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Mapping DAG-Based Power System Computing and Simulation Applications to Grid

In this paper, we focus on the scheduling issue for one kind of high performance computing applications, that is, power system computing and simulation (PCS) applications. PCS applications contain sub-jobs depending on each other, which can be represented as a DAG. Those sub-jobs often require specific grid resource. Efficient and robust scheduling algorithm have to be developed that can cope with a high number of competing and demanding applications, the inherent resource heterogeneity and the often limited view on resource availability. We present a heuristic scheduling algorithm that is based on a well-known list scheduling algorithm. It utilizes the job and machine calculability, and supports resource reservation. The proposed algorithm is implemented within a grid simulation framework. An extensive simulation study was conducted to evaluate and compare the performance of the algorithm. It showed the general suitability of our enhanced list scheduling heuristics within heterogeneous grid environments.