Graph Based Anomaly Detection in Chimbuko: Feasible or Fallible?
Published in Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC '23), 2023
Recommended citation: Chase Phelps, Ankur Lahiry, Tanzima Z Islam, and Christopher Kelly. (2023). "Graph Based Anomaly Detection in Chimbuko: Feasible or Fallible?" Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC '23). https://sc23.supercomputing.org/proceedings/tech_poster/tech_poster_pages/rpost184.html
A study on the applicability of graph-based deep learning methods for performance anomaly classification in the Chimbuko framework — a performance analytics tool used to monitor and improve the efficiency of large-scale supercomputing applications.
Authors: Chase Phelps, Ankur Lahiry, Tanzima Z Islam, and Christopher Kelly