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tdba | 4 years ago

It depends on the model, yes. Here are some examples in the benchmarks section of our docs: https://www.tensil.ai/docs/reference/benchmarks/

We haven't specifically tested on any ICE40 FPGAs yet - if this is something that you'd really like to see, let me know! Taking a look at the lineup, the ICE40 LP8K and LP4K would be suitable for running a very small version of the Tensil accelerator. You'd want to run a small model in order to get reasonable performance.

Generally speaking, FPGAs with some kind of DSP (digital signal processing) capability will work best, since they can most efficiently implement the multiply-accumulate operations needed.

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ColonelPhantom|4 years ago

I think iCE40 LP/HX series are the biggest ones, but the iCE40UP5K is also neat: it has hardware multipliers unlike the LP/HX, and a relatively large 1 megabit RAM on-chip. Unfortunately, I think the UP family is relatively slow (as in propagation delay/max clock frequency).

323454|4 years ago

Thanks for pointing this out! The UP5K does look promising.

mochomocha|4 years ago

I'm curious if you have any benchmark (or anecdotal evidence) on the relative perf&power efficiency of using the DSP blocks of the FPGA boards or not?

323454|4 years ago

I don't have hard numbers at hand, but I'd estimate something like an order of magnitude improvement for using DSP for multiplication vs not. If they're available on the fabric, you'll definitely want to use them! If this is an experiment you want to run, I'd be very happy to help you figure out how to do it.

rowanG077|4 years ago

Cool! Yeah I would be interested in that. I would actually have some use cases for edge compute if it can fit into tiny FPGAs like the ICE40.

rbkettlewell|4 years ago

Here is an example of deploying a basic ML application to an ICE40 using a custom Keras to NN generator https://github.com/edge-analytics/fpga-sleep-tracker

So it definitely can be done with some careful attention to the limited number of multipliers on the device. I’ll be curious to check out how Tensil does in terms of mapping with highly resource constrained FPGAs. Regardless, Tensil looks like a very cool tool.