Implementation of Parallel Algorithms

Abstract : This dissertation develops fast algorithms for solving closest point problems on parallel and vector computers. Algorithms for such problems have applications in many areas including statistical classification, crystallography, data compression, and finite element analysis. We present a simple and flexible programming model for designing and analyzing parallel algorithms. Also, fast parallel algorithms for nearest-neighbor searching and constructing Voronoi diagrams are described. Finally, we demonstrate that the algorithms actually obtain good performance on a wide variety of machine architectures, including the MasPar MP-1, Cray Y-MP and KSR-1 supercomputers.