Dear Hans and sage-devel readers,

As I wrote on sage-devel a bit earlier, I had some polynomials that were 
causing singular gcd to slow down dramatically.  I had thought this was 
inconsistent, but upon more investigation it seems very consistent (on two 
different computers).

Here's some singular code to illustrate the problem.  The first one computes 
the gcd slowly, but not too bad (several seconds).
http://sage.math.washington.edu/home/jbmohler/gcd_fast.singular
This one takes a long time on my computer (at least a couple of minutes).
http://sage.math.washington.edu/home/jbmohler/gcd_slow.singular
Those time indications are on a P4 2.4 ghz.  Memory usage of the Singular 
executable is listed in 'top' at 12 MB (which seems perfectly reasonable to 
me).  Note also that mathematica (on sage.math) can write the ratio of these 
polynomials in reduced form with-in a second (I'm supposing it computes a gcd 
on the way to doing this).

I computed the semi-random polynomials from this python script:
http://sage.math.washington.edu/home/jbmohler/singular_vs_mathematica.py

Basically, they are products of binomials of the form
 (1-{x0}^{e0}*...*{xn}^{en})
where the {ei} are chosen randomly from {0,1}.  I multiply about 8-12 of these 
together to get polynomials of approximately 2^8 to 2^12 monomials.  There is 
a huge speed difference between n=4 and n=5 (5 variables vs. 6 variables).

It also seems to make a difference if I select my {ei} from a larger set (say 
{0,1,...,10}).  This seems to be significantly faster (I'm guessing it's 
because the gcd is of lower degree).

I've now reproduced this with the singular that is built from sage and also 
with a singular build from the singular website (3.0.3-ix86-Linux).

Thanks
Joel

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