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A Monte Carlo algorithm for real time task scheduling on multi-core processors with software controlled dynamic voltage scaling

机译:用于软件控制动态电压缩放的多核处理器上实时任务调度的蒙特卡洛算法

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The task scheduling problem for multi-core processors is an important algorithm design issue. Dynamic voltage scaling (DVS) is used to reduce the energy consumption of cores. We ponder the problem of task scheduling on a multi-core processor with software controlled DVS where the objective is to reduce the energy consumption. We consider a system with a single multi-core processor with software controlled DVS having a finite set of core speeds and discuss a task scheduling problem associated with it. The problem that we address is to find a minimum energy task schedule for a given set of independent tasks that have to be completed within a given common deadline. We propose a Monte Carlo algorithm of complexity O(t(mp + q + log(t)) + p(t + q)(D~(pq) + n)) for solving the task scheduling problem and compare it with the optimal algorithm. Here r is the number of tasks, p is the number of cores, q is the number of core speeds, m is an integer parameter that is the number of iterations we should try to get a feasible solution before declaring that no solution is possible, n is an integer parameter that is the number of iterations we should try to reduce the energy consumption when we get a feasible solution, and D is the common deadline of the tasks.
机译:多核处理器的任务调度问题是重要的算法设计问题。动态电压缩放(DVS)用于减少内核的能耗。我们考虑在具有软件控制的DVS的多核处理器上执行任务调度的问题,其目的是降低能耗。我们考虑具有单个多核处理器且软件控制的DVS具有有限的核心速度集的系统,并讨论与之相关的任务调度问题。我们要解决的问题是为必须在给定的共同期限内完成的一组给定的独立任务找到最小的能源任务时间表。我们提出了一种复杂度为O(t(mp + q + log(t))+ p(t + q)(D〜(pq)+ n))的蒙特卡罗算法来解决任务调度问题并将其与最优算法进行比较算法。这里r是任务数,p是核心数,q是核心速度数,m是一个整数参数,它是在声明没有可能的解决方案之前我们应该尝试获得可行解决方案的迭代次数, n是一个整数参数,它是获得可行解决方案时应尝试减少能耗的迭代次数,D是任务的常见截止日期。

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