Hybrid Approach to HPC Cluster Telemetry and Hardware Log Analytics

2020 IEEE High Performance Extreme Computing Conference (HPEC)(2020)

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摘要
The number of computer processing nodes and processor cores in cluster systems is growing rapidly. Discovering, and reacting to, a hardware or environmental issue in a timely manner enables proper fault isolation, improves quality of service, and improves system up-time. In the case of performance impacts and node outages, RAS policies can direct actions such as job quiescence or migration. Additionally, power consumption, thermal information, and utilization metrics can be used to provide cluster energy and cooling efficiency improvements as well as optimized job placement. This paper describes a highly scalable telemetry architecture that allows event aggregation, application of RAS policies, and provides the ability for cluster control system feedback. The architecture advances existing approaches by including both programmable policies, which are applied as events stream through the hierarchical network to persistence storage, and treatment of sensor telemetry in an extensible framework. This implementation has proven robust and is in use in both cloud and HPC environments including the Summit system of 4,608 nodes at Oak Ridge National Laboratory [5].
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关键词
hybrid approach,HPC cluster telemetry,hardware log analytics,computer processing nodes,cluster systems,fault isolation,quality of service,node outages,RAS policies,job quiescence,power consumption,thermal information,utilization metrics,cluster energy,cooling efficiency improvements,optimized job placement,highly scalable telemetry architecture,event aggregation,cluster control system feedback,programmable policies,sensor telemetry,cloud computing,summit system
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