Proposed Change Could Speed Python Dramatically

'One of Python's long-standing weaknesses, its inability to scale well in multithreaded environments, is the target of a new proposal among the core developers of the popular programming language,' reports InfoWorld:
Developer Sam Gross has proposed a major change to the Global Interpreter Lock, or GIL — a key component in CPython, the reference implementation of Python. If accepted, Gross's proposal would rewrite the way Python serializes access to objects in its runtime from multiple threads, and would boost multithreaded performance significantly... The new proposal makes changes to the way reference counting works for Python objects, so that references from the thread that owns an object are handled differently from those coming from other threads.

The overall effect of this change, and a number of others with it, actually boosts single-threaded performance slightly — by around 10%, according to some benchmarks performed on a forked version of the interpreter versus the mainline CPython 3.9 interpreter. Multithreaded performance, on some benchmarks, scales almost linearly with each new thread in the best case — e.g., when using 20 threads, an 18.1x speedup on one benchmark and a 19.8x speedup on another.

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