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Precise micro-architectural modeling for WCET analysis via AI#x002B;SAT

机译:通过AI&#x002b进行WCET分析的精确微架构模型;坐了

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Hard real-time systems are required to meet critical deadlines. Worst case execution time (WCET) is therefore an important metric for the system level schedulability analysis of hard real-time systems. However, performance enhancing features of a processor (e.g. pipeline, caches) makes WCET analysis a very difficult problem. In this paper, we propose a novel approach to combine abstract interpretation (AI) and satisfiability (SAT) checking (hence the name AI+SAT) for different varieties of micro-architectural modeling. Our work in this paper is inspired by the research advances in program flow analysis(e.g. infeasible path analysis). We show that the accuracy of WCET estimates can be improved in a scalable fashion by using SAT checkers to integrate infeasible path analysis results into micro-architectural modeling. Our modeling is implemented on top of the Chronos WCET analysis tool and we improve the accuracy of WCET estimates for instruction cache, data cache, branch predictors and shared caches.
机译:需要硬实时系统来满足关键的截止日期。因此,最坏的情况执行时间(WCET)是硬实时系统的系统级别调度分析的重要指标。但是,处理器的性能增强功能(例如管道,缓存)使WCET分析成为一个非常困难的问题。在本文中,我们提出了一种新的方法来结合抽象解释(AI)和可靠性(SAT)检查(因此AI+ sat)用于不同品种的微架构建模。我们本文的工作是通过计划流程分析的研究进展的启发(例如,不可行的路径分析)。我们表明,通过使用SAT检查器可以以可扩展的方式改进WCET估计的准确性,以将不可行的路径分析结果集成为微型架构建模。我们的建模是在Chronos WCET分析工具的顶部实现,我们提高了WCET估计的指令缓存,数据缓存,分支预测器和共享缓存的准确性。

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