Tightening the Bounds on Feasible Preemption Points

H. Ramaprasad, F. Mueller
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引用次数: 54

Abstract

Caches have become invaluable for higher-end architectures to hide, in part, the increasing gap between processor speed and memory access times. While the effect of caches on timing predictability of single real-time tasks has been the focus of much research, bounding the overhead of cache warm-ups after preemptions remains a challenging problem, particularly for data caches. This paper makes multiple contributions. 1) We bound the penalty of cache interference for real-time tasks by providing accurate predictions of data cache behavior across preemptions, including instruction cache and pipeline effects. We show that, when considering cache preemption, the critical instant does not occur upon simultaneous release of all tasks. 2) We develop analysis methods to calculate upper bounds on the number of possible preemption points for each job of a task. To make these bounds tight, we consider the entire range between the best-case and worst-case execution times (BCET and WCET) of higher priority jobs. The effects of cache interference are integrated into the WCET calculations by using a feedback mechanism to interact with a static timing analyzer. Significant improvements in tightening bounds of up to an order of magnitude over two prior methods and up to half a magnitude over a third prior method are obtained by experiments for (a) the number of preemptions, (b) the WCET and (c) the response time of a task. Overall, this work contributes by calculating the worst-case preemption delay under consideration of data caches
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收紧可行抢占点的界限
对于高端架构来说,缓存已经变得非常有价值,在某种程度上,它可以隐藏处理器速度和内存访问时间之间越来越大的差距。虽然缓存对单个实时任务的时间可预测性的影响一直是许多研究的焦点,但在抢占后限制缓存预热的开销仍然是一个具有挑战性的问题,特别是对于数据缓存。本文做出了多方面的贡献。1)我们通过提供跨抢占的数据缓存行为的准确预测(包括指令缓存和管道效应)来约束实时任务的缓存干扰惩罚。我们表明,当考虑缓存抢占时,关键时刻不会在同时释放所有任务时发生。2)我们开发了分析方法来计算一个任务的每个作业可能的抢占点数量的上界。为了使这些界限更紧密,我们考虑了高优先级作业的最佳情况和最坏情况执行时间(BCET和WCET)之间的整个范围。通过使用反馈机制与静态定时分析仪交互,将缓存干扰的影响集成到WCET计算中。通过实验(a)抢占数,(b) WCET和(c)任务的响应时间,在收紧边界方面取得了显著的改进,比两种先前的方法提高了一个数量级,比第三种先前的方法提高了半个数量级。总的来说,这项工作通过计算考虑数据缓存的最坏情况下的抢占延迟做出了贡献
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