An implementation of the tile QR factorization for a GPU and multiple CPUs

Jakub Kurzak; Rajib Nath; Peng Du; Jack Dongarra

doi:10.1007/978-3-642-28145-7_25

An implementation of the tile QR factorization for a GPU and multiple CPUs

Jakub Kurzak, Rajib Nath, Peng Du, Jack Dongarra

Computer Science and Mathematics Div

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

9 Scopus citations

Abstract

The tile QR factorization provides an efficient and scalable way for factoring a dense matrix in parallel on multicore processors. This article presents a way of efficiently implementing the algorithm on a system with a powerful GPU and many multicore CPUs.

Original language	English
Title of host publication	Applied Parallel and Scientific Computing - 10th International Conference, PARA 2010, Revised Selected Papers
Pages	248-257
Number of pages	10
Edition	PART 2
DOIs	https://doi.org/10.1007/978-3-642-28145-7_25
State	Published - 2012
Event	10th International Conference on Applied Parallel and Scientific Computing, PARA 2010 - Reykjavik, Iceland Duration: Jun 6 2010 → Jun 9 2010

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 2
Volume	7134 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	10th International Conference on Applied Parallel and Scientific Computing, PARA 2010
Country/Territory	Iceland
City	Reykjavik
Period	06/6/10 → 06/9/10

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10.1007/978-3-642-28145-7_25

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Kurzak, J., Nath, R., Du, P., & Dongarra, J. (2012). An implementation of the tile QR factorization for a GPU and multiple CPUs. In Applied Parallel and Scientific Computing - 10th International Conference, PARA 2010, Revised Selected Papers (PART 2 ed., pp. 248-257). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7134 LNCS, No. PART 2). https://doi.org/10.1007/978-3-642-28145-7_25

Kurzak, Jakub ; Nath, Rajib ; Du, Peng et al. / An implementation of the tile QR factorization for a GPU and multiple CPUs. Applied Parallel and Scientific Computing - 10th International Conference, PARA 2010, Revised Selected Papers. PART 2. ed. 2012. pp. 248-257 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2).

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title = "An implementation of the tile QR factorization for a GPU and multiple CPUs",

abstract = "The tile QR factorization provides an efficient and scalable way for factoring a dense matrix in parallel on multicore processors. This article presents a way of efficiently implementing the algorithm on a system with a powerful GPU and many multicore CPUs.",

author = "Jakub Kurzak and Rajib Nath and Peng Du and Jack Dongarra",

year = "2012",

doi = "10.1007/978-3-642-28145-7_25",

language = "English",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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pages = "248--257",

booktitle = "Applied Parallel and Scientific Computing - 10th International Conference, PARA 2010, Revised Selected Papers",

edition = "PART 2",

note = "10th International Conference on Applied Parallel and Scientific Computing, PARA 2010 ; Conference date: 06-06-2010 Through 09-06-2010",

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Kurzak, J, Nath, R, Du, P & Dongarra, J 2012, An implementation of the tile QR factorization for a GPU and multiple CPUs. in Applied Parallel and Scientific Computing - 10th International Conference, PARA 2010, Revised Selected Papers. PART 2 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 2, vol. 7134 LNCS, pp. 248-257, 10th International Conference on Applied Parallel and Scientific Computing, PARA 2010, Reykjavik, Iceland, 06/6/10. https://doi.org/10.1007/978-3-642-28145-7_25

An implementation of the tile QR factorization for a GPU and multiple CPUs. / Kurzak, Jakub; Nath, Rajib; Du, Peng et al.
Applied Parallel and Scientific Computing - 10th International Conference, PARA 2010, Revised Selected Papers. PART 2. ed. 2012. p. 248-257 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7134 LNCS, No. PART 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - The tile QR factorization provides an efficient and scalable way for factoring a dense matrix in parallel on multicore processors. This article presents a way of efficiently implementing the algorithm on a system with a powerful GPU and many multicore CPUs.

AB - The tile QR factorization provides an efficient and scalable way for factoring a dense matrix in parallel on multicore processors. This article presents a way of efficiently implementing the algorithm on a system with a powerful GPU and many multicore CPUs.

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Kurzak J, Nath R, Du P, Dongarra J. An implementation of the tile QR factorization for a GPU and multiple CPUs. In Applied Parallel and Scientific Computing - 10th International Conference, PARA 2010, Revised Selected Papers. PART 2 ed. 2012. p. 248-257. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2). doi: 10.1007/978-3-642-28145-7_25

An implementation of the tile QR factorization for a GPU and multiple CPUs

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