Hi Everyone, I recently opened a pull request for a pair of changes to improve the time and memory costs when registering types and I'd like to also solicit feedback from the list.
https://github.com/boostorg/python/pull/62 The brief summary is that there are a couple of places in the inheritance registration code that scale as O(N^2). For us, N has become large enough that Boost Python is showing up in our internal performance profiles during module imports. The larger of the two changes (b565ac4) switches the smart_graph structures to use a sparse representation. The original smart_graph behaves nicely when N is small and the graph is dense, but as N becomes large, the cost of initializing the table becomes significant. The sparse representation cuts memory usage from hundreds of megabytes down to tens of kilobytes. The second change (e1d2da5) is for those of us using standard libraries that implement std::list::size() in O(N) time, which results in num_edges on our graph also being in O(N). Adding casts is effectively quadratic due to the repeated calls to num_edges. Combined, these changes save ~400ms of application startup time on a 2.3GHz Haswell Xeon. Let me know if you have any questions or concerns, especially if you have performance targets that might be affected by these changes. John _______________________________________________ Cplusplus-sig mailing list Cplusplus-sig@python.org https://mail.python.org/mailman/listinfo/cplusplus-sig
