评估用于超级计算机测井分析的时间聚合技术

C. Martino, M. Cinque, Domenico Cotroneo
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引用次数: 37

摘要

本文提出了一种评估时间聚结技术的新方法。这些技术被广泛用于重建系统的故障过程,并从事件日志中估计可靠性测量值。该方法基于使用自动生成的日志,并伴随着对故障过程的地面真相的准确了解。通过将通过合并重建的假定失效过程与实际情况进行比较,从而进行评估。我们主要关注超级计算机日志,因为自动事件日志分析对这些系统的重要性日益增加。实验结果表明,该方法可以比较不同的时间聚结技术,并根据给定的系统设置识别它们的弱点。此外,结果还揭示了由聚结引起的误差与可靠性测量估计误差之间的有趣相关性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Assessing time coalescence techniques for the analysis of supercomputer logs
This paper presents a novel approach to assess time coalescence techniques. These techniques are widely used to reconstruct the failure process of a system and to estimate dependability measurements from its event logs. The approach is based on the use of automatically generated logs, accompanied by the exact knowledge of the ground truth on the failure process. The assessment is conducted by comparing the presumed failure process, reconstructed via coalescence, with the ground truth. We focus on supercomputer logs, due to increasing importance of automatic event log analysis for these systems. Experimental results show how the approach allows to compare different time coalescence techniques and to identify their weaknesses with respect to given system settings. In addition, results revealed an interesting correlation between errors caused by the coalescence and errors in the estimation of dependability measurements.
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