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:20210402T160550Z
LOCATION:Poster Module
DTSTART;TZID=America/New_York:20201119T083000
DTEND;TZID=America/New_York:20201119T170000
UID:submissions.supercomputing.org_SC20_sess341_spostg104@linklings.com
SUMMARY:AI-Guided Adaptive Multiscale Modeling of Platelet Dynamics
DESCRIPTION:ACM Student Research Competition: Graduate Poster, ACM Student
  Research Competition: Undergraduate Poster, Posters\n\nAI-Guided Adaptive
  Multiscale Modeling of Platelet Dynamics\n\nHan, Zhang, Deng\n\nWe develo
 ped an AI-guided adaptive multiple time stepping algorithm to model platel
 et activation, adhesion and aggregation, complex dynamical processes that 
 cause physiological reactions including cardiovascular diseases and stroke
 . The dynamics spans 6 spatial and 9 temporal scales. Our algorithm can in
 telligently adapt integration time step sizes to the underlying dynamics. 
 We access the accuracy and speed of our algorithm on a heterogeneous super
 computer with the IBM POWER9 CPUs and Nvidia V100 GPUs. The algorithm spee
 d increases by 4000x with CPUs and an extra 5-10x with GPUs while preservi
 ng the solution accuracy within 97%, compared with the conventional algori
 thm. The poster presents the details of the AI-guided multiple time steppi
 ng algorithm and its performance for speeding up modeling of this challeng
 ing multiscale biomedical problem.\n\nTag: Student Program\n\nRegistration
  Category: Tech Program Reg Pass, Exhibits Reg Pass
END:VEVENT
END:VCALENDAR