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:20210402T160544Z
LOCATION:Poster Module
DTSTART;TZID=America/New_York:20201119T083000
DTEND;TZID=America/New_York:20201119T170000
UID:submissions.supercomputing.org_SC20_sess337_rpost126@linklings.com
SUMMARY:Analysis of FastEddy Model Data on GPUs
DESCRIPTION:Posters, Research Posters\n\nAnalysis of FastEddy Model Data o
 n GPUs\n\nLiu, Suresh, Miller, Sauer\n\nData analysis of atmospheric model
  outputs is often embarrassingly parallel and compute intensive, and is tr
 aditionally done on central processing units (CPUs).  FastEddy is a Genera
 l Purpose Graphical Processing Units (GPGPU) -based Large Eddy Simulation 
 (LES) atmospheric model developed at NCAR-Research Application Laboratory 
 that solves fundamental dynamical equations and computes turbulence at a h
 igh resolution, producing large datasets that reside on GPUs. To reduce th
 e amount of data movement from GPUs to CPUs for analysis, and to reduce th
 e need for end-users to learn complex GPU programming using CUDA, this wor
 k explores performing the analysis on GPUs using only Python libraries.\n\
 nRegistration Category: Tech Program Reg Pass, Exhibits Reg Pass
END:VEVENT
END:VCALENDAR