Interesting. Did you use the updated Julia code? Have you done any comparisons between reading and writing Numba JIT classes and Julia types in tight loops?
On Monday, July 25, 2016 at 10:41:48 AM UTC-4, dexto...@gmail.com wrote: > > Just for the sake of comprehensiveness, I ran your Python benchmark > through the Numba JIT library (which uses the same underlying LLVM > infrastructure that Julia does) and on my computer the Python code is > faster than Julia by 68%. Vanilla CPython is terrible for this kind of > simple explicit loop code, but Numba and other JIT libraries largely solve > that issue with minimal effort as long as the code is simple enough. That > by no means solves all of Python's issues in the context of numerical > programming and I'm sure the Julia benchmark could be improved as others > have already mentioned, but benchmarking Python this way isn't necessarily > representative of how a performance-conscious programmer would reasonably > approach a problem of this kind. >
