支持延迟敏感任务的可预测内存- cpu协同调度

Daniel Casini, P. Pazzaglia, Alessandro Biondi, M. Natale, G. Buttazzo
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引用次数: 10

摘要

多年来,人们提出了可预测的执行模型,通过将数据预加载到专用的本地内存中来实现实时任务的无争用执行。通过这种方式,可以通过委派DMA引擎在处理器执行的同时执行内存传输来隐藏内存访问延迟。然而,由于优先级反转,最先进的协议引入了额外的阻塞,这可能会严重惩罚对延迟敏感的应用程序,甚至与使用经典调度方案相比,会使系统的可调度性恶化。本文提出了一种新的协议,可以在减少优先级反转的同时隐藏内存传输延迟,从而有利于延迟敏感任务的可调度性。相应的分析被表述为一个优化问题。实验结果表明,与现有的解决方案相比,所提出的协议具有优势。
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Predictable Memory-CPU Co-Scheduling with Support for Latency-Sensitive Tasks
Predictable execution models have been proposed over the years to achieve contention-free execution of real-time tasks by preloading data into dedicated local memories. In this way, memory access delays can be hidden by delegating a DMA engine to perform memory transfers in parallel with processor execution. Nevertheless, state-of-the-art protocols introduce additional blocking due to priority inversion, which may severely penalize latency-sensitive applications and even worsen the system schedulability with respect to the use of classical scheduling schemes. This paper proposes a new protocol that allows hiding memory transfer delays while reducing priority inversion, thus favoring the schedulability of latency-sensitive tasks. The corresponding analysis is formulated as an optimization problem. Experimental results show the advantages of the proposed protocol against state-of-the-art solutions.
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