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DTSTAMP:20181221T160902Z
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:HPC Impact Showcase\nWorkshop Reg Pass, Tutorial Reg Pass, Tec
 h Program Reg Pass, Exhibits Reg Pass, Exhibits - Exhibit Hall Only Reg Pa
 ss, Industry\n\nComputationally-Accelerated Engineering at GE: Physics + D
 eep Learning\n\nArthur\n\nIn support of a global team of engineers working
  on designing, building and servicing complex machines such as jet engines
  and gas turbines, GE Global Research hosts a centralized HPC environment 
 for computational modeling, simulation and analytics. GE’s Digital Thread 
 for Design (DT4D) framework revolutionizes product engineering by harnessi
 ng data services, automation and machine learning to advance multi-discipl
 inary modeling and simulation productivity and capability.  Engineers can 
 offload previously labor-intensive, manual, and ad-hoc tasks to focus on i
 mproving product performance and reliability. Through collaborations betwe
 en domain experts and data scientists, we introduce “Deep Physics” – blend
 ing traditional physics models and knowledge with the emerging power of de
 ep learning to enable deeper exploration of parametric trade-off spaces an
 d reshape the state of the art.
URL:https://sc18.supercomputing.org/presentation/?id=pec292&sess=sess483
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