Understanding the Interplay between Hardware Errors and User Job Characteristics on the Titan Supercomputer

Seung-Hwan Lim, Ross G. Miller, Sudharshan S. Vazhkudai
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引用次数: 1

Abstract

Designing dependable supercomputers begins with an understanding of errors in real-world, large-scale systems. The Titan supercomputer at Oak Ridge National Laboratory provides a unique opportunity to investigate errors when an actual system is actively used by multiple concurrent users and workloads from diverse domains at varying scales. This study presents a thorough analysis of 6, 908, 497 hardware errors from 18, 688 compute nodes of Titan for 312, 215 user jobs over a 3-year time period. Through careful joining of two system logs – the Machine Check Architecture (MCA) log and the job scheduler log – we show the correlated pattern of hardware errors for each job and user, in addition to individual descriptive statistics of errors, jobs, and users. Since the majority of hardware errors are memory errors, this study also shows the importance of error correcting in memory systems.
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了解Titan超级计算机上硬件错误与用户作业特征之间的相互作用
设计可靠的超级计算机首先要了解现实世界中大规模系统中的错误。橡树岭国家实验室(Oak Ridge National Laboratory)的Titan超级计算机提供了一个独特的机会,可以在实际系统被来自不同领域、不同规模的多个并发用户和工作负载积极使用时调查错误。这项研究对Titan的18,688个计算节点的6,908,497个硬件错误进行了全面的分析,这些错误在3年的时间里用于312,215个用户作业。通过仔细地连接两个系统日志——Machine Check Architecture (MCA)日志和作业调度器日志——我们显示了每个作业和用户的硬件错误的相关模式,以及对错误、作业和用户的单独描述性统计数据。由于大多数硬件错误是内存错误,本研究也显示了内存系统纠错的重要性。
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