#4260: use LinBox as native matrix representation for dense matrices over GF(p)
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Reporter: malb | Owner: cpernet
Type: enhancement | Status: needs_review
Priority: major | Milestone: sage-4.7.2
Component: linear algebra | Keywords: linbox, linear algebra,
sd32
Work_issues: extend documentation | Upstream: N/A
Reviewer: | Author: Burcin Erocal, Martin
Albrecht, Rob Beezer
Merged: | Dependencies:
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Comment(by SimonKing):
Replying to [comment:17 malb]:
> * Simon, can you try again after setting {{{MAX_MODULUS}}} in
sage.matrix.matrix_modn_dense_float to 2^6^? This forces the use of
doubles for GF(101) which might be more efficient.
It isn't:
{{{
sage: sage.matrix.matrix_modn_dense_float.MAX_MODULUS = 2^6
sage: MS = MatrixSpace(GF(101),2000,2000)
sage: %time A = MS.random_element()
CPU times: user 0.21 s, sys: 0.01 s, total: 0.22 s
Wall time: 0.22 s
sage: B = MS.random_element()
sage: %time C = A*B
CPU times: user 1.88 s, sys: 0.04 s, total: 1.92 s
Wall time: 1.93 s
sage: %time A.echelonize()
CPU times: user 2.65 s, sys: 0.00 s, total: 2.65 s
Wall time: 2.69 s
sage: type(A)
<type 'sage.matrix.matrix_modn_dense_double.Matrix_modn_dense_double'>
}}}
> Also, how fast is {{{A.echelonize('gauss')}}} for you on that benchmark?
You mean "how slow", I suppose:
{{{
sage: A = MS.random_element()
sage: %time A.echelonize('gauss')
CPU times: user 41.53 s, sys: 0.10 s, total: 41.63 s
Wall time: 41.75 s
}}}
--
Ticket URL: <http://trac.sagemath.org/sage_trac/ticket/4260#comment:19>
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