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Convergence Analysis of a Domain Decomposition Paradigm
Randolph E. Bank
Department of Mathematics
UCSD
Abstract
We describe a domain decomposition algorithm
for use in several variants of the parallel
adaptive meshing paradigm of Bank and Holst.
This algorithm has low communication, makes
extensive use of existing sequential solvers,
and exploits in several important ways data
generated as part of the adaptive meshing paradigm.
We show that for an idealized version of the
algorithm, the rate of convergence is independent
of both the global problem size N and the number
of subdomains p used in the domain decomposition
partition. Numerical examples illustrate the
effectiveness of the procedure.
This is joint work with Panayot Vassilevski, Lawrence
Livermore National Laboratory
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