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Title:Layer potential evaluations on distributed memory machines
Author(s):Gao, Hao
Advisor(s):Kloeckner, Andreas
Department / Program:Computer Science
Discipline:Computer Science
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:M.S.
Genre:Thesis
Subject(s):Layer Potentials
Distributed Memory Parallelism
Integral Equations
Singular Integrals
Fast Multipole Method
Abstract:One of the main challenges of using integral equation methods (IEM) for solving partial differential equations is evaluating layer potentials with singular kernels. Quadrature by Expansion (QBX) is a quadrature method to evaluate such layer potentials accurately for targets near or on the source boundary, by forming expansions in the high-accuracy region away from the boundary, and evaluating the targets using the expansions. Recently, a new algorithm, called 'GIGAQBX', has combined QBX with the Fast Multipole Method to achieve linear complexity in terms of the number of degrees of freedom. Despite this advancement, QBX is still computationally expensive. To enable IEM on large-scale problems, this thesis investigates evaluating layer potentials on distributed-memory machines. The distributed algorithm introduced in this thesis is based on GIGAQBX and shows GIGAQBX contains plenty of parallelism. We evaluate our algorithm on the Comet supercomputer at the San Diego Supercomputer Center and show that it exhibits good strong scaling up to 1536 cores.
Issue Date:2020-05-12
Type:Thesis
URI:http://hdl.handle.net/2142/108032
Rights Information:Copyright 2020 Hao Gao
Date Available in IDEALS:2020-08-26
Date Deposited:2020-05


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