#20681: Cythonize the special methods in the categories that handle coercion in
arithmetic
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Reporter: nthiery | Owner:
Type: enhancement | Status: needs_review
Priority: major | Milestone: sage-7.3
Component: categories | Resolution:
Keywords: performance | Merged in:
Authors: Nicolas M. Thiéry | Reviewers:
Report Upstream: N/A | Work issues:
Branch: | Commit:
Dependencies: | Stopgaps:
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Changes (by nthiery):
* status: new => needs_review
Old description:
New description:
Recall that the Sage categories provide implementations for Python's
special methods for the basic arithmetic operations (e.g. `__mul__`,
`__add__`), that dispatch to the coercion model or call Sage's special
methods (e.g. `_mul_`, `_add_`) for the internal operations.
Before this ticket, this indirection induces an overhead of roughly
500ns:
{{{
sage: S = Semigroups().example()
sage: x = S.an_element()
sage: sage: %timeit [x*x for i in range(1000)]
1000 loops, best of 3: 1.21 ms per loop
sage: sage: %timeit [x.__mul__(x) for i in range(1000)]
1000 loops, best of 3: 1.12 ms per loop
sage: sage: %timeit [x._mul_(x) for i in range(1000)]
1000 loops, best of 3: 643 µs per loop
}}}
(the average timing don't vary much if we try again)
After this ticket, which Cythonize those methods, the overhead is
reduced to roughly 260ns, which is a speedup by a factor of 2:
{{{
sage: %timeit [x*x for i in range(1000)]
1000 loops, best of 3: 929 µs per loop
sage: %timeit [x.__mul__(x) for i in range(1000)]
1000 loops, best of 3: 884 µs per loop
sage: %timeit [x._mul_(x) for i in range(1000)]
1000 loops, best of 3: 624 µs per loop
}}}
--
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Ticket URL: <http://trac.sagemath.org/ticket/20681#comment:1>
Sage <http://www.sagemath.org>
Sage: Creating a Viable Open Source Alternative to Magma, Maple, Mathematica,
and MATLAB
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