Prospectus for a dense linear algebra software library

James Demmel, Beresford Parlett, William Kahan, Ming Gu, David Bindel, Yozo Hida, E. Jason Riedy, Christof Voemel, Jack Dongarra, Jakub Kurzak, Alfredo Buttari, Julie Langou, Stanimire Tomov, Xiaoye Li, Osni Marques, Julien Langou, Piotr Luszczek

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

Dense linear algebra (DLA) forms the core of many scientific computing applications. Consequently, there is continuous interest and demand for the development of increasingly better algorithms in the field. Here “better” has a broad meaning, and includes improved reliability, accuracy, robustness, ease of use, and most importantly new or improved algorithms that would more efficiently use the available computational resources to speed up the computation. The rapidly evolving high end computing systems and the close dependence of DLA algorithms on the computational environment is what makes the field particularly dynamic.

Original languageEnglish
Title of host publicationHandbook of Parallel Computing
Subtitle of host publicationModels, Algorithms and Applications
PublisherCRC Press
Pages29-1-29-22
ISBN (Electronic)9781420011296
ISBN (Print)9781584886235
DOIs
StatePublished - Jan 1 2007

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