The Dagstuhl Seminar 23171 (April 23-28, 2023) brought together 35 practitioners and researchers in the areas of HPC system management and monitoring, data analytics, and computer science to collaboratively work on developing community solutions for revolutionizing HPC system operations. Autonomous operations have long been the vision for efficient HPC system operations due to the size and complexity of current and evolving HPC systems and the need for pervasive, low-latency response. Autonomous operations are a complex topic encompassing monitoring, analysis, feedback, and response. The seminar goals were to make substantial progress on the technical, community, and funding challenges necessary for the community to move forward and reach this vision.

The seminar schedule comprised a mix of keynotes presentations, seed and position talks, enlisted and ad-hoc lightning talks, interleaved with plenary discussions and working group discussions, both in the seminar rooms as well as outdoors.

These program elements and the active participation of the attendees lead to many fruitful discussions on the following topics:

• Center-specific urgent use cases that drive data collection, analysis, and response requirements across the variety of institutions represented.
• Types of available data, including sources, semantics, and fidelity, to support continuous analyses.
• Requirements for actionable analytics. What is needed to convert raw data into information upon which action can be taken (e.g., confidence measures, explainability requirements not inherent in AI approaches, representation of results, latency, etc.)?
• Applicability of existing analytics and informatics approaches to the domain-specifics of HPC operations. While there are many promising ML/AI approaches in other domains (e.g., image/speech processing, autonomous vehicles), it is not yet clear how many and which of those apply to the HPC operations and research domains (e.g., the occurrence of rare fault events, discontinuity of inertia-less measurements).
• Opportunities for response involving infrastructure, hardware, system software, and applications. Identification of feedback hooks that would need to be added to existing and evolving system components (e.g., hardware, firmware, system software, application software) to support automated response.
• Exploration of formalism and architectural design patterns from the field of Self-Adaptive Systems to facilitate common, interoperable, and interchangeable design and development paths forward.

The technical presentations and engaging discussions reinforced the urgent need and desire for a community approach to advance the state and practice of HPC Monitoring and Operational Data Analytics, with the goal of revolutionizing HPC operations and research, in order to deliver efficient and sustainable HPC systems and applications.

The fundamental results of this community discussion are given in Section 10 of the full report of this report. These include assessments of the state of autonomous loops in HPC operations and assessments of challenges and opportunities. The community agreed to continue meeting, on a monthly basis and at upcoming community-relevant events. They further agreed to develop proofs of concepts for concrete use cases that will showcase both the need for holistic monitoring and analysis and their benefits for more efficient HPC operations. These proofs of concepts will also serve as a basis for technical design decisions and prototype solutions to be deployed in various HPC systems. The final goals of our effort are to continue to build and progress on a community collaborative technical path forward, a community interaction path forward, and a community collaborative funding path forward, as described in Section 11 of the full report, to fulfill the vision of autonomous and efficient HPC system operations.

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Jim Brandt, Florina M. Ciorba, Ann Gentile, Michael Ott, and Torsten Wilde