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Hybrid task scheduling: integrating static and dynamic heuristics

Researchers are constantly looking for ways to improve the execution time of parallel applications on distributed systems. Although compile-time static scheduling heuristics employ complex mechanisms, the quality of their schedules are handicapped by estimated run-time costs. On the other hand, while dynamic schedulers use actual run-time costs, they have to be of low complexity in order to reduce the scheduling overhead. We investigate the viability of integrating these two approaches into a hybrid scheduling framework. The relationship between static schedulers, dynamic heuristics and scheduling events are examined. The results show that a hybrid scheduler can indeed improve the schedules produced by good traditional static list scheduling algorithms.