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Distributed one-stage Hessenberg-triangular reduction with wavefront scheduling
Umeå University, Faculty of Science and Technology, Department of Computing Science. Umeå University, Faculty of Science and Technology, High Performance Computing Center North (HPC2N).
Umeå University, Faculty of Science and Technology, Department of Computing Science. Umeå University, Faculty of Science and Technology, High Performance Computing Center North (HPC2N).
Umeå University, Faculty of Science and Technology, Department of Computing Science. Umeå University, Faculty of Science and Technology, High Performance Computing Center North (HPC2N).
2018 (English)In: SIAM Journal on Scientific Computing, ISSN 1064-8275, E-ISSN 1095-7197, Vol. 40, no 2, p. C157-C180Article in journal (Refereed) Published
Abstract [en]

A novel parallel formulation of Hessenberg-triangular reduction of a regular matrix pair on distributed memory computers is presented. The formulation is based on a sequential cacheblocked algorithm by K degrees agstrom et al. [BIT, 48 (2008), pp. 563 584]. A static scheduling algorithm is proposed that addresses the problem of underutilized processes caused by two-sided updates of matrix pairs based on sequences of rotations. Experiments using up to 961 processes demonstrate that the new formulation is an improvement of the state of the art and also identify factors that limit its scalability.

Place, publisher, year, edition, pages
Society for Industrial and Applied Mathematics, 2018. Vol. 40, no 2, p. C157-C180
Keywords [en]
generalized eigenvalue problem, Hessenberg-triangular reduction, parallel algorithms, wavefront scheduling
National Category
Computational Mathematics
Identifiers
URN: urn:nbn:se:umu:diva-147843DOI: 10.1137/16M1103890ISI: 000431100400039OAI: oai:DiVA.org:umu-147843DiVA, id: diva2:1207059
Available from: 2018-05-18 Created: 2018-05-18 Last updated: 2018-06-09Bibliographically approved

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Adlerborn, BjörnKarlsson, LarsKågström, Bo

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