On Tue, Sep 27, 2016 at 7:18 PM, 'Bill Hart' via sage-devel <
sage-devel@googlegroups.com> wrote:

> I'm pretty sure the charpoly routine in Flint is much more recent that 2
> years. Are you referring to a Sage implementation on top of Flint
> arithmetic or something?
>

It is just a problem with Sage. Sorry, I thought I was clear about that. I
assume that no one has been using the algorithm='flint' option in Sage in
the last two years, which makes sense, because most people aren't going to
bother changing the default.


> The only timing that I can find right at the moment had us about 5x faster
> than Sage. It's not in a released version of Flint though, just in master.
>

That sounds really nice. On my laptop with current Sage, it might be the
other way around. With Sage 7.3 on my laptop, with this particular matrix,
I get

sage: %time f = A.charpoly(algorithm='flint')
CPU times: user 1min 24s, sys: 24 ms, total: 1min 24s
Wall time: 1min 24s

sage: %time f = A.charpoly(algorithm='linbox')
CPU times: user 13.3 s, sys: 4 ms, total: 13.3 s
Wall time: 13.3 s

However, perhaps the average runtime with linbox is infinity. (Also, this
in an out of date Linbox.)

I think that Linbox may be "cheating" in a way that Flint is not. I'm
pretty sure both implementations work mod p (or p^n?) for a bunch of p and
reconstruct. From my reading of the Flint source code (actually, I didn't
check the version in Sage) and comments from Clement Pernet, I think that
Flint uses an explicit Hadamard bound to determine how many primes to use,
while Linbox just waits for the CRT'd polynomial to stabilize for a few
primes. I have no idea how much of a difference that makes in this case.


> Bill.
>
> On Tuesday, 27 September 2016 05:49:47 UTC+2, Jonathan Bober wrote:
>>
>> On Tue, Sep 27, 2016 at 4:18 AM, William Stein <wst...@gmail.com> wrote:
>>
>>> On Mon, Sep 26, 2016 at 6:55 PM, Jonathan Bober <jwb...@gmail.com>
>>> wrote:
>>> > On Mon, Sep 26, 2016 at 11:52 PM, William Stein <wst...@gmail.com>
>>> wrote:
>>>
>>> >>
>>> >> On Mon, Sep 26, 2016 at 3:27 PM, Jonathan Bober <jwb...@gmail.com>
>>> wrote:
>>> >> > In the matrix_integer_dense charpoly() function, there is a note in
>>> the
>>> >> > docstring which says "Linbox charpoly disabled on 64-bit machines,
>>> since
>>> >> > it
>>> >> > hangs in many cases."
>>> >> >
>>> >> > As far as I can tell, that is not true, in the sense that (1) I have
>>> >> > 64-bit
>>> >> > machines, and Linbox charpoly is not disabled, (2)
>>> >> > charpoly(algorithm='flint') is so horribly broken that if it were
>>> ever
>>> >> > used
>>> >> > it should be quickly noticed that it is broken, and (3) I can't see
>>> >> > anywhere
>>> >> > where it is actually disabled.
>>> >> >
>>> >> > So I actually just submitted a patch which removes this note while
>>> >> > fixing
>>> >> > point (2). (Trac #21596).
>>> >> >
>>> >> > However...
>>> >> >
>>> >> > In some testing I'm noticing problems with charpoly(), so I'm
>>> wondering
>>> >> > where that message came from, and who knows something about it.
>>> >>
>>> >> Do you know about "git blame", or the "blame" button when viewing any
>>> >> file here: https://github.com/sagemath/sage/tree/master/src
>>> >
>>> >
>>> > Ah, yes. Of course I know about that. And it was you!
>>> >
>>> > You added that message here:
>>>
>>> Dang... I had a bad feeling that would be the conclusion :-)
>>>
>>
>> Well, I'm sure you've done one or two things in the meantime that will
>> allow me to forgive this one oversight.
>>
>>
>>> In my defense, Linbox/FLINT have themselves changed a lot over the
>>> years...  We added Linbox in 2007, I think.
>>>
>>>
>> Yes. As I said, this comment, and the design change, is ancient. In some
>> limiting testing, linbox tends to be faster than flint, but has very high
>> variance in the timings. (I haven't actually checked flint much.) Right now
>> I'm running the following code on 64 cores, which should test linbox:
>>
>> import time
>>
>> @parallel
>> def test(n):
>>     start = time.clock()
>>     f = B.charpoly()
>>     end = time.clock()
>>     runtime = end - start
>>     if f != g:
>>         print n, 'ohno'
>>         return runtime, 'ohno'
>>     else:
>>         return runtime, 'ok'
>>
>> A = load('hecke_matrix')
>> A._clear_cache()
>> B, denom = A._clear_denom()
>> g = B.charpoly()
>> B._clear_cache()
>>
>> import sys
>>
>> for result in test(range(100000)):
>>     print result[0][0][0], ' '.join([str(x) for x in result[1]])
>>     sys.stdout.flush()
>>
>> where the file hecke_matrix was produced by
>>
>> sage: M = ModularSymbols(3633, 2, -1)
>> sage: S = M.cuspidal_subspace().new_subspace()
>> sage: H = S.hecke_matrix(2)
>> sage: H.save('hecke_matrix')
>>
>> and the results are interesting:
>>
>> jb12407@lmfdb5:~/sage-bug$ sort -n -k 2 test_output3 | head
>> 30 27.98 ok
>> 64 28.0 ok
>> 2762 28.02 ok
>> 2790 28.02 ok
>> 3066 28.02 ok
>> 3495 28.03 ok
>> 3540 28.03 ok
>> 292 28.04 ok
>> 437 28.04 ok
>> 941 28.04 ok
>>
>> jb12407@lmfdb5:~/sage-bug$ sort -n -k 2 test_output3 | tail
>> 817 2426.04 ok
>> 1487 2466.3 ok
>> 1440 2686.43 ok
>> 459 2745.74 ok
>> 776 2994.01 ok
>> 912 3166.9 ok
>> 56 3189.98 ok
>> 546 3278.22 ok
>> 1008 3322.74 ok
>> 881 3392.73 ok
>>
>> jb12407@lmfdb5:~/sage-bug$ python analyze_output.py test_output3
>> average time: 53.9404572616
>> unfinished: [490, 523, 1009, 1132, 1274, 1319, 1589, 1726, 1955, 2019,
>> 2283, 2418, 2500, 2598, 2826, 2979, 2982, 3030, 3057, 3112, 3166, 3190,
>> 3199, 3210, 3273, 3310, 3358, 3401, 3407, 3434, 3481, 3487, 3534, 3546,
>> 3593, 3594, 3681, 3685, 3695, 3748, 3782, 3812, 3858, 3864, 3887]
>>
>> There hasn't yet been an ohno, but on a similar run of 5000 tests
>> computing A.charpoly() instead of B I have 1 ohno and 4 still running after
>> 5 hours. (So I'm expecting an error in the morning...)
>>
>> I think that maybe I was getting a higher error rate in Sage 7.3. The
>> current beta is using a newer linbox, so maybe it fixed something, but
>> maybe it isn't quite fixed.
>>
>> Maybe I should use a small matrix to run more tests more quickly, but
>> this came from a "real world" example.
>>
>>
>>> --
>>> William (http://wstein.org)
>>>
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>>
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