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