Autonomy Loops for Monitoring, Operational Data Analytics, Feedback, and Response in HPC Operations

Francieli Boito, Jim Brandt, Valeria Cardellini, Philip Carns, Florina Ciorba, Hilary Egan, Ahmed Eleliemy, Ann Gentile, Thomas Gruber, Jeff Hanson, Utz-Uwe Haus, Kevin Huck, Thomas Ilshe, Thomas Jakobsche, Terry Jones, Sven Karlsson, Abdullah Mueen, Michael Ott, Tapasya Patki, Ivy PengKrishnan Raghavan, Stephen Simms, Kathleen Shoga, Michael Showerman, Devesh Tiwari, Torsten Wilde, Keiji Yamamoto

Research output: Contribution to conferencePaper


Many High Performance Computing (HPC) facilities have developed and deployed frameworks in support of continuous monitoring and operational data analytics (MODA) to help improve efficiency and throughput. Because of the complexity and scale of systems and workflows and the need for low-latency response to address dynamic circumstances, automated feedback and response have the potential to be more effective than current human-in-the-loop approaches which are laborious and error prone. Progress has been limited, however, by factors such as the lack of infrastructure and feedback hooks, and successful deployment is often site- and case-specific. In this position paper we report on the outcomes and plans from a recent Dagstuhl Seminar, seeking to carve a path for community progress in the development of autonomous feedback loops for MODA, based on the established formalism of similar (MAPE-K) loops in autonomous computing and self-adaptive systems. By defining and developing such loops for significant cases experienced across HPC sites, we seek to extract commonalities and develop conventions that will facilitate interoperability and interchangeability with system hardware, software, and applications across different sites, and will motivate vendors and others to provide telemetry interfaces and feedback hooks to enable community development and pervasive deployment of MODA autonomy loops.
Original languageAmerican English
Number of pages7
StatePublished - 2023
Event2023 IEEE International Conference on Cluster Computing Workshops (CLUSTER Workshops) - Santa Fe, NM
Duration: 31 Oct 202331 Oct 2023


Conference2023 IEEE International Conference on Cluster Computing Workshops (CLUSTER Workshops)
CitySanta Fe, NM

NREL Publication Number

  • NREL/CP-2C00-88642


  • autonomy loops
  • high performance computing
  • MAPE-K
  • monitoring and operational data analytics


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