An Evolutionary Approach to Task Graph Scheduling

Authors:
Saeed Parsa;Shahriar Lotfi;Naser Lotfi
Affiliations:
Faculty of Computer Engineering, Iran University of Science and Technology, Tehran, Iran;Faculty of Computer Engineering, Iran University of Science and Technology, Tehran, Iran;Faculty of Computer Engineering, Iran University of Science and Technology, Tehran, Iran
Venue:
ICANNGA '07 Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part I
Year:
2007

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Abstract

Effective scheduling is of great importance to parallel programming environments. The aim is to minimize the completion time of task graphs. The completion time of a task graph is directly affected by the length of its critical path. Hence, the trend of an evolutionary approach for task graph scheduling can be biased towards reduction of the critical path. In this paper, a new genetic scheduling algorithm is presented. The algorithm, in the first priority, minimizes the critical path length of the parallel program task graph and in the second priority minimizes the inter-processor communication time. Thereby, it achieves a better scheduling in comparison with the existing approaches.