Hello,

On Wed, Sep 10, 2008 at 6:23 PM, phil <[EMAIL PROTECTED]> wrote:
> This seems to scale very poorly with the number of variables.
> Basically, it's impractical to compute determinants when there are
> more than 4 variables.

While the problem does become more computationally challenging, a
non-trivial amount of time in your benchmarks is taken up by string
conversion.  Note that what you're doing is not what Martin's patch
does.  Here are the timings with Martin's patch:

sage: R.<a,b> = QQ[]
sage: C = random_matrix(R,8,8)
sage: %time d = C.det()
CPU times: user 0.18 s, sys: 0.00 s, total: 0.18 s
Wall time: 0.20 s

sage: R.<a,b,c> = QQ[]
sage: C = random_matrix(R,8,8)
sage: %time d = C.det()
CPU times: user 0.94 s, sys: 0.00 s, total: 0.94 s
Wall time: 0.95 s

sage: R.<a,b,c,d> = QQ[]
sage: C = random_matrix(R,8,8)
sage: %time d = C.det()
CPU times: user 9.54 s, sys: 0.02 s, total: 9.56 s
Wall time: 10.16 s

sage: R.<a,b,c,d,e> = QQ[]
sage: C = random_matrix(R,8,8)
sage: %time d = C.det()
CPU times: user 128.78 s, sys: 0.18 s, total: 128.96 s
Wall time: 135.36 s

--Mike

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