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Insights into the Diagnosis of System Failures from Cluster Message Logs

机译:从群集消息日志中诊断系统故障的诊断

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Large cluster systems are composed of complex, interacting hardware and software components. Components, or the interactions between components, may fail due to many different reasons, leading to the eventual failure of executing jobs. This paper investigates an open question about failure diagnosis: What are the characteristics of the errors that lead to cluster system failures? To this end, this paper gives a systematic process for identifying and characterizing the root-causes of failures. We applied an extended version of the FDiagV3 diagnostics toolkit to the log-files of the Ranger and Lonestar supercomputers. Our results show that: (i) failures were a result of recurrent issues and errors, (ii) a small set of nodes are associated with these issues and errors, and (iii) Ranger and Lonestar display similar sets of problems. FDiagV3 will be put in the public domain for support of failure diagnosis for large cluster systems in May, 2015.
机译:大型集群系统由复杂,交互硬件和软件组件组成。组件或组件之间的相互作用可能由于许多不同的原因而失败,导致执行作业的最终失败。本文调查了有关失败诊断的开放问题:导致群集系统故障的错误的特征是什么?为此,本文提供了识别和表征故障根本原因的系统过程。我们将FDIAGV3诊断工具包的扩展版本应用于Ranger和Lonestar超级计算机的日志文件。我们的结果表明:(i)失败是经常发生的问题和错误的结果,(ii)一小组节点与这些问题和错误相关联,(iii)游侠和Lonestar显示类似的问题。 FDIAGV3将投入公共领域,以支持2015年5月的大集群系统的失败诊断。

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