Julia's Python performance example in pypy

Question

Julia is a new statistical programming language that claims significantly better performance than competing languages. I'm trying to verify this. Julia has a performance test written in Python: https://github.com/JuliaLang/julia/blob/master/test/perf/perf.py

I can't get it to work with pypy. Perhaps this is due to numpypy incompatibilities with numpy, but I'm not getting far enough to determine that. I followed the ImportError advice "...or just write 'import numpypy' first in your program..." but I get another ImportError: "No module named numpy.linalg"

I have near zero experience with Python and I'm looking for a complete solution that I can run. The benefit of getting this to work is that we can we have a apples-to-apples (jit lang-to-jit lang) comparison.

Answer 1

Linalg is not implemented as of now. I think a new ffi and getting 1.9 out of the door (which require quite a few numpy fixes, see the bug tracker) are getting top priority. I don't think having linalg right now is that interesting. We would like to have more of numpy running first. I'm open to be convinced though. Arguments?

Answer 2

There are 4 test on Julia git (perf.py) in pure Python. Here, I run, in the same computer, perf.py (only the pure Python test) and perf.pl for a apples-to-apples comparison. I'm a little worried for Python/Pypy timing :/

And... Why

## fibonacci ##

def fib(n):
    if n<2:
        return n
    return fib(n-1)+fib(n-2)

is slower in Pypy than in Python ?

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I post this question in https://bugs.pypy.org/issue1344 [Pypy slower in recursion than Python2.7, Python3.2 and Julia] I get the next answer:

This is a situation where the warmup time is very significant (it tries to inline all the recursion), but once you warm it up it's actually very fast.

So, I do the text with different numbers of n for fib(n). Indeed, Pypy comes faster than Python with a n > 30, but in recursion is slower than Julia:

[ En bold the faster python implementation ]

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Because are implemented with recursion, Quicksort and fib are slower in Pypy. Julia seems to be faster than PyPy.