5 ms·
Ah yes. 25% faster. I get 50x faster (that would be 5000%) just dipping into Numpy when I need to (admittedly with AVX), and C when I have to. Both are like, t
by vegabook 11y ago
Ah yes. 25% faster.
I get 50x faster (that would be 5000%) just dipping into Numpy when I need to (admittedly with AVX), and C when I have to. Both are like, trivially easy.
Why are we bothering with making native Python marginally faster when it is already the perfect tool for the mission it is there to accomplish (glue), and there are dozens of other tools which are optimized for performance?
- rcarmo 11y agoBecause we need faster glue? :)
- Animats 11y ago"Both are like, trivially easy." Until you screw up memory allocation and have to debug. There's a race condition in Python 3's CPickle that corrupts memory.[1] I can't reproduce it well enough to submit a bug report that won't be ignored. [1] http://bugs.python.org/issue23655 http://bugs.python.org/issue23655
- deleted 11y ago[deleted]
- deleted 11y ago[deleted]
- burfog 11y agoDebugging gets way easier if you finish the C-to-Python transition, ripping out the last bit of Python. Having the interpreter running makes debugging way harder than it needs to be. Lose that, and suddenly you can take advantage of all sorts of powerful debugging tools. (valgrind, less-painful use of a standard debugger, -fsanitize= compiler options, C interpreters, coverity, etc.) Ditching the python also dramatically improves start-up latency.