Randomized incremental constructions are widely used in computational geometry, but they perform very badly on large data because of their inherently random memory access patterns. We define a biased randomized insertion order which removes enough randomness to significantly improve performance, but leaves enough randomness so that the algorithms remain theoretically optimal.
Issue Date
2003-06-01
Language
ENG
Citation
SCG '03 Proceedings of the nineteenth annual symposium on Computational geometry, pp.211 - 219