Parallelization alternatives and their performance for the convex hull problem

High performance machines have become available nowadays to an increasing number of researchers. Most of us might have both an access to a supercomputing center and an algorithm that could benefit from these high performance machines. The aim of the present work is to revisit all existing parallelization alternatives, including emerging technologies like software-only speculative parallelization, to solve on different architectures the same representative problem: The computation of the convex hull of a point set.