BEGIN:VCALENDAR
VERSION:2.0
PRODID:Linklings LLC
BEGIN:VTIMEZONE
TZID:America/New_York
X-LIC-LOCATION:America/New_York
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:19700308T020000
RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=2SU
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:19701101T020000
RRULE:FREQ=YEARLY;BYMONTH=11;BYDAY=1SU
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20250626T233532Z
LOCATION:B302-B305
DTSTART;TZID=America/New_York:20241121T100000
DTEND;TZID=America/New_York:20241121T170000
UID:submissions.supercomputing.org_SC24_sess534_post219@linklings.com
SUMMARY:HPC Fastpass: Visualizing Descriptive and Predictive HPC Queue Tim
 e Data
DESCRIPTION:Connor Scully-Allison (University of Utah, Scientific Computin
 g and Imaging Institute (SCI); National Renewable Energy Laboratory (NREL)
 )\n\nWith large HPC systems, users will often jockey for better queue time
 s to get quicker results. Unfortunately, getting accurate estimations of q
 ueue times requires understanding complex and abundant data collected from
  myriad HPC system loggers. To aid with this, researchers are exploring ma
 chine learning to shortcut the analysis of these factors and give discrete
  predictions. Unfortunately, these models are imperfect, expressing varyin
 g degrees of accuracy. This imperfection must be conveyed to users in the 
 form of uncertainty quantification. Thus, to provide users with a better u
 nderstanding of queue wait times on NREL's Eagle HPC system, we developed 
 a visualization that simplifies this complex data and aids decision making
 . This visualization summarizes uncertainty information associated with a 
 user's specific queue time prediction and places it into the larger contex
 t of historical data, encoding job submission variables that users can cha
 nge to show the impact of their choices on queue wait time.\n\nRegistratio
 n Category: Tech Program Reg Pass, Exhibits Reg Pass\n\nSession Chairs: Ay
 esha Afzal (Friedrich-Alexander University, Erlangen-Nuremberg; Erlangen N
 ational High Performance Computing Center); Sally Ellingson (University of
  Kentucky); and Alan Sussman (University of Maryland)\n\n
END:VEVENT
END:VCALENDAR