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Scheduling of Periodic Tasks with Data Dependency on Multiprocessors

机译:对多处理器数据依赖性的定期任务的调度

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This article studies the scheduling problem of a set of tasks with time or data constraints on a number of identical processors with full connections. We present an algorithm, in which a set of static schedule lists can be obtained, each for a processor, such that each task starts executing after its release time and completes its computation before its deadline, and all the precedence relations between tasks resulting from data dependency are satisfied. The data dependency relations between tasks are represented by Synchronous Dataflow Graphs (SDF) as they can indicate tasks' concurrency and enable effective scheduling on multiprocessor platforms. The SDF, however, does not support the time constraints of tasks directly, thus an adaption is applied to conform to the time limits. With this adaption, the periodic tasks of implicit-deadline or constrained-deadline can be scheduled on multiprocessor platform effectively.
机译:本文研究了一系列任务的调度问题,其中包含具有完整连接的多个相同处理器的时间或数据约束。我们呈现了一种算法,其中可以获得一组静态计划列表,每个静态计划列表对于处理器,使得每个任务开始在其发布时间之后执行,并在其截止日期之前完成其计算,以及由数据产生的任务之间的所有优先关系依赖性满意。任务之间的数据依赖关系是由同步数据流图(SDF)表示的,因为它们可以指示任务的并发性并在多处理器平台上启用有效调度。然而,SDF不支持直接任务的时间约束,因此应用了适应性以符合时间限制。通过这种调整,可以有效地调度隐式截止日期或约束截止日期的周期性任务。

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