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Software Automatic Tuning pp 19–32Cite as

ATLAS Version 3.9: Overview and Status

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Abstract

This paper describes the widely used ATLAS (Automatically Tuned Linear Algebra Software) project as it stands today. ATLAS is an instantiation of a paradigm in high performance library production and maintenance, which we term AEOS (Automated Empirical Optimization of Software); this style of library management has been created to allow software to keep pace with the incredible rate of hardware advancement inherent in Moore’s Law. ATLAS is the application of this AEOS paradigm to dense linear algebra software. ATLAS produces a full BLAS (Basic Linear Algebra Subprograms) library as well as provides some optimized routines for LAPACK (Linear Algebra PACKage). This paper overviews the basics of what ATLAS is and how it works, highlights some of the recent improvements available as of version 3.9.23, in addition to discussing some of the current challenges and future work.

This work was supported in part by the National Science Foundation, grants NSF CRI CNS-0551504 and NSF HECURA CCF-0833203

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Notes

  1. 1.

    ∗ This work was supported in part by the National Science Foundation, grants NSF CRI CNS-0551504 and NSF HECURA CCF-0833203.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Univ of TX, San Antonio, TX, 78249, USA

    R. Clint Whaley

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  1. R. Clint Whaley
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Correspondence to R. Clint Whaley .

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Editors and Affiliations

  1. Central Research Laboratory, Hitachi Ltd., Higashi-Koigakubo 1-280, Kokubunji-shi, Tokyo, 185-8601, Japan

    Ken Naono

  2. Cray, Inc., Jackson St. 380, St Paul, 55101, Minnesota, USA

    Keita Teranishi

  3. Dept. Computer & Information Sciences, University of Delaware, Smith Hall 101, Newark, 19716, Delaware, USA

    John Cavazos

  4. Dept. Computer Science, University of Tokyo, Hongo 7-3-1, Tokyo, 113-0033, Japan

    Reiji Suda

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Whaley, R.C. (2011). ATLAS Version 3.9: Overview and Status. In: Naono, K., Teranishi, K., Cavazos, J., Suda, R. (eds) Software Automatic Tuning. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-6935-4_2

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  • DOI: https://doi.org/10.1007/978-1-4419-6935-4_2

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