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ABSTRACT
Two techniques are introduced to reduce the working storage requirement for the recent multifrontal method of Duff and Reid used in the sparse out-of-core factorization of symmetric matrices. For a given core size, the reduction in working storage allows some large problems to be solved without having to use auxiliary storage for the working arrays. Even if the working arrays exceed the core size, it will reduce the amount of input-output traffic necessary to manipulate the working vectors. Experimental results are provided to demonstrate significant storage reduction on practical problems using the proposed techniques.
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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CITED BY 12
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Douglas Davis , William Ribarsky , T. Y. Jiang , Nickolas Faust , Sean Ho, Real-time visualization of scalably large collections of heterogeneous objects (case study), Proceedings of the conference on Visualization '99: celebrating ten years, p.437-440, October 1999, San Francisco, California, United States
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Douglass Davis , William Ribarsky , Nickolas Faust , T. Y. Jiang, Intent, perception, and out-of-core visualization applied to terrain, Proceedings of the conference on Visualization '98, p.455-458, October 18-23, 1998, Research Triangle Park, North Carolina, United States
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REVIEW
"Ian Gladwell : Reviewer"
This paper considers two techniques for reducing the working storage needed
for the multifrontal method of factorization of sparse symmetric matrices.
This reduction in working storage permits larger problems than previously
to be solved in core
more...
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