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What's the nature of the performance regressions? Is everything just universally 5% slower, or did the benchmark scores drop by 5% because some particular operations/workloads are slower in this release? If the latter, which ones?


Basically the way we did the JIT/greenlet integration involved restructuring how frames are represented in the JIT, which was very slightly slower.

This was needed to support greenlets fully, and so on its own it might be worth it, however it also gives us the ability to do some more (very creative) optimizations, which should let us buy that performance back, and more.


Cool, thanks. I'll probably run one of my projects' benchmark set later today to see how this stacks up... I suspect that if some of the numpy and cffi stuff is enough faster, I may still be better off on this release than the last. Either way, gevent support seems worth it to me. Kudos on the release.


How integral are greenlets now to PyPy? Just an optimization add-on, or something that the JIT core will rely on?


We include a builtin _continuation module, which is the foundation for greenlets and stackless. PyPy compiles just fine if you don't include that though.




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