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BEGIN:VEVENT
DTSTAMP:20181221T160731Z
LOCATION:A2 Ballroom
DTSTART;TZID=America/Chicago:20181114T153000
DTEND;TZID=America/Chicago:20181114T160000
UID:submissions.supercomputing.org_SC18_sess466_gb102@linklings.com
SUMMARY:A Fast Scalable Implicit Solver for Nonlinear Time-Evolution Earth
 quake City Problem on Low-Ordered Unstructured Finite Elements with Artifi
 cial Intelligence and Transprecision Computing
DESCRIPTION:ACM Gordon Bell Finalist, Awards Presentation\n\n\nA Fast Scal
 able Implicit Solver for Nonlinear Time-Evolution Earthquake City Problem 
 on Low-Ordered Unstructured Finite Elements with Artificial Intelligence a
 nd Transprecision Computing\n\nIchimura, Fujita, Yamaguchi, Naruse, Wells.
 ..\n\nTo address problems that occur due to earthquakes in urban areas, we
  propose a method that utilizes artificial intelligence (AI) and transprec
 ision computing to accelerate a nonlinear dynamic low-order unstructured f
 inite-element solver. The AI is used to improve the convergence of iterati
 ve solver leading to 5.56-fold reduction in arithmetic count from a standa
 rd solver, and FP16-FP21-FP32-FP64 computing is used to accelerate the spa
 rse matrix-vector product kernel, which demonstrated 71.4% peak FP64 perfo
 rmance on Summit. This is 25.3 times faster than a standard solver and 3.9
 9 times faster than the state-of-the-art SC14 Gordon Bell Finalist solver.
  Furthermore, the proposed solver demonstrated high scalability (88.8% on 
 the K computer and 89.5% on Piz Daint), leading to 14.7% peak FP64 perform
 ance on 4096 nodes of Summit. The proposed approach utilizing AI and FP16 
 arithmetic has implications for accelerating other implicit solvers used f
 or earthquake city simulations as well as various fields.
URL:https://sc18.supercomputing.org/presentation/?id=gb102&sess=sess466
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