DagSemProc.09061.13.pdf
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Multifrontral multithreaded rank-revealing sparse QR factorization
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Dagstuhl Seminar Proceedings, Volume 9061
Series: Dagstuhl Seminar Proceedings (DagSemProc) - License:
Creative Commons Attribution 4.0 International license
- Publication Date: 2009-07-24
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Timothy Davis. Multifrontral multithreaded rank-revealing sparse QR factorization. In Combinatorial Scientific Computing. Dagstuhl Seminar Proceedings, Volume 9061, pp. 1-3, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2009)
https://doi.org/10.4230/DagSemProc.09061.13
https://doi.org/10.4230/DagSemProc.09061.13
Abstract
SuiteSparseQR is a sparse multifrontal QR factorization algorithm.
Dense matrix methods within each frontal matrix enable
the method to obtain high performance on multicore architectures. Parallelism
across different frontal matrices is handled with Intel's Threading Building
Blocks library.
Rank-detection is performed within each
frontal matrix using Heath's method, which does not require column pivoting.
The resulting sparse QR factorization obtains a substantial fraction of the
theoretical peak performance of a multicore computer.
Keywords
- Sparse matrix algorithms
- QR factorization
- multifrontal
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