Multifrontral multithreaded rank-revealing sparse QR factorization

Davis, Timothy

doi:10.4230/DagSemProc.09061.13

Document

Multifrontral multithreaded rank-revealing sparse QR factorization

Author Timothy Davis

Part of: Volume: Dagstuhl Seminar Proceedings, Volume 9061
Part of: Series: Dagstuhl Seminar Proceedings (DagSemProc)
License: Creative Commons Attribution 4.0 International license
Publication Date: 2009-07-24

PDF

File

PDF

DagSemProc.09061.13.pdf

Filesize: 83 kB
3 pages

Document Identifiers

DOI: 10.4230/DagSemProc.09061.13
URN: urn:nbn:de:0030-drops-20781

Subject Classification

Keywords

Sparse matrix algorithms
QR factorization
multifrontal

Metrics

Access Statistics
Total Accesses (updated on a weekly basis)

0

PDF Downloads

0

Metadata Views

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 Get BibTex

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

Author Details

Timothy Davis

Questions / Remarks / Feedback

Feedback for Dagstuhl Publishing

Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail