Hi. > > I think SymPy is an excellent benchmark target. The nature of SymPy > (or any computer algebra system) is such that any high-level operation > will exercise most parts of the system. For example > "integrate(x**3*exp(x)*sin(x), x)" performs ~4 million function calls > to some 200 functions all over SymPy, and it's a calculation that > you'd use SymPy for in practice, so it would be a good real-world test > case. > > Also, mpmath might be a good target (mpmath is a subpackage of SymPy). > There are some microbenchmarks at [1] although I could come up with > some slightly more complex "real world" calculation if you are > interested. Mpmath heavily depends on long integer performance in > particular, but if you use low precision, it will exercise general > Python performance. For myself, I would be interested in whether > PyPy's new JIT can beat psyco, which all around makes mpmath ~2x > faster on top of CPython.
Long integer performance is not *exactly* on top of my list of stuff to look to. About PyPy JIT beating psyco, yes, but not exactly right now :-) I was also wondering what *does not* exercise most of the system and yet still makes some sort of sense. Cheers, fijal --~--~---------~--~----~------------~-------~--~----~ You received this message because you are subscribed to the Google Groups "sympy" group. To post to this group, send email to [email protected] To unsubscribe from this group, send email to [email protected] For more options, visit this group at http://groups.google.com/group/sympy?hl=en -~----------~----~----~----~------~----~------~--~---
