Statistical and Shapelet Analysis of HPC Application Performance Using Time-Series Heartbeat Data
Mohammad Al-Tahat, Strahinja Trecakov, Jonathan Emdin Cook · 2024
AppEKG is a high performance computing (HPC) oriented application heartbeat framework designed for low-overhead monitoring of HPC applications in production, providing a unified, understandable view of dynamic HPC application behavior by capturing time-varying behavior with little overhead (~1%). In this paper we demonstrate the value of heartbeat data collected with AppEKG, showing that it can be used for anomaly detection and run classification. This paper uses statistical modeling and time-series shapelet analyses as initial examples of heartbeat data analysis. The results of these analyses show that application heartbeats can be useful to help better understand how HPC applications are using the costly time and resources they consume, and that this can be applied in production.