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Show HN: I built a hardware processor that runs Python (runpyxl.com)

983 points by hwpythonner · 460 days ago · 265 comments on HN

Article summary

The article introduces RunPyXL, a custom hardware processor that runs Python programs directly without a traditional VM or interpreter. It achieves a GPIO round-trip latency of 480ns, which is 30x faster than MicroPython on a Pyboard. The processor is designed for embedded and real-time environments, where determinism and speed are crucial. The project aims to bring C-like performance to Python code without sacrificing the ease of writing Python.

Main themes

  • Python performance optimization
  • Custom hardware design
  • Embedded systems
  • Real-time computing
  • Determinism and predictability
  • Language design and compilation

What commenters say

  • The project's goal is to achieve C-like performance with the ease of writing Python, but it may not be possible to reach native C performance due to the nature of Python.
  • The use of CPython bytecode as an intermediate step may limit the project's flexibility and make it vulnerable to changes in the Python language.
  • The project's custom instruction set and hardware design could potentially be adapted for other languages, such as Lua or Ruby, but it would require significant changes.
  • The lack of speculative execution and JIT compilation in the current design is intentional, as it prioritizes determinism and predictability over raw performance.
  • The project's future plans include potentially turning it into a RISC-V extension or an ASIC, which could improve performance and reduce costs.
  • Some commenters suggest that the project could be improved by targeting the Python AST instead of bytecode, which would make it more resilient to changes in the Python language.
  • Others argue that the project's focus on embedded and real-time environments makes it less relevant to general-purpose computing, where JIT compilation and other optimizations are more important.
  • The project's potential applications include real-time control systems, ML inference, and robotics, where determinism and low latency are critical.