Abstract
In this paper we investigate the parallelization of the ILUPACK library for the solution of sparse linear systems on distributed-memory multiprocessors. The parallelization approach employs multilevel graph partitioning algorithms in order to identify a set of concurrent tasks and their dependencies, which are then statically mapped to processors. Experimental results on a cluster of Intel QuadCore processors report remarkable speed-ups.
Original language | English |
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Title of host publication | Applied Parallel and Scientific Computing - 10th International Conference, PARA 2010, Revised Selected Papers |
Pages | 162-172 |
Number of pages | 11 |
Edition | PART 1 |
DOIs | |
Publication status | Published - 1 Mar 2012 |
Externally published | Yes |
Event | International Conference on Applied Parallel and Scientific Computing, 2010 - Reykjavik, Iceland Duration: 6 Jun 2010 → 9 Jun 2010 Conference number: 10th |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Number | PART 1 |
Volume | 7133 LNCS |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | International Conference on Applied Parallel and Scientific Computing, 2010 |
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Abbreviated title | PARA 2010 |
Country/Territory | Iceland |
City | Reykjavik |
Period | 6/06/10 → 9/06/10 |
Keywords
- distributed-memory multiprocessor
- ILU decomposition
- iterative solver
- MPI
- preconditioner
- Sparse linear system