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Resource-Aware Partitioned Scheduling for Heterogeneous Multicore Real-Time Systems

机译:异构多核实时系统的资源感知分区调度

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Heterogeneous multicore processors have become popular computing engines for modern embedded real-time systems recently. However, there is rather limited research on the scheduling of real-time tasks running on heterogeneous multicore systems with shared resources. Note that, different partitionings of tasks upon heterogeneous cores can affect the synchronization overheads of tasks (and thus the system schedulability). Focusing on the partitioned-EDF scheduling and resource access protocol MSRP (Multiprocessor Stack Resource Policy), this paper proposes an effective synchronization aware task partitioning algorithm for heterogeneous multicores (SA-TPA-HM). Several resource-oriented heuristics are exploited to tighten the bound on the synchronization costs of tasks through dynamic task prioritization and to find an appropriate core for each task that can minimize the system utilization increment. The simulation results show that our proposed SA-TPA-HM scheme can achieve higher acceptance ratio (e.g., 60% more), when compared to the existing schemes designed for homogeneous multicores.
机译:异构多核处理器最近已成为现代嵌入式实时系统的流行计算引擎。但是,关于在具有共享资源的异构多核系统上运行的实时任务的调度的研究非常有限。请注意,异构内核上任务的不同分区可能会影响任务的同步开销(从而影响系统的可调度性)。针对分区EDF调度和资源访问协议MSRP(多处理器堆栈资源策略),本文提出了一种有效的针对异构多核的同步感知任务划分算法(SA-TPA-HM)。利用几种面向资源的启发式方法,通过动态任务优先级来加强任务同步成本的界限,并为每个任务找到合适的核心,以最大程度地减少系统利用率。仿真结果表明,与为同类多核设计的现有方案相比,我们提出的SA-TPA-HM方案可以实现更高的接受率(例如,提高60%)。

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