#8096: Speed up parent creation for multiplication of square matrices
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Reporter: boothby | Owner: boothby
Type: defect | Status: needs_review
Priority: minor | Milestone:
Component: linear algebra | Keywords:
Author: | Upstream: N/A
Reviewer: | Merged:
Work_issues: |
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Comment(by SimonKing):
Replying to [comment:4 boothby]:
> You'll note that the 32.5µs is matrix-by-matrix, whereas the 142ns is
element-by-element. Before my patch, the matrix-by-matrix time was 101µs.
I'd like the 32.5µs to go away, but I don't know how much of that would be
possible, at the moment.
OK, then it is an improvement. I hope to be able to do some refereeing
later today or tomorrow.
Anyway, I still wonder why basic matrix operations in Sage tend to be so
slow. I mean, do any complicated operations with parents happen behind the
scenes? By "slow", I mean "compared with MeatAxe matrices as provided by
my cohomology spkg":
{{{
sage: from pGroupCohomology.mtx import MTX
sage: F = GF(3)
sage: A = random_matrix(F,3)
sage: B = random_matrix(F,3)
sage: a = MTX(3,[list(r) for r in A.rows()])
sage: b = MTX(3,[list(r) for r in B.rows()])
sage: timeit("C=A*B")
625 loops, best of 3: 99.6 µs per loop
sage: timeit("c=a*b")
625 loops, best of 3: 1.01 µs per loop
sage: a*b == MTX(3,[list(r) for r in C.rows()])
True
sage: A = random_matrix(F,100)
sage: B = random_matrix(F,100)
sage: a = MTX(3,[list(r) for r in A.rows()])
sage: b = MTX(3,[list(r) for r in B.rows()])
sage: timeit("C=A*B")
125 loops, best of 3: 2.43 ms per loop
sage: timeit("c=a*b")
625 loops, best of 3: 376 µs per loop
sage: a*b == MTX(3,[list(r) for r in C.rows()])
True
}}}
--
Ticket URL: <http://trac.sagemath.org/sage_trac/ticket/8096#comment:5>
Sage <http://www.sagemath.org>
Sage: Creating a Viable Open Source Alternative to Magma, Maple, Mathematica,
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