Measurement-Based Probabilistic Timing Analysis for Multi-path Programs

L. Cucu-Grosjean, L. Santinelli, Michael Houston, Code Lo, T. Vardanega, Leonidas Kosmidis, J. Abella, E. Mezzetti, E. Quiñones, F. Cazorla
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引用次数: 260

Abstract

The rigorous application of static timing analysis requires a large and costly amount of detail knowledge on the hardware and software components of the system. Probabilistic Timing Analysis has potential for reducing the weight of that demand. In this paper, we present a sound measurement-based probabilistic timing analysis technique based on Extreme Value Theory. In all the experiments made as part of this work, the timing bounds determined by our technique were less than 15% pessimistic in comparison with the tightest possible bounds obtainable with any probabilistic timing analysis technique. As a point of interest to industrial users, our technique also requires a comparatively low number of measurement runs of the program under analysis, less than 650 runs were needed for the benchmarks presented in this paper.
基于测量的多路径程序概率时序分析
静态时序分析的严格应用需要大量且昂贵的关于系统硬件和软件组件的详细知识。概率时序分析有可能减少这种需求的权重。本文提出了一种基于极值理论的基于声波测量的概率时序分析技术。在作为这项工作的一部分所做的所有实验中,与任何概率时序分析技术可获得的最严格的可能界限相比,我们的技术确定的时序界限的悲观程度小于15%。作为工业用户感兴趣的一点,我们的技术还需要相对较低数量的正在分析的程序的测量运行,本文中提供的基准测试所需的运行少于650次。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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