An associative static and dynamic convex hull algorithm

This paper presents a new static and dynamic recursive parallel algorithm for the convex hull problem. This algorithm is a parallel adaptation of the Graham Scan and Quick Hull algorithms. The computational model selected for this algorithm is the associative computing model (ASC) which supports massive parallelism through the use of data parallelism and constant time associative search and maximum functions. Also, ASC can be supported on existing SIMD computers. The static algorithm requires O(n) space, O(log n) average case running time, and O(n) worst case running time. If O(log n) ISs are used the, static algorithm should have an average running time of O(log log n).