This paper describes the Automatically Tuned Linear Algebra Software (ATLAS) project, as well as the fundamental principles that underly it. ATLAS is an instantiation of a new paradigm in high performance library production and maintenance, which we term automated empirical optimization of software; this style of library management has been created in order to allow software to keep pace with the incredible rate of hardware advancement inherent in Moore’s Law. ATLAS is the application of this new paradigm to linear algebra software, with the present emphasis on the basic linear algebra subprograms, a widely used, performance-critical, linear algebra kernel library

This software is also referenced in ORMS.

References in zbMATH (referenced in 197 articles , 1 standard article )

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  8. Vadhiyar, Sathish S.; Fagg, Graham E.; Dongarra, Jack J.: Towards an accurate model for collective communications (2001)
  9. Vuduc, Richard; Demmel, James W.; Bilmes, Jeff: Statistical models for automatic performance tuning (2001)
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  11. Bridson, Robert; Tang, Wei-Pai: Refining an approximate inverse (2000)
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