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[JULIA] Faster than CGAL Delaunay

TL;DR

DelaunayJL is an incremental 2D Delaunay triangulation algorithm implemented in Julia, it is robust and ~20% faster than CGAL, the C++ de-facto industry standard. And it's MIT Licensed! all links to code are below

Show me the data!

The figure below shows how much time it takes to run a benchmark on my computer, an Intel Core i7-4800MQ CPU @ 2.7Ghz, 16GB RAM, Win8 64bit. The benchmark consists of inserting a number of points uniformly distributed. The benchmark is run 5 times for each number of points once for CGAL and once for Julia. The numbers of points used are 10K, 100K, 1M, and 10M. CGAL v4.4 was compiled with VS2013 64bit release mode, Julia is of version 0.3.0 Commit 7681878 (2014-08-20 20:43 UTC) x86_64-w64-mingw32 the delaunay code is here (see other gists of mine for complementing files... I'll compile this all into a library when I have the time)