Partitioning sparse rectangular matrices for parallel processing
The authors are interested in partitioning sparse rectangular matrices for parallel processing. The partitioning problem has been well-studied in the square symmetric case, but the rectangular problem has received very little attention. They will formalize the rectangular matrix partitioning problem and discuss several methods for solving it. They will extend the spectral partitioning method for symmetric matrices to the rectangular case and compare this method to three new methods -- the alternating partitioning method and two hybrid methods. The hybrid methods will be shown to be best.
- Research Organization:
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
- Sponsoring Organization:
- USDOE Office of Energy Research, Washington, DC (United States)
- DOE Contract Number:
- AC05-96OR22464
- OSTI ID:
- 658436
- Report Number(s):
- ORNL/CP-98161; CONF-980813-; ON: DE98005713; BR: KJ0101010; TRN: AHC2DT06%%320
- Resource Relation:
- Conference: 5. international symposium on solving irregularly structured problems in parallel, Berkeley, CA (United States), 9-11 Aug 1998; Other Information: PBD: May 1998
- Country of Publication:
- United States
- Language:
- English
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