[nynx]

This is cool for sure. I think you’ll ultimately find that this can’t really be faster than modern OoO cores because python instructions are so complex. To execute them OoO or even at a reasonable frequency (e.g. to reduce combinatorial latency), you’ll need to emit type-specialized microcode on the fly, but you can’t do that until the types are known — which is only the case once all the inputs are known for python.

[hwpythonner]

Thanks — appreciate it!

You're right that dynamic typing makes high-frequency execution tricky, and modern OoO cores are incredibly good at hiding latencies. But PyXL isn't trying to replace general-purpose CPUs — it's designed for efficient, predictable execution in embedded and real-time systems, where simplicity and determinism matter more than absolute throughput. Most embedded cores (like ARM Cortex-M and simple RISC-V) are in-order too — and deliver huge value by focusing on predictability and power efficiency. That said, there’s room for smart optimizations even in a simple core — like limited lookahead on types, hazard detection, and other techniques to smooth execution paths. I think embedded and real-time represent the purest core of the architecture — and once that's solid, there's a lot of room to iterate upward for higher-end acceleration later.

[IshKebab]

Very cool! Nobody who really wants simplicity and determinism is going to be using Python on a microcontroller though.

[gavinsyancey]

Sure, but for embedded use cases (which this is targeting), the goal isn't raw speed so much as being fast enough for specific use cases while minimizing power usage / die area / cost.