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TZID:Europe/Stockholm
X-LIC-LOCATION:Europe/Stockholm
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TZNAME:CEST
DTSTART:19700308T020000
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DTSTART:19701101T020000
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BEGIN:VEVENT
DTSTAMP:20230831T095742Z
LOCATION:Davos
DTSTART;TZID=Europe/Stockholm:20230628T163000
DTEND;TZID=Europe/Stockholm:20230628T173000
UID:submissions.pasc-conference.org_PASC23_sess127_panel101@linklings.com
SUMMARY:PD01 - Better Together: How Can We Enhance Inter-Community Collabo
 ration?
DESCRIPTION:Panel\n\nEleni Chatzi (ETH Zurich), Mike Heroux (Sandia Nation
 al Laboratories), Hannah Cohoon (University of Utah), Axel Huebl (Lawrence
  Berkeley National Laboratory), Neena Imam (NVIDIA Inc.), and Simone Pezzu
 to (University of Trento)\n\nThis panel discussion will focus on the PASC2
 3 theme: <em>Computing Across Scales, Domains, and Communities</em>. The p
 anel will discuss how to aggregate and synthesize distinct sources of tech
 nique and insight to improve the fidelity, effectiveness, efficiency, and 
 usefulness of scientific results at the frontiers of scientific computing.
  <br /><br />PASC23 investigates harnessing multi-scale methods, operating
  on the basis of hybridizations of physics and data, to enable higher fide
 lity predictive capabilities, especially for complex phenomena with emerge
 nt behavior. Aggregating and synthesizing approaches from multiple domains
 , including techniques from modeling & simulation and data-driven discipli
 nes, is essential to improving the quality and computational feasibility o
 f results. Forming teams across distinct scientific communities, up to and
  including the social and cognitive sciences, has also become essential to
  improve how teams develop and use computational tools for research, and c
 ommunicate results to the broader public. <br /><br />The panel discussion
  will specifically address these and other relevant topics from various pe
 rspectives. Our panelists will help us explore themes such as scientific-s
 oftware development, distributed heterogeneous computing and physics-based
  machine learning for multi-scale simulation, large scientific software te
 ams in the pursuit of leading-edge scientific simulation, as well as the n
 ature of scientific software teams.\n\nSession Chairs: Eleni Chatzi (ETH Z
 urich) and Michael A. Heroux (Sandia National Laboratories, St. John's Uni
 versity)
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