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DTSTART:19700308T020000
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BEGIN:VEVENT
DTSTAMP:20210402T160555Z
LOCATION:Track 5
DTSTART;TZID=America/New_York:20201113T110000
DTEND;TZID=America/New_York:20201113T112500
UID:submissions.supercomputing.org_SC20_sess224_ws_eduhpcp101@linklings.co
 m
SUMMARY:Integrating Machine Learning with HPC-Driven Simulations for Enhan
 ced Student Learning
DESCRIPTION:Workshop\n\nIntegrating Machine Learning with HPC-Driven Simul
 ations for Enhanced Student Learning\n\nJadhao, Kadupitiya\n\nWe explore t
 he idea of integrating machine learning (ML) with high performance computi
 ng (HPC)-driven simulations to address challenges in using simulations to 
 teach computational science and engineering courses. We demonstrate that a
  ML surrogate, designed using artificial neural networks, yields predictio
 ns in excellent agreement with explicit simulation, but at far less time a
 nd computing costs. \n\nWe develop a web application on nanoHUB that suppo
 rts both HPC-driven simulation and the ML surrogate methods to produce sim
 ulation outputs. \nThis tool is used for both in-classroom instruction and
  for solving homework problems associated with two courses covering topics
  in the broad areas of computational materials science, modeling and simul
 ation, and engineering applications of HPC-enabled simulations.\n\nThe eva
 luation of the tool via in-classroom student feedback and surveys shows th
 at the ML-enhanced tool provides a dynamic and responsive simulation envir
 onment that enhances student learning.  The improvement in the interactivi
 ty with the simulation framework in terms of real-time engagement and anyt
 ime access enables students to develop intuition for the physical system b
 ehavior through rapid visualization of variations in output quantities wit
 h changes in inputs.\n\nTag: Education, Training and Outreach, HPC Trainin
 g and Education\n\nRegistration Category: Workshop Reg Pass
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