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

S. Ichikawa and Y. Fujimura (Japan)


: Optimization, Load balancing, Schedul ing, Cluster computing


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 iter ative 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.

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