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Multifrontral multithreaded rank-revealing sparse QR factorization

Authors: Timothy Davis

Published in: Dagstuhl Seminar Proceedings, Volume 9061, Combinatorial Scientific Computing (2009)


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.

Cite as

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)


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@InProceedings{davis:DagSemProc.09061.13,
  author =	{Davis, Timothy},
  title =	{{Multifrontral multithreaded rank-revealing sparse QR factorization}},
  booktitle =	{Combinatorial Scientific Computing},
  pages =	{1--3},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2009},
  volume =	{9061},
  editor =	{Uwe Naumann and Olaf Schenk and Horst D. Simon and Sivan Toledo},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.09061.13},
  URN =		{urn:nbn:de:0030-drops-20781},
  doi =		{10.4230/DagSemProc.09061.13},
  annote =	{Keywords: Sparse matrix algorithms, QR factorization, multifrontal}
}
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