Corrfunc is a set of high-performance routines to measure clustering statistics. The main features of Corrfunc are:
Fast All theory pair-counting is at least an order of magnitude faster than all existing public codes. Particularly suited for MCMC.
OpenMP Parallel All pair-counting codes can be done in parallel (with strong scaling efficiency >~ 95% up to 10 cores)
Python Extensions Python extensions allow you to do the compute-heavy bits using C while retaining all of the user-friendliness of python.
Modular The code is written in a modular fashion and is easily extensible to compute arbitrary clustering statistics.
Future-proof As I get access to newer instruction-sets, the codes will get updated to use the latest and greatest CPU features.
The source code is publicly available at https://github.com/manodeep/Corrfunc.