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An Efficient Greedy Scheduling Algorithm for Join Task Graphs in Heterogeneous Computing Systems

机译:一种高效的贪婪调度算法在异构计算系统中加入任务图

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Many previous algorithms for scheduling task graphs are mainly for homogeneous processors and ignore the economization on processors in real applications, which leads to low efficiency in practice. In this paper we presents a new insertion based greedy algorithm, called the HGS_J algorithm for scheduling join task graphs in heterogeneous computing systems, which schedules tasks according to the critical task and tries to insert the tasks having the larger amounts of the total costs of computation and communication to used faster processors while guaranteeing shorter schedule length and so improves the scheduling performance. The simulation results show that the proposed algorithm has the characteristics of shorter schedule length and less number of used processors than other compared algorithms.
机译:用于调度任务图的许多以前的算法主要用于均匀处理器,并忽略真实应用中处理器上的节电,这导致实践中的低效率。在本文中,我们提出了一种新的基于插入的贪婪算法,称为HGS_J算法,用于在异构计算系统中调度连接任务图,该算法根据关键任务计划任务,并试图插入具有更大数量计算成本的任务和通信使用更快的处理器,同时保证更短的时间表长度,因此提高了调度性能。仿真结果表明,该算法的特点是比其他比较算法更短的时间表长度和少量使用的处理器。

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