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DTSTART:19700308T020000
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BEGIN:VEVENT
DTSTAMP:20210402T160557Z
LOCATION:Track 9
DTSTART;TZID=America/New_York:20201111T163000
DTEND;TZID=America/New_York:20201111T170000
UID:submissions.supercomputing.org_SC20_sess196_ws_works109@linklings.com
SUMMARY:Characterizing Scientific Workflows on HPC Systems Using Logs
DESCRIPTION:Workshop\n\nCharacterizing Scientific Workflows on HPC Systems
  Using Logs\n\nGhoshal, Austin, Bard, Daley, Lockwood...\n\nScientific adv
 ances depend on the ability to effectively and efficiently use high perfor
 mance computing (HPC) systems to manage and run large, complex scientific 
 workflows.  Toward understanding the characteristics of these large scient
 ific workflows, we propose two methods to identify workflows with temporal
  connections and data-dependencies from batch queue and I/O logs available
  at HPC systems.  We use the two methods to characterize and correlate wor
 kflow runtime with node requests, I/O patterns, and resource usage on thre
 e months of log data available for Cori, a supercomputer at NERSC.  A key 
 result from our analyses shows that single-job workflows often do not use 
 all allocated CPUs that provides opportunities to consider allocating reso
 urces at a finer-granularity.\n\nTag: Scientific Computing, Workflows\n\nR
 egistration Category: Workshop Reg Pass
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