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Context-Aware TLB Preloading for Interference Reduction in Embedded Multi-Tasked Systems

机译:上下文感知TLB预加载嵌入式多任务系统中的干扰减少

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Rapid system responsiveness and execution time predictability are of significant importance for a large class of real-time embedded systems. Multi-tasking leads to interference in the shared processor resources such as caches and TLBs, which in turn results in not only deteriorated performance but also, and for some applications even more importantly, highly suboptimal worst-case execution time (WCET) estimates due to the interference unpredictability. We present a methodology for task-aware D - TLB interference reduction sad preloading through an application-specific task's state introspection at context-switch time for embedded multitasking. The proposed technique addresses the problem through a synergis-tic cooperation between the compiler, for an application-specific analysis of the task's context, and the OS, for a run-time introspection of the context and an efficient identification of TLB entries of current (live) and of "near-future" usage.
机译:快速系统响应性和执行时间可预测性对于大类实时嵌入式系统而言具有重要意义。多任务导致共享处理器资源(如缓存和TLB)的干扰,这又导致性能恶化,而且对于某些应用程序,以及更重要的是,由于甚至更重要地,高度次优的最坏情况执行时间(WCET)估计干扰不可预测性。我们通过在嵌入式多任务处理的上下文 - 切换时间下,通过应用程序特定的任务的状态内向量提出了一种任务感知D-TLB干扰减少悲伤预加载的方法。所提出的技术通过编译器之间的协同性协同合作来解决问题,用于对任务的上下文的特定于应用程序的上下文分析以及操作系统,用于上下文的运行时内部的运行时间和当前TLB条目的有效识别(生活)和“近期”使用。

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