Global Experiences with HPC Operational Data Measurement, Collection and Analysis
- Leibniz Supercomputing Centre
- ORNL
- Lawrence Berkeley National Laboratory (LBNL)
- Hewlett Packard Enterprise
- Energy Efficient HPC Working Group
As we move into the exascale era, supercomputers grow larger, denser, more heterogeneous, and ever more complex. Operating such machines reliably and efficiently requires deep insight into the operational parameters of the machine itself as well as its supporting infrastructure. To fulfill this need, early adopter sites have started the development and deployment of Operational Data Analytics (ODA) frameworks allowing the continuous monitoring, archiving, and analysis of near realtime performance data from the machine and infrastructure levels, providing immediately actionable information for multiple operational uses. To understand their ODA goals, requirements, and use cases, we have conducted a survey among eight early adopter sites from the US, Europe, and Japan that operate top 50 high-performance computing systems. We have assessed the technologies leveraged to build their ODA frameworks, identified use cases and other push and pull factors that drive the sites' ODA activities, and report on their operational lessons.
- Research Organization:
- Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)
- DOE Contract Number:
- AC05-00OR22725
- OSTI ID:
- 1706258
- Resource Relation:
- Conference: Energy Efficient HPC State of the Practice Workshop 2020 - Kobe, , Japan - 9/14/2020 4:00:00 AM-9/14/2020 4:00:00 AM
- Country of Publication:
- United States
- Language:
- English
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