[Numpy-discussion] Numpy's policy for releasing memory

[Austin Bingham]

I'm trying to understand how numpy decides when to release memory and
whether it's possible to exert any control over that. The situation is that
I'm profiling memory usage on a system in which a great deal of the overall
memory is tied up in ndarrays. Since numpy manages ndarray memory on its
own (i.e. without the python gc, or so it seems), I'm finding that I can't
do much to convince numpy to release memory when things get tight. For
python object, for example, I can explicitly run gc.collect().

So, in an effort to at least understand the system better, can anyone tell
me how/when numpy decides to release memory? And is there any way via
either the Python or C-API to explicitly request release? Thanks.

Austin
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mail.python.org/pipermail/numpy-discussion/attachments/20121113/e9cddc7d/attachment.html>