4 ms·
I don't know. I also don't use pypy much, since python+numba is actually fast enough most of the time, and I always see pypy as a fallback to see if I can squee
by bsdubernerd 6y ago
I don't know. I also don't use pypy much, since python+numba is actually fast enough most of the time, and I always see pypy as a fallback to see if I can squeeze a little bit more performance before running a task.
- goatlover 6y agoDoes Numba offer significantly faster compile times than Julia's JIT?
- jakobnissen 6y agoNo, from my own (relatively limited) experience with Numba, if you enable "@nopython", it's about the same speed as Julia, which is the same speed as C. The thing is that Numba is only applicable for simple numeric code. Last I checked it didn't even support custom classes. In fact, last I checked it didn't even support Numpy - to support "Numpy" it had to internally re-implement much of Numpy, which really says something bad about its use cases. In contrast, the Julia JIT speeds up the entire language from string processing to set operations. Edit: To not be misleading: Julia and C (and Numba) have the same speed only in the simple cases you can apply Numba to. In more diverse workloads, C pulls ahead of Julia for various small reasons.