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Iterative list scheduling for heterogeneous computing
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DOI：10.1016/j.jpdc.2005.01.002.png)
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Abstract
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Optimal scheduling of parallel applications on distributed computing systems represented by directed acyclic graph (DAG) is NP-complete in the general case. List scheduling is a very popular heuristic method for DAG-based scheduling. However, it is more suited to homogenous distributed computing systems. This paper presents an iterative list scheduling algorithm to deal with scheduling on heterogeneous computing systems. The main idea in this iterative scheduling algorithm is to improve the quality of the schedule in an iterative manner using results from previous iterations. The algorithm first uses the heterogeneous earliest-finish-time (HEFT) algorithm to find an initial schedule and iteratively improves it. Hence the algorithm can potentially produce shorter schedule length. The simulation results show that in the majority of the cases, there is significant improvement to the initial schedule. The algorithm is also found to perform best when the tasks to processors ratio is large. (c) 2005 Elsevier Inc. All rights reserved.
Keywords:
task scheduling
heterogeneous computing systems
list scheduling
randomly generated DAGs
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