Goal: Yes — the main goal is to bring C-like or close-to-C performance to Python code, without sacrificing the ease of writing Python. However, due to the nature of Python itself, I'm not sure how close I can get to native C performance, especially competing with systems (both SW and HW) that were revised and refined for decades.

Performance comparison against C: I don't have a formal benchmark directly against C yet. The early GPIO benchmark (480ns toggle) is competitive with hand-written C on ARM microcontrollers — even when running at a lower clock speed. But a full systematic comparison (across different workloads) would definitely be interesting for the future.

Main challenge: Yes — memory management is one of the biggest challenges. Dynamic memory allocation and garbage collection are tricky to manage efficiently without breaking real-time guarantees. I have a roadmap for it, but would like to stick to a real use case before moving forward.

Software emulation: I am using Icarus (could use Verilator) for RTL simulation if that's what you meant. But hardware behavior (like GPIO timing) still needs to be tested on the real FPGA to capture true performance characteristics.

There are a lot of dimensions to what you could call performance. The FPGA here is only clocked at 100 MHz and there's no way you're going to get the same throughput with it as you would on a conventional processor, especially if you add a JIT to optimize things. What you do get here is very low latency.