BEGIN:VCALENDAR
VERSION:2.0
PRODID:Linklings LLC
BEGIN:VTIMEZONE
TZID:America/Chicago
X-LIC-LOCATION:America/Chicago
BEGIN:DAYLIGHT
TZOFFSETFROM:-0600
TZOFFSETTO:-0500
TZNAME:CDT
DTSTART:19700308T020000
RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=2SU
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0500
TZOFFSETTO:-0600
TZNAME:CST
DTSTART:19701101T020000
RRULE:FREQ=YEARLY;BYMONTH=11;BYDAY=1SU
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20181221T160726Z
LOCATION:D220
DTSTART;TZID=America/Chicago:20181111T144200
DTEND;TZID=America/Chicago:20181111T144500
UID:submissions.supercomputing.org_SC18_sess160_ws_whpc118@linklings.com
SUMMARY:In Situ Performance Analysis of Event-driven Simulations to Suppor
 t the Codesign of Extreme-Scale Systems
DESCRIPTION:Workshop\nDiversity, Education, Hot Topics, Workshop Reg Pass\
 n\nIn Situ Performance Analysis of Event-driven Simulations to Support the
  Codesign of Extreme-Scale Systems\n\nRoss\n\nParallel discrete event simu
 lation (PDES) is a productive and cost-effective tool in exploring the des
 ign space of high performance computing (HPC) system architectures.  In di
 screte event simulation, the modeled entities (e.g., network router) inter
 act through the exchange of timestamped messages. For parallel simulations
 , the synchronization protocol ensures causal correctness of the simulatio
 n.  In PDES, synchronization protocols are classified as conservative or o
 ptimistic. Conservative methods ensure that events are processed only when
  it is safe to do so, while optimistic methods allow for speculative proce
 ssing of events and provide out-of-order event detection and recovery mech
 anisms. Because optimistic protocols can better exploit the parallelism in
 herent in models, optimistic simulations tend to be more scalable than con
 servative simulations. However, optimizing optimistic simulations to minim
 ize the time spent performing unproductive work (i.e., rolling back the si
 mulation state to fix causality errors) is not a trivial task. The factors
  that affect optimistic performance exist at multiple levels of the simula
 tion, from the physical hardware running the simulation, communication of 
 MPI ranks, as well as characteristics of the simulated model itself.  The 
 interplay of these factors is difficult to understand, making it difficult
  for optimistic PDES to be used efficiently, especially by simulation user
 s, such as network architects.
URL:https://sc18.supercomputing.org/presentation/?id=ws_whpc118&sess=sess1
 60
END:VEVENT
END:VCALENDAR