[syrusakbary]

Hey, I'd love to reproduce the ~2x slowdown you commented from running the workload in Native CPython compared to Wasm CPython (in any runtime, browser or outside).

Any tip would be helpful so we can debug it. If your claims are accurate, we can easily get py2wasm even running faster than native CPython!

Note: we benchmarked in a M3 Max laptop, so maybe there's some difference there?

[kelp]

Here is a trivial example, also on a M3 Max:

  cat hello.py
  print("Hello, Wasm!")

  time python3 ./hello.py
  Hello, Wasm!

  ________________________________________________________
  Executed in   26.86 millis    fish           external
     usr time   16.37 millis    0.13 millis   16.24 millis
     sys time    7.25 millis    1.14 millis    6.11 millis

  time wasmer hello.wasm
  Hello, Wasm!

  ________________________________________________________
  Executed in   84.77 millis    fish           external
     usr time   50.26 millis    0.14 millis   50.12 millis
     sys time   28.97 millis    1.21 millis   27.76 millis

  time wasmtime hello.wasm
  Hello, Wasm!

  ________________________________________________________
  Executed in  141.72 millis    fish           external
     usr time  120.86 millis    0.13 millis  120.72 millis
     sys time   16.65 millis    1.20 millis   15.45 millis

[5-]

note that i'm not claiming 2x slowdown for cpython.

but here's one test i've run just now:

using your test file, i've run this one-liner on my x86_64 linux laptop in https://pyodide.org/en/stable/console.html in chromium (v8) and natively (pyodide's urllib doesn't handle https for some reason):

   import requests;exec(requests.get('https://gist.githubusercontent.com/syrusakbary/b318c97aaa8de6e8040fdd5d3995cb7c/raw/1c6cc96cf98bd7bd41c81ba9d10dc4d19b1c3e53/pystone.py').text)

native: ~470k

pyodide: ~200k

i.e. ~2.4x slowdown

[syrusakbary]

Thanks!

That should help us a lot to investigate further the difference in timing. I remember trying the py2wasm strategy about 4 years ago, and I got it running faster than native CPython, so there must be something we are missing!