The Quest For Faster Python
This report <https://www.theregister.com/2021/05/06/the_quest_for_faster_python/> on Facebook’s new “Cinder” project for speeding up Python code also mentions some other existing alternatives for doing the same. Python is commonly considered slow, yet note this one interesting comparison that was done with JavaScript: In May 2020 AI specialists DLabs tested JavaScript versus Python performance for machine learning. For JavaScript Node 12.16.1 was used, and for Python 3.7.6. The results seem surprising: although JavaScript benefits from an excellent JIT in Node (which uses the V8 engine as used by Google Chrome), Python easily outperformed it. "The learnings from the tests I ran are stark. JavaScript couldn’t get close to Python’s tasks — across the board. JavaScript’s computational performance is still much better than Python’s. However, the maturity of the libraries — which often have underlying modules written in C — means that operations on large datasets can offer so much more than sheer computational power," said developer Krzysztof Miśtal. Which is what Guido van Rossum has long advised: write performance-critical parts as extension modules in C.
Relevant: Energy Efficiency across Programming Languages How Does Energy, Time, and Memory Relate? https://greenlab.di.uminho.pt/wp-content/uploads/2017/09/paperSLE.pdf Python doesn't seem to fare well. C appears at the top of all 'pareto optimal sets for different combinations of objects' in Table 5. Cheers, Matthew *Doctoral Researcher, TAIAO project <https://taiao.ai/>Machine Learning Laboratory, FG.2.01LinkedIn <https://www.linkedin.com/in/matthew-skiffington>* On Fri, May 7, 2021 at 2:36 PM Lawrence D'Oliveiro <ldo(a)geek-central.gen.nz> wrote:
This report <https://www.theregister.com/2021/05/06/the_quest_for_faster_python/> on Facebook’s new “Cinder” project for speeding up Python code also mentions some other existing alternatives for doing the same. Python is commonly considered slow, yet note this one interesting comparison that was done with JavaScript:
In May 2020 AI specialists DLabs tested JavaScript versus Python performance for machine learning. For JavaScript Node 12.16.1 was used, and for Python 3.7.6. The results seem surprising: although JavaScript benefits from an excellent JIT in Node (which uses the V8 engine as used by Google Chrome), Python easily outperformed it. "The learnings from the tests I ran are stark. JavaScript couldn’t get close to Python’s tasks — across the board. JavaScript’s computational performance is still much better than Python’s. However, the maturity of the libraries — which often have underlying modules written in C — means that operations on large datasets can offer so much more than sheer computational power," said developer Krzysztof Miśtal.
Which is what Guido van Rossum has long advised: write performance-critical parts as extension modules in C. _______________________________________________ wlug mailing list -- wlug(a)list.waikato.ac.nz | To unsubscribe send an email to wlug-leave(a)list.waikato.ac.nz Unsubscribe: https://list.waikato.ac.nz/postorius/lists/wlug.list.waikato.ac.nz
On Mon, 31 May 2021 14:16:33 +1200, Matthew Skiffington wrote:
Energy Efficiency across Programming Languages How Does Energy, Time, and Memory Relate? https://greenlab.di.uminho.pt/wp-content/uploads/2017/09/paperSLE.pdf
Measured specifically on Intel processors? Not exactly the most energy-efficient architecture out there ...
participants (2)
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Lawrence D'Oliveiro -
Matthew Skiffington