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UID:submissions.supercomputing.org_SC19_sess133_ws_daac104@linklings.com
SUMMARY:MELA: A Visual Analytics Tool for Studying Multifidelity HPC Syste
 m Logs
DESCRIPTION:Workshop\n\nMELA: A Visual Analytics Tool for Studying Multifi
 delity HPC System Logs\n\nShilpika, Lusch, Emani, Vishwanath, Papka...\n\n
 To maintain a robust and reliable supercomputing hardware system there is 
 a critical need to understand various system events, including failures oc
 curring in the system. Toward this goal, we analyze various system logs su
 ch as error logs, job logs and environment logs from Argonne Leadership Co
 mputing Facility's (ALCF) Theta Cray XC40 supercomputer. This log data inc
 orporates multiple subsystem and component measurements at various fidelit
 y levels and temporal resolutions - a very diverse and massive dataset. To
  effectively identify various patterns that characterize system behavior a
 nd faults over time, we have developed a visual analytics tool, MELA,  to 
 better identify patterns and glean insights from these log data.\n\nTag: W
 orkshop Reg Pass, Big Data, Collaborative Environments, Data Analytics, Da
 ta Management, Datacenter\n\nRegistration Category: Workshop Reg Pass, Big
  Data, Collaborative Environments, Data Analytics, Data Management, Datace
 nter
URL:https://sc19.supercomputing.org/presentation/?id=ws_daac104&sess=sess1
 33
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