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A static task scheduling algorithm for heterogeneous systems based on merging tasks and critical tasks

机译:基于合并任务和关键任务的异构系统静态任务调度算法

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A novel task scheduling algorithm called Merge Tasks and Predict Earliest Finish Time (MTPEFT) has been proposed for static task scheduling in a heterogeneous computing environment. The algorithm merges tasks satisfying constraints and assigns the best processor for the node that has at least one immediate successor as the critical node, thereby effectively reducing the schedule length without increasing the algorithm time complexity. Experiments regarding aspects of randomly generated graphs and real-world application graphs are performed, and comparisons are made based on the scheduling length ratio, robustness and frequency of the best result. The results show that the MTPEFT algorithm outperforms the PEFT, CPOP and HEFT algorithms in terms of the schedule length ratio, frequency of the best result and robustness while maintaining the same time complexity.
机译:提出了一种新颖的任务调度算法,称为“合并任务和预测最早完成时间”(MTPEFT),用于异构计算环境中的静态任务调度。该算法合并满足约束的任务,并为具有至少一个直接后继节点的节点分配最佳处理器作为关键节点,从而在不增加算法时间复杂度的情况下有效地减少了调度时间。进行了有关随机生成的图和实际应用图的各个方面的实验,并根据调度长度比率,鲁棒性和最佳结果的频率进行了比较。结果表明,MTPEFT算法在调度长度比,最佳结果的频率和鲁棒性方面都优于PEFT,CPOP和HEFT算法,同时保持了相同的时间复杂度。

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