电磁云计算的多目标任务调度算法研究

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Abstract With the development of cloud computing in the field of high-performance computing, large-scale electromagnetic finite element and multi-sample computing are gradually completed by cloud computing. Therefore, cloud computing task scheduling, especially multi-target task scheduling, has become an important issue to be solved. The multi-objective task scheduling algorithm optimizes the three objectives of maximum computing completion time, total machine load and maximum machine load. In this paper, Aiming at the indivisibility of electromagnetic finite element single sample computation, a multi-group hybrid algorithm is proposed. Making use of multi-attribute decision model based on weighted grey target to select the most satisfied cloud platform task scheduling solution. This paper obtains the optimal CPU core number and memory allocation by running three cases of finite element calculation on the cloud platform. The feasibility and effectiveness of the algorithm are verified by test benchmarks and actual cases. The finite element efficient calculation and the full utilization of resources are realized on the cloud platform.

Key words： cloud computing finite element method multi-objective evolutionary algorithm task scheduling weighted multi-attribute grey target decision model

Received: 29 October 2019 Published: 16 April 2020

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	Articles by authors
	Jin Liang
	Wang Jingtao
	Liu Xiangzhen
	Feng Wei

Cite this article:

Jin Liang,Wang Jingtao,Liu Xiangzhen等. Research on multi-objective task scheduling algorithm for electromagnetic cloud computing[J]. Electrical Engineering, 2020, 21(4): 44-49.

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http://dqjs.cesmedia.cn/EN/Y2020/V21/I4/44

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