Abstract
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.
Original language | English |
---|---|
Title of host publication | Proceedings - 2020 IEEE International Conference on Cluster Computing, CLUSTER 2020 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 499-508 |
Number of pages | 10 |
ISBN (Electronic) | 9781728166773 |
DOIs | |
State | Published - Sep 2020 |
Externally published | Yes |
Event | 22nd IEEE International Conference on Cluster Computing, CLUSTER 2020 - Kobe, Japan Duration: Sep 14 2020 → Sep 17 2020 |
Publication series
Name | Proceedings - IEEE International Conference on Cluster Computing, ICCC |
---|---|
Volume | 2020-September |
ISSN (Print) | 1552-5244 |
Conference
Conference | 22nd IEEE International Conference on Cluster Computing, CLUSTER 2020 |
---|---|
Country/Territory | Japan |
City | Kobe |
Period | 09/14/20 → 09/17/20 |
Funding
This research used resources of the National Energy Research Scientific Computing Center (NERSC), a US Department of Energy Office of Science User Facility operated under Contract No. DE-AC02-05CH11231. Also, this work was supported by, and used the resources of, the Oak Ridge Leadership Computing Facility, located in the National Center for Computational Sciences at ORNL, which is managed by UT Battelle, LLC for the U.S. DOE (under the contract No. DE-AC05-00OR22725). ACKNOWLEDGMENT We thank the many individuals from the participant sites for their contribution to our survey. This research used resources of the National Energy Research Scientific Computing Center (NERSC), a US Department of Energy Office of Science User Facility operated under Contract No. DE-AC02-05CH11231. Also, this work was supported by, and used the resources of, the Oak Ridge Leadership Computing Facility, located in the National Center for Computational Sciences at ORNL, which is managed by UT Battelle, LLC for the U.S. DOE (under the contract No. DE-AC05-00OR22725).
Keywords
- energy efficiency
- exascale
- HPC operations
- operational data
- site survey
- Top500