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Static Task Graph Scheduling in Real Time Homogenous Multiprocessor Systems Using Learning Automata

机译:使用学习自动机的实时同质多处理器系统中的静态任务图调度

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Multiprocessor system have widely application in parallel computation. one of the application is using them in real time systems. a job in multiprocessor real time systems divide in the set of the tasks with the relation between them in order that one task can be execute only when it's parents executed. by difficulty in scheduling the task graph and it's complexity, many effort accomplish for finding the best optimized solution. In this paper, we tried to have the balance between the processor and also reduce relation between the processor and importance of them we tried to improved the speed of getting the response. In most of the activity and experiment, the run time of the scheduling algorithm ignored. finally, the result of maintaining this solution show that we can have the appropriate schedule in acceptable time. also in this paper, at the end, we compared the proposal algorithm with the other famous scheduling algorithm.
机译:多处理器系统在并行计算中有着广泛的应用。应用程序之一是在实时系统中使用它们。多处理器实时系统中的一项工作将任务集与它们之间的关系进行划分,以使一个任务仅在其父项执行时才能执行。由于难以安排任务图及其复杂性,因此为找到最佳的优化解决方案需要付出很多努力。在本文中,我们试图在处理器之间取得平衡,并减少处理器与处理器之间的关系,并尝试提高响应速度。在大多数活动和实验中,调度算法的运行时间都被忽略了。最后,维持该解决方案的结果表明,我们可以在可接受的时间内制定适当的时间表。同样在本文的最后,我们将提案算法与其他著名的调度算法进行了比较。

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