It seems to be spending a lot of time in cython code, so "%crun" might give
the best idea. This is part of the profile obtained by running the "copy"
command 20 times:
0 0.0% 1.3% 2575 98.2%
__pyx_pw_4sage_6matrix_21matrix_integer_sparse_21Matrix_integer_sparse_5__init__
27 1.0% 2.4% 2271 86.6%
__pyx_f_4sage_7modules_21vector_integer_sparse_mpz_vector_set_entry
0 0.0% 2.4% 1719 65.6% PyRun_FileExFlags
24 0.9% 3.3% 1290 49.2%
__pyx_f_4sage_7modules_21vector_integer_sparse_allocate_mpz_vector
213 8.1% 11.4% 1201 45.8% sig_malloc (inline)
0 0.0% 11.4% 1193 45.5% PyRun_SimpleFileExFlags
27 1.0% 12.4% 957 36.5% __gmpz_init
38 1.4% 13.9% 930 35.5%
__pyx_f_4sage_3ext_6memory_sage_sig_malloc
316 12.1% 25.9% 828 31.6% __GI___libc_malloc
163 6.2% 32.2% 751 28.7% sig_free (inline)
5 0.2% 32.4% 733 28.0%
__pyx_f_4sage_3ext_6memory_sage_sig_free
0 0.0% 32.4% 705 26.9% Py_Main
323 12.3% 44.7% 512 19.5% _int_malloc
336 12.8% 57.5% 340 13.0% _int_free
334 12.7% 70.2% 334 12.7% sig_unblock (inline)
There's no obvious culprit to my eye. It looks like a lot of time is spent
in memory allocation and in setting of entries. Using a boolean matrix
could be much more efficient.
On Saturday, August 24, 2019 at 3:47:25 AM UTC-7, Frédéric Chapoton wrote:
>
> Hello,
>
> With sage 8.9.b7 under py3, I get
>
> sage: P = posets.TamariLattice(8)
> sage: H = P._hasse_diagram
> sage: L = H.lequal_matrix()
> sage: %time copy(L)
> CPU times: user 2.71 s, sys: 4.01 ms, total: 2.71 s
> Wall time: 2.71 s
> 1430 x 1430 sparse matrix over Integer Ring (use the '.str()' method to
> see the entries)
>
> And this seems to me to be a bit too much. But maybe I am wrong ? This
> comes from here:
>
> sage: ms = L.parent()
> sage: ec = ms.element_class
> sage: d = L.dict()
> sage: %timeit ec(ms, entries=d, coerce=False, copy=False)
> 1 loop, best of 5: 2.63 s per loop
>
> Any idea on what is happening ? on how to improve the situation ?
>
> cheers,
> Frédéric
>
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