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Reducing Memory Interference Latency of Safety-Critical Applications via Memory Request Throttling and Linux Cgroup

机译:通过内存请求限制和Linux Cgroup减少安全关键型应用程序的内存干扰延迟

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With the advent of high-performance multicore processors that operate under a limited power budget, dedicated low-end microprocessors with different levels of criticality are rapidly consolidated into a mixed-criticality system. One of the major challenges in designing such a mixed-criticality system is to tightly control the amount of resource contention for a critical application by effectively limiting its performance interference incurred due to sharing resources with non-critical tasks. In this paper, we propose application-aware dynamic memory request throttling to reduce the memory interference latency of a critical application in a dual criticality system. Our approach carefully differentiates critical task instances from normal task instances and groups them into the critical and normal cgroup, respectively. It then predicts the occurrence of excessive memory contention under critical task execution and then throttles memory requests generated by the normal cgroup via the CPUFreq governor when necessary. We have implemented the approach on the NVIDIA Jetson TX2 with Linux kernel 4.4.38. Experimental results show that the proposed approach reduces the end-to-end latency of a critical application up to 9.49% while incurring only negligible overhead.
机译:随着在有限的功率预算下运行的高性能多核处理器的出现,具有不同关键级别的专用低端微处理器迅速集成到了混合关键系统中。设计这样的混合关键性系统的主要挑战之一是通过有效地限制由于与非关键任务共享资源而引起的性能干扰来严格控制关键应用程序的资源争用量。在本文中,我们提出了可感知应用程序的动态内存请求限制,以减少双关键系统中关键应用程序的内存干扰等待时间。我们的方法仔细区分了关键任务实例和正常任务实例,并将它们分别分为关键和正常cgroup。然后,它预测在关键任务执行下会发生过多的内存争用,然后在必要时通过CPUFreq调控器限制正常cgroup生成的内存请求。我们已经在具有Linux内核4.4.38的NVIDIA Jetson TX2上实现了该方法。实验结果表明,该方法将关键应用程序的端到端延迟降低了9.49%,而仅产生了可忽略的开销。

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