Parallel implicit domain-decomposed solvers for PDEs

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Parallel computing is providing the next advance in computer hardware and software for the solution of partial differential equations. The real potential in these advances is in massively parallel computing (the next generation of supercomputers) and in distributed computing (large clusters of workstations). In both of these cases, algorithms that are efficient for these machines must make efficient use of local memory and restrict the use of distant memory, while not sacrificing overall performance. Current research into domain-decomposition algorithms has shown how to efficiently combine a small amount of global information with purely local information to construct efficient solvers for systems of linear equations arising from PDEs. This paper will review the current state of the art and discuss some aspects of software that implements these algorithms.

Original languageEnglish (US)
Title of host publicationAdaptive, Multilevel, and Hierarchical Computational Strategies
PublisherPubl by ASME
Number of pages14
ISBN (Print)0791811344
StatePublished - 1992
Externally publishedYes
EventWinter Annual Meeting of the American Society of Mechanical Engineers - Anaheim, CA, USA
Duration: Nov 8 1992Nov 13 1992

Publication series

NameAmerican Society of Mechanical Engineers, Applied Mechanics Division, AMD
ISSN (Print)0160-8835


OtherWinter Annual Meeting of the American Society of Mechanical Engineers
CityAnaheim, CA, USA

ASJC Scopus subject areas

  • Mechanical Engineering


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