诊断NFS错误:从网桥的Syslog分析的初步发现

P. Choudhary, R. Sooriamurthi, J. R. Scott, Ed Hanna, J. Sommerfield, A. Kar
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引用次数: 0

摘要

Bridges是匹兹堡超级计算中心目前的主要系统。考虑到系统的复杂性及其使用量,它是探索机器学习技术在研究次优性能方面的潜力的一个非常好的环境。这篇简短的报告讨论了一名新研究生探索这一新颖领域的初步和正在进行的工作。我们最初的重点是学习如何从之前的syslog消息中预测NFS超时错误的发生。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Diagnosing NFS errors: Preliminary Findings from a Syslog Analysis of Bridges
Bridges is the current main system at the Pittsburgh Supercomputing Center. Given the complexity of the system and the volume of its use, it is a very good environment for exploring the potential of machine learning techniques in studying sub-optimal performance. This short report discusses preliminary and ongoing work of a new graduate student exploring this novel realm. Our initial focus has been on learning to predict the occurrence of NFS time out errors from preceding syslog messages.
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