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Stable, globally non-iterative, non-overlapping domain decomposition parallel solvers for parabolic problems
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Source Conference on High Performance Networking and Computing archive
Proceedings of the 2001 ACM/IEEE conference on Supercomputing (CDROM) table of contents
Denver, Colorado
Pages: 19 - 19  
Year of Publication: 2001
ISBN:1-58113-293-X
Authors
Yu Zhuang  Texas Tech University, Lubbock, Texas
Xian-He Sun  Illinois Institute of Technology, Chicago, Illinois
Sponsors
ACM: Association for Computing Machinery
SIGARCH: ACM Special Interest Group on Computer Architecture
IEEE-CS\DATC : IEEE Computer Society
Publisher
ACM  New York, NY, USA
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ABSTRACT

In this paper, we report a class of stabilized explicit-implicit domain decomposition (SEIDD) methods for the parallel solution of parabolic problems, based on the explicit-implicit domain decomposition (EIDD) methods. EIDD methods are globally non-iterative, non-overlapping domain decomposition methods which, when compared with Schwarz alternating algorithm based parabolic solvers, are computationally and communicationally efficient for each simulation time step but suffer from time step size restrictions due to conditional stability or conditional consistency. By adding a stabilization step to the EIDD methods, the SEIDD methods are freed from time step size restrictions while retaining EIDD's computational and communicational efficiency for each time step, rendering themselves excellent candidates for large-scale parallel simulations. Three algorithms of the SEIDD type are implemented, which are experimentally tested to show excellent stability, computation and communication efficiencies, and high parallel speedup and scalability.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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