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DTSTAMP:20200129T163602Z
LOCATION:E Concourse
DTSTART;TZID=America/Denver:20191121T083000
DTEND;TZID=America/Denver:20191121T170000
UID:submissions.supercomputing.org_SC19_sess348_rpost137@linklings.com
SUMMARY:Poster 50: Implementing an Adaptive Sparse Grid Discretization (AS
GarD) for High Dimensional Advection-Diffusion Problems on Exascale Archit
ectures
DESCRIPTION:Posters, Research Posters\n\nPoster 50: Implementing an Adapti
ve Sparse Grid Discretization (ASGarD) for High Dimensional Advection-Diff
usion Problems on Exascale Architectures\n\nLopez, Green, Mu, D'Azevedo, E
lwasif...\n\nMany scientific domains require the solution of high dimensio
nal PDEs. Traditional grid- or mesh-based methods for solving such systems
in a noise-free manner quickly become intractable due to the scaling of t
he degrees of freedom going as O(N^d) sometimes called "the curse of dimen
sionality." We are developing an arbitrarily high-order discontinuous-Gale
rkin finite-element solver that leverages an adaptive sparse-grid discreti
zation whose degrees of freedom scale as O(N*log2 N^D-1). This method and
its subsequent reduction in the required resources is being applied to sev
eral PDEs including time-domain Maxwell's equations (3D), the Vlasov equat
ion (in up to 6D) and a Fokker-Planck-like problem in ongoing related effo
rts. Here we present our implementation which is designed to run on multip
le accelerated architectures, including distributed systems. Our implement
ation takes advantage of a system matrix decomposed as the Kronecker produ
ct of many smaller matrices which is implemented as batched operations.\n\
nRegistration Category: Tech Program Reg Pass, Exhibits Reg Pass, Exhibits
- Exhibit Hall Only Reg Pass
URL:https://sc19.supercomputing.org/presentation/?id=rpost137&sess=sess348
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