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BEGIN:VEVENT
DTSTAMP:20260522T150110Z
LOCATION:C2/3/4 Ballroom
DTSTART;TZID=America/Chicago:20181114T083000
DTEND;TZID=America/Chicago:20181114T170000
UID:submissions.supercomputing.org_SC18_sess326_spost107@linklings.com
SUMMARY:Holistic Root Cause Analysis of Node Failures in Production HPC
DESCRIPTION:Anwesha Das (North Carolina State University)\n\nProduction HP
 C clusters endure failures incurring computation and resource wastage. Des
 pite the presence of various failure detection and prediction schemes, a c
 omprehensive understanding of how nodes fail considering various component
 s and layers of the system is required for sustained resilience. This work
  performs a holistic root cause diagnosis of node failures using a measure
 ment-driven approach on contemporary system logs that can help vendors and
  system administrators support exascale resilience.\n\nOur work shows that
  lead times can be increased by at least 5 times if external subsystem cor
 relations are considered as opposed to considering the events of a specifi
 c node in isolation. Moreover, when detecting sensor measurement outliers 
 and interconnect related failures, triggering automated recovery events ca
 n exacerbate the situation if recovery is unsuccessful.\n\nRegistration Ca
 tegory: Tech Program Reg Pass, Exhibits Reg Pass\n\n
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