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Real-Time Scheduling and Analysis of Synchronous OpenMP Task Systems with Tied Tasks

机译:具有捆绑任务的同步OpenMP任务系统的实时调度和分析

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Synchronous parallel tasks are widely used in HPC for purchasing high average performance, but merely consider how to guarantee good timing predictabilities. OpenMP is a promising framework for multi-core real-time embedded systems. The synchronous OpenMP tasks are significantly more difficult to schedule and analyze due to constraints posed by OpenMP specifications. An important OpenMP feature is tied task, which must execute on the same thread during the whole life cycle. This paper designs a novel method, called group scheduling, to schedule synchronous OpenMP tasks, which divides tasks into several groups, and assigns some of them to dedicated cores, in order to isolate tied tasks. We derive a linear-time computable response time bound. Experiments with both randomly generated and realistic OpenMP tasks show that our new bound significantly outperforms the existing bound.
机译:同步并行任务在HPC中广泛用于购买高平均性能,但仅考虑如何保证良好的时序可预测性。 OpenMP是用于多核实时嵌入式系统的有前途的框架。由于OpenMP规范的限制,同步的OpenMP任务很难安排和分析。 OpenMP的一项重要功能是绑定任务,该任务必须在整个生命周期内在同一线程上执行。本文设计了一种新的方法,称为组调度,以调度同步的OpenMP任务,该任务将任务划分为几个组,并将其中一些分配给专用内核,以隔离绑定的任务。我们导出了线性时间可计算的响应时间范围。对随机生成的和实际的OpenMP任务进行的实验表明,我们的新界限明显优于现有界限。

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