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Energy-aware real-time scheduling on Heterogeneous Multi-Processor

机译:异构多处理器上的能量感知实时调度

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Heterogeneous Multi-Processor has been steadily gaining importance because of its potential energy efficiency compared to homogeneous multi-processor architectures. Many challenges for scheduling algorithms on heterogeneous multi-process are created during the shift from homogeneous multi-processor to heterogeneous architectures, especially for real-time applications. In this paper, we introduce an optimal algorithm, using energy-aware real-time scheduling, for multiple tasks on heterogeneous multi-core processors. We first propose an energy modelling from both dynamic and static energy perspectives, considering the parameters both of software and hardware levels. After that we propose a real-time scheduling policy of Optimal Job to a Fast Processor First (OJFPF) using the parameter of energy achieved from energy modelling, the length of tasks as well as the local priority to assign the priority to each task. Our simulation results show that OJFPF algorithm using the energy modelling significantly reduce the overall energy consumption and improve the performance.
机译:与同质多处理器体系结构相比,异质多处理器由于具有潜在的能源效率,因此一直在稳步提高重要性。从异构多处理器向异构体系结构转变期间,特别是对于实时应用,在异构多进程上调度算法面临许多挑战。在本文中,我们介绍了一种基于能量感知的实时调度的最佳算法,该算法可用于异构多​​核处理器上的多个任务。我们首先从动态和静态能源角度提出能源模型,同时考虑软件和硬件级别的参数。之后,我们使用从能量建模获得的能量参数,任务的长度以及为每个任务分配优先级的本地优先级,提出了“最佳作业到快速处理器优先(OJFPF)”的实时调度策略。我们的仿真结果表明,使用能量模型的OJFPF算法可显着降低总体能耗并提高性能。

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