Progress on No-GIL CPython

• aiobotocore

  3 1,085 7.6 Python

  asyncio support for botocore library using aiohttp

  

• Disruptor

  30 17,020 5.4 Java

  High Performance Inter-Thread Messaging Library

  

LMAX Disruptor has on their wiki that average latency to send a message from one thread to another at 53 nanoseconds. For comparison a mutex is like 25 nanoseconds and more if Contended but a mutex is point to point synchronization.

The great thing about it is that multiple threads can receive the same message without much more effort.

https://github.com/LMAX-Exchange/disruptor/wiki/Performance-...

https://gist.github.com/rmacy/2879257

I am dreaming of language that is similar to Smalltalk that stays single threaded until it makes sense to parallise.

I am looking for problems to parallelism that are not big data. Parallelism is like adding more cars to the road rather than increasing the speed of the car. But what does a desktop or mobile user need to do locally that could take advantage of the mathematical power of a computer? I'm still searching.

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• legion

  11 647 9.9 C++

  The Legion Parallel Programming System (by StanfordLegion)

  

Parallelism in CS is a bit like security in CS. People know it matters in the abstract senses but you really only get into it if you look for the training specifically. We're getting better at both over time: just as more languages/libraries/etc. are secure by default, more now are parallel by default. There's a ways to go, but I'm glad we didn't do this prematurely, because the technology has improved a lot in the last decade. Look for example at what we can do (safely!) with Rayon in Rust vs (unsafely!) with OpenMP in C++.

And there are things even further afield like what I work on [1][2][3].

[1]: https://legion.stanford.edu/

[2]: https://regent-lang.org/

[3]: https://github.com/nv-legate/cunumeric

• cupy

  21 7,774 9.9 Python

  NumPy & SciPy for GPU

  

• nanobind

  11 2,028 9.6 C++

  nanobind: tiny and efficient C++/Python bindings

Take a look at https://github.com/wjakob/nanobind

> More concretely, benchmarks show up to ~4× faster compile time, ~5× smaller binaries, and ~10× lower runtime overheads compared to pybind11.

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