pyperformance
nogil
pyperformance | nogil | |
---|---|---|
6 | 31 | |
817 | 2,853 | |
0.9% | - | |
6.6 | 5.7 | |
20 days ago | 2 months ago | |
Python | Python | |
MIT License | GNU General Public License v3.0 or later |
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pyperformance
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Phoronix: PyPerformance benchmark is on average 32% faster on Python 3.11 compared to 3.10 (on a Ryzen 9 5950X)
PyPerformance benchmark: https://github.com/python/pyperformance
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Faster CPython 3.12 Plan
25% number is from pyperformance benchmark suite, which you can replicate. Whether pyperformance is representative benchmark suite is another question.
https://github.com/python/pyperformance
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The Performance Benchmarks Comparing various combinations of GCC and Python
For each combination, We launch a GCC container and build Python with the GCC. Then run benchmarks using pyperformance and export to a JSON file.
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This Week In Python
pyperformance – Python Performance Benchmark Suite
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Hello, I created a interpreted dynamic programming language in C#. I use a bytecode compiler and a vm for interpretation. Right now I'm trying to optimise it. Any help would be great!
There are some standard benchmarks like fannkuch, deltablue, and so on (see a bunch for Python here) that you can port to your VM. They have adjustable values that you can raise or lower to increase or decrease the amount of time you take.
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Why is python so much slower on MacOS?
So I decided to run some actual benchmark suite. I found pyperformance which would seem to do the trick.
nogil
- Proof-of-Concept Multithreaded Python Without the GIL
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Our Plan for Python 3.13
This might be a dumb question, but why would removing the GIL break FFI? Is it just that existing no-GIL implementations/proposals have discarded/ignored it, or is there a fundamental requirement, e.g. C programs unavoidably interact directly with the GIL? I know that the C-API is only stable between minor releases [0] compiled in the same manner [1], so it's not like the ecosystem is dependent upon it never changing.
I cannot seem to find much discussion about this. I have found a no-GIL interpreter that works with numpy, scikit, etc. [2][3] so it doesn't seem to be a hard limit. (That said, it was not stated if that particular no-GIL implementation requires specially built versions of C-API libs or if it's a drop-in replacement.)
[0]: https://docs.python.org/3/c-api/stable.html#c-api-stability
[1]: https://docs.python.org/3/c-api/stable.html#platform-conside...
[2]: https://github.com/colesbury/nogil
[3]: https://discuss.python.org/t/pep-703-making-the-global-inter...
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Real Multithreading Is Coming to Python
https://github.com/colesbury/nogil does manage to get rid of the GIL, but it's not certain to make it into Python core. The main problem is the amount of existing libraries that depend on the existence of the GIL without realizing it - breaking those would be extremely disruptive.
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[D] The hype around Mojo lang
CPython is also investigating the removal of the GIL (PEP703, nogil). I think requiring the GIL is a wider thing that libraries will need to address anyway. But also, for the same reason as above I'd be surprised if the Modular team thought that saying "you can run all your python code unchanged" was a good idea if there was a secret "except for code that uses numpy" muttered under the breath.
- PEP 684 was accepted – Per-interpreter GIL in Python 3.12
- PEP 703 – Making the Global Interpreter Lock Optional in CPython
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Python 3.11.0 final is now available
I'm worried about the speedup
My understanding is that it's based on the most recent attempt to remove the GIL by Sam Gross
https://github.com/colesbury/nogil
In addition to some ways to try to not have nogil have as much overhead he added a lot of unrelated speed improvements so that python without the gil would still be faster not slower in single thread mode. They seem to have merged those performance patches first that means if they add his Gil removal patches in say python 3.12 it will still be substantially slower then 3.11 although faster then 3.10. I hope that doesn't stop them from removing the gil (at least by default)
- Removed the GIL back in 1996 from Python 1.4, primarily to create a re-entrant Python interpreter.
- I Tried Removing Python's GIL Back in 1996
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Faster CPython 3.12 Plan
Looks like it's still active to me:
https://github.com/colesbury/nogil/
What are some alternatives?
pybench - Python benchmark tool inspired by Geekbench.
hpy - HPy: a better API for Python
asv - Airspeed Velocity: A simple Python benchmarking tool with web-based reporting
mypyc - Compile type annotated Python to fast C extensions
pyperf - Toolkit to run Python benchmarks
numpy - The fundamental package for scientific computing with Python.
Nuitka - Nuitka is a Python compiler written in Python. It's fully compatible with Python 2.6, 2.7, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 3.10, and 3.11. You feed it your Python app, it does a lot of clever things, and spits out an executable or extension module.
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
ga-extractor - Tool for extracting Google Analytics data suitable for migrating to other platforms/databases
python-feedstock - A conda-smithy repository for python.
pyeventbus - Python Eventbus
sbcl - Mirror of Steel Bank Common Lisp (SBCL)'s official repository