#3498: [with patch, needs work] make numpy the backend for matrices over CDF and
RDF
----------------------------+-----------------------------------------------
Reporter: jason | Owner: was
Type: defect | Status: new
Priority: major | Milestone: sage-3.1.3
Component: linear algebra | Resolution:
Keywords: |
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Comment (by mabshoff):
Ok, this is a problem:
{{{
==10940== LEAK SUMMARY:
==10940== definitely lost: 13,108 bytes in 321 blocks.
==10940== possibly lost: 303,196 bytes in 829 blocks.
==10940== still reachable: 34,200,409 bytes in 198,999 blocks.
==10940== suppressed: 340,122 bytes in 5,402 blocks.
==10940== Reachable blocks (those to which a pointer was found) are not
shown.
==10940== To see them, rerun with: --leak-check=full --show-reachable=yes
}}}
This happens when valgrinding sage/modules/complex_double_vector.pyx. But
the issue is not the code that Jason wrote, but that we leak not
insignificant amounts of memory if we (re)import numpy. So I would suggest
doing it once at the toplevel and killing all other import numpy
statements.
Another thing that concerns me is that the number of still reachable
objects has gone up dramatically, i.e. contrast the above to the situation
before:
{{{
==16395== LEAK SUMMARY:
==16395== definitely lost: 612 bytes in 11 blocks.
==16395== possibly lost: 312,717 bytes in 866 blocks.
==16395== still reachable: 33,376,714 bytes in 193,940 blocks.
==16395== suppressed: 329,948 bytes in 5,223 blocks.
==16395== Reachable blocks (those to which a pointer was found) are not
shown.
==16395== To see them, rerun with: --leak-check=full --show-reachable=yes
}}}
One would need to run some longer tests to see if this is just additional,
but constant crap from numpy or if the amount grows as we use it more.
Cheers,
Michael
--
Ticket URL: <http://trac.sagemath.org/sage_trac/ticket/3498#comment:14>
Sage <http://sagemath.org/>
Sage - Open Source Mathematical Software: Building the Car Instead of
Reinventing the Wheel
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