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I didn't phrase that well. How much of the Python community is writing code that would be positively affected by the removal of the GIL?

The entire debate seems to be for code that strikes me as being far and away from the typical Python programmer.

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Every ML engineer will be impacted. Web server probably less so.

I think it’s the other way around? I haven’t run into any ML code that could be multithreaded that wasn’t written in C++, but have often run into server tasks that could use a polling thread, etc.

All the ML code is written in lower level languages and that’s very unlikely to change, GIL or no.

driving multiple GPUs on the same node is better handled by threads. Python is forced to use multiprocessing

Yeah, you're right - even though CUDA is async, doing any preprocessing (in Python) can be harder if you don't have shared memory (the start-up latency hit of multiprocessing is not a problem in this context). I've only ever encountered "embarrassingly parallel" data-feeding problems, where the memory overhead of multiprocessing was small, but I could see other situations. Comment retracted.

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