view .hgsigs @ 5363:058e93c3d07d

I have spotted the biggest bottleneck in "bdiff.c". Actually it was pretty easy to find after I recompiled the python interpreter and mercurial for profiling. In "bdiff.c" function "equatelines" allocates the minimum hash table size, which can lead to tons of collisions. I introduced an "overcommit" factor of 16, this is, I allocate 16 times more memory than the minimum value. Overcommiting 128 times does not improve the performance over the 16-times case.
author Christoph Spiel <cspiel@freenet.de>
date Thu, 27 Sep 2007 23:57:57 -0500
parents cf8b8f62688a
children 5d8f5ad45c12
line wrap: on
line source

35fb62a3a673d5322f6274a44ba6456e5e4b3b37 0 iD8DBQBEYmO2ywK+sNU5EO8RAnaYAKCO7x15xUn5mnhqWNXqk/ehlhRt2QCfRDfY0LrUq2q4oK/KypuJYPHgq1A=
2be3001847cb18a23c403439d9e7d0ace30804e9 0 iD8DBQBExUbjywK+sNU5EO8RAhzxAKCtyHAQUzcTSZTqlfJ0by6vhREwWQCghaQFHfkfN0l9/40EowNhuMOKnJk=
36a957364b1b89c150f2d0e60a99befe0ee08bd3 0 iD8DBQBFfL2QywK+sNU5EO8RAjYFAKCoGlaWRTeMsjdmxAjUYx6diZxOBwCfY6IpBYsKvPTwB3oktnPt5Rmrlys=
27230c29bfec36d5540fbe1c976810aefecfd1d2 0 iD8DBQBFheweywK+sNU5EO8RAt7VAKCrqJQWT2/uo2RWf0ZI4bLp6v82jACgjrMdsaTbxRsypcmEsdPhlG6/8F4=
fb4b6d5fe100b0886f8bc3d6731ec0e5ed5c4694 0 iD8DBQBGgHicywK+sNU5EO8RAgNxAJ0VG8ixAaeudx4sZbhngI1syu49HQCeNUJQfWBgA8bkJ2pvsFpNxwYaX3I=