A low complexity algorithm for dynamic scheduling of independent tasks onto heterogeneous computing systems

Authors:
Prashanth C SaiRanga;Sanjeev Baskiyar
Affiliations:
Auburn University, Auburn, AL;Auburn University, Auburn, AL
Venue:
Proceedings of the 43rd annual Southeast regional conference - Volume 1
Year:
2005

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Abstract

Scheduling a set of independent tasks onto a network of heterogeneous computing systems to minimize the overall execution time is NP-hard. Among the algorithms that have been proposed in the past, the Sufferage algorithm [5] has the best performance in minimizing the makespan of a set of independent tasks. We propose a new low complexity scheduling algorithm, Heterogeneous Largest Task First (HLTF). Its complexity is O(s(Log s + m)) vs. O(s2*m) of Sufferage, where s is the number of tasks and m is the number of available machines. Simulation results reveal that in terms of minimizing the makespan, the performance of HLTF is slightly better than that of the Sufferage algorithm. In terms of running cost, HLTF significantly outperforms the Sufferage algorithm.