Iterative Data Partitioning Scheme of Parallel PDE Solver for Heterogeneous Computing Cluster

Shuichi Ichikawa and Yoshikatsu Fujimura

Department of Knowledge-based Information Engineering,
Toyohashi University of Technology
Hibarigaoka, Tempaku, Toyohashi, Aichi 441-8580, JAPAN

Proceedings of IASTED International Conference Applied Informatics: International Symposium on Parallel and Distributed Computing and Networks, ACTA Press, pp. 364--369 (2002).


This paper presents a static load balancing scheme for a parallel PDE solver targeting heterogeneous computing clusters. The proposed scheme adopts a mathematical programming approach and optimizes the execution time of the PDE solver, considering both computation and communication time. While traditional task graph scheduling algorithms only distribute loads to processors, the proposed scheme adopts a combined approach of iterative data partitioning and load distribution to make total execution time minimal. The approximation algorithm presented here shows good accuracy and is solvable in practical time.