[rachitnigam]

Yeah, we've been able to compile entire neural networks like GoogleNet etc. through Calyx. See: https://calebmkim.github.io/files/pubs/src.pdf

HLS-like languages are an input to Calyx. For example, we're currently building a Vivado alternative using Calyx and the frontend there does the pipelining for us. Calyx then goes in and performs a bunch of other optimizations.

A big edge we have is that Calyx supports both statically-scheduled circuits (where the latencies of things are known) and dynamically-scheduled circuits (where latency is not known). Because of this, we have been able to do optimizations in this new flow that take advantage of both.

[vrinsd]

This is great to hear. It might be nice to bubble those examples up to your Github page along with some diagrams and logic/resource results after synthesis (i.e. how many LUTs, BRAM, etc).

It's easy for people to do a lot of naysaying, it's a lot harder to try and actually do something evolutionary, let alone revolutionary. Please keep posting with up-to-date results.