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DTSTART:19700308T020000
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BEGIN:VEVENT
DTSTAMP:20211207T055359Z
LOCATION:Second Floor Atrium
DTSTART;TZID=America/Chicago:20211117T083000
DTEND;TZID=America/Chicago:20211117T170000
UID:submissions.supercomputing.org_SC21_sess279_rpost126@linklings.com
SUMMARY:Detecting and Identifying Applications by Job Signatures
DESCRIPTION:Posters, Research Posters\n\nDetecting and Identifying Applica
 tions by Job Signatures\n\nLi, Cook, Chen\n\nKnowing the applications of j
 obs running in high-performance computing (HPC) systems is invaluable for 
 administrators. This research aims to detect and identify applications thr
 ough job signatures built upon monitoring traces obtained from the LDMS mo
 nitoring infrastructure on Cori. By constructing job signatures and applyi
 ng machine learning models to them, we will be able to detect and identify
  job applications without user intervention. In addition to application na
 mes, job signatures offer the potential to study workloads by computation 
 motif.\n\nRegistration Category: Tech Program Reg Pass, Exhibit Hall Only
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