vurtun

Gilbert–Johnson–Keerthi (GJK) 3D distance algorithm

The Gilbert–Johnson–Keerthi (GJK) distance algorithm is a method of determining the minimum distance between two convex sets. The algorithm's stability, speed which operates in near-constant time, and small storage footprint make it popular for realtime collision detection.

Unlike many other distance algorithms, it has no requirments on geometry data to be stored in any specific format, but instead relies solely on a support function to iteratively generate closer simplices to the correct answer using the Minkowski sum (CSO) of two convex shapes.

macton

// This file: https://gist.github.com/macton/4dd5fec2113be284796e
// See: Intel Intrinsics Guide  https://software.intel.com/sites/landingpage/IntrinsicsGuide/
// See: CPUID Explorer          http://www.flounder.com/cpuid_explorer1.htm
// See: Playing with cpuid      http://newbiz.github.io/cpp/2010/12/20/Playing-with-cpuid.html
// See: MSDN __cpuid, __cpuidex http://msdn.microsoft.com/en-us/library/hskdteyh.aspx
// See: Notes on MMX/SSE and a searchable table of intrinsics. http://www.taffysoft.com/pages/20120418-01.html
// See: AMD CPUID Specification http://amd-dev.wpengine.netdna-cdn.com/wordpress/media/2012/10/25481.pdf

#if defined(__GNUC__)
#include <stdint.h>