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.
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.
Java is statically typed and a lot saner than Python, and JavaCard is a fairly restricted subset. Apparently real cards don't typically support garbage collection.
IMO JavaCard doesn't really make sense either. There's clearly space for another language here, though I suspect most people would much rather just use Rust than learn a new language.
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.
