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DTSTART:19700308T020000
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DTSTAMP:20260522T150128Z
LOCATION:D171
DTSTART;TZID=America/Chicago:20181114T163000
DTEND;TZID=America/Chicago:20181114T170000
UID:submissions.supercomputing.org_SC18_sess483_pec292@linklings.com
SUMMARY:Computationally-Accelerated Engineering at GE: Physics + Deep Lear
 ning
DESCRIPTION:Richard B. Arthur (General Electric Company)\n\nIn support of 
 a global team of engineers working on designing, building and servicing co
 mplex machines such as jet engines and gas turbines, GE Global Research ho
 sts a centralized HPC environment for computational modeling, simulation a
 nd analytics. GE’s Digital Thread for Design (DT4D) framework revolutioniz
 es product engineering by harnessing data services, automation and machine
  learning to advance multi-disciplinary modeling and simulation productivi
 ty and capability.  Engineers can offload previously labor-intensive, manu
 al, and ad-hoc tasks to focus on improving product performance and reliabi
 lity. Through collaborations between domain experts and data scientists, w
 e introduce “Deep Physics” – blending traditional physics models and knowl
 edge with the emerging power of deep learning to enable deeper exploration
  of parametric trade-off spaces and reshape the state of the art.\n\nTag: 
 Industry\n\nRegistration Category: Workshop Reg Pass, Tutorial Reg Pass, T
 ech Program Reg Pass, Exhibits Reg Pass, Exhibits - Exhibit Hall Only Reg 
 Pass\n\nSession Chairs: Lyle Long (Pennsylvania State University) and Davi
 d Martin (Lawrence Berkeley National Laboratory (LBNL), Energy Sciences Ne
 twork (ESnet))\n\n
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