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Looking back at dense linear algebra software

delete2014-07-01
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P
Piotr Łuszczek
J
Jakub Kurzak
J
Jack Dongarra *
DOI:10.1016/j.jpdc.2013.10.005delete
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Abstract

Abstract

En 中文
Over the years, computational physics and chemistry served as an ongoing source of problems that demanded the ever increasing performance from hardware as well as the software that ran on top of it. Most of these problems could be translated into solutions for systems of linear equations: the very topic of numerical linear algebra. Seemingly then, a set of efficient linear solvers could be solving important scientific problems for years to come. We argue that dramatic changes in hardware designs precipitated by the shifting nature of the marketplace of computer hardware had a continuous effect on the software for numerical linear algebra. The extraction of high percentages of peak performance continues to require adaptation of software. If the past history of this adaptive nature of linear algebra software is any guide then the future theme will feature changes as well - changes aimed at harnessing the incredible advances of the evolving hardware infrastructure. Published by Elsevier Inc.
Keywords:
Decompositional approach
Parallel algorithms
Dense linear algebra
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Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Journal of Parallel and Distributed Computing cover
Journal of Parallel and Distributed Computing
IF:
4
Papers:
3.8K
Citations:
4.8K

Organization

U
University of Tennessee Knoxville
Scholars:
1.1W
Papers: 9.4K
Citations: 17
University of Tennessee System cover
University of Tennessee System
Scholars:
2.9W
Papers: 2.7W
Citations: 115
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