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DTSTAMP:20210916T132450Z
LOCATION:Louis Favre
DTSTART;TZID=Europe/Stockholm:20210706T143000
DTEND;TZID=Europe/Stockholm:20210706T150000
UID:submissions.pasc-conference.org_PASC21_sess125_msa153@linklings.com
SUMMARY:High Performance Computing for Probabilistic Tsunami Hazard Analys
 is
DESCRIPTION:Minisymposium\n\nHigh Performance Computing for Probabilistic 
 Tsunami Hazard Analysis\n\nLøvholt, Gibbons, Lorito, Volpe, Selva...\n\nTs
 unamis represent a hazard which strikes the population infrequently while 
 involving potentially large consequences. Probabilistic Tsunami Hazard Ana
 lysis (PTHA) addresses the likelihood of a tsunami exceeding given metric 
 within a given time interval. Uncertainty quantification in PTHA sometimes
  necessitates as many as tens to hundreds of thousands of scenarios for a 
 single target location. For every scenario, a numerical wave model involvi
 ng a wide range of spatial scales simulates the wave generation, propagati
 on over transoceanic distances, and inundation at high resolution (e.g. a 
 few meters). Obtaining sufficient accuracy necessitates need for huge comp
 utational resources which so far have been out of reach. Recently, efficie
 nt GPU-optimized shallow water type models for simulating tsunami inundati
 on along with larger HPC resources availability, have made a regional and 
 local long-term hazard assessment feasible. High-resolution PTHA is one Pi
 lot Demonstrator of the EC-funded ChEESE project (Center of Excellence for
  Exascale Computing in the Solid Earth). A ChEESE workflow has been develo
 ped with three main stages: source specification and discretization, effic
 ient numerical inundation simulation for each scenario using the Tsunami-H
 ySEA model at high resolution onshore, and hazard aggregation. The definit
 ion of a refined set of sources and probabilities is based on an existing 
 lower-resolution PTHA (TSUMAPS-NEAM), through disaggregation and refinemen
 t of the low-resolution sources. Here, we illustrate the PTHA workflow as 
 implemented for HPC applications, including preliminary simulations carrie
 d out on intermediate scale GPU clusters. Finally, we outline how upscalin
 g this application using Exascale resources would help solving problems of
  this scale to the required accuracy.\n\nDomain: CS and Math, Solid Earth 
 Dynamics
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