPYNQ-Z2.html

Heh very similar experience with myriad-x there. Going off the beaten path is a pain, especially since the low-level is now so hidden...

Absolutely, the UX for compiler tools often leaves a lot to be desired. This is something we want to fix!

This is hard, very hard stuff. Between MLIR, the xla world, most HLS things (generalist stuff leaves a lot of perf on the table and you often end up in vhdl/asm anyway - while specialised stuff is often too restricted...) and the vivado 'let's write HDL/RTL like C', many broke their teeth.

I wish you good luck there, but you're up a huge task. You have all my congrats for going open source, and I think now it's mostly the only way forward. FINN is OSS and I'm very happy to have an OSS alternative. If only old Altera would go full OSS on new AI+FPGA stuff maybe we'd see great cross pollination.

Anyway, if Intel FPGA people aren't watching this, I can assure you they'll be looking soon.

Thank you - we'd love to see more OSS support from FPGA vendors too and we'll be watching closely for any developments there.

Apart from the discontinued Intel sticks, are there pytorch compatible USB accelerators on the market?

I'm not completely sure if the answer is no but I have had difficulty finding anything like that.