SC22 Proceedings

The International Conference for High Performance Computing, Networking, Storage, and Analysis

Research Posters Archive

Interactive Visual Analysis Tool for Anomaly Provenance Data

Authors: Alicia Guite and Tanzima Z. Islam (Texas State University) and Christopher Kelly and Wei Xu (Brookhaven National Laboratory)

Abstract: Chimbuko is a framework for detecting real-time performance anomalies incurred by large-scale applications. Understanding the source of anomalous behaviors is difficult due to the high volume of information stored by Chimbuko in a provenance database. This undergraduate research project aims to intuitively display this high volume of information without overwhelming users. We then integrate our analysis and visualization techniques into a publicly available framework called Dashing. This project facilitates interactive user investigation of anomaly provenance in large-scale applications.

Best Poster Finalist (BP): no

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