# Numpy.sort vs Julia sort

**URL:** <https://discourse.julialang.org/t/numpy-sort-vs-julia-sort/123421>\
**Category:** Performance\
**Tags:** benchmark, python\
**Created:** [December 3, 2024, 5:14pm UTC](https://discourse.julialang.org/t/numpy-sort-vs-julia-sort/123421 "2024-12-03T17:14:53Z")\
**Posts on this page:** 1\
**Showing post:** 7

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**Author:** ![Benny](https://avatars.discourse-cdn.com/v4/letter/b/49beb7/32.png) [@Benny](https://discourse.julialang.org/u/Benny)\
**Post date:** [December 4, 2024, 12:16pm UTC](https://discourse.julialang.org/t/numpy-sort-vs-julia-sort/123421/7 "2024-12-04T12:16:51Z")

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> [@gitboy16](#):
>
> I guess apple M processors don’t support avx and we can’t see that type of performance?

Yes, AVX is specific to x86, though Apple’s chips have their own vector instructions.

> [@gitboy16](#):
>
> Possibly room for improvements?

NumPy wraps Intel’s [x86-simd-sort](https://github.com/intel/x86-simd-sort) C++ library.  
[Intel Publishes Blazing Fast AVX-512 Sorting Library, Numpy Switching To It For 10~17x Faster Sorts - Phoronix](https://www.phoronix.com/news/Intel-AVX-512-Quicksort-Numpy)  
Many if not all of those contributions were made by an Intel developer, who also wrapped at least one other Intel library to support AVX-512.  
[Intel Contributes AVX-512 Optimizations To Numpy, Yields Massive Speedups - Phoronix](https://www.phoronix.com/news/Intel-Numpy-AVX-512-Landed)  
Though it’s worth noting that this isn’t necessarily the fastest implementation.  
[sort-research-rs/writeup/intel\_avx512/text.md at main · Voultapher/sort-research-rs · GitHub](https://github.com/Voultapher/sort-research-rs/blob/main/writeup/intel_avx512/text.md)

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