Automated empirical optimizations of software and the ATLAS project

This paper describes the ATLAS (Automatically Tuned Linear Algebra Software) 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 AEOS (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 (BLAS), a widely used, performance-critical, linear algebra kernel library. This work was supported in part by: U.S. Department of Energy under contract number DE-AC0596OR22464; National Science Foundation Science and Technology Center Cooperative Agreement No. CCR8809615; University of California, Los Alamos National Laboratory, subcontract # B76680017-3Z. Dept. of Computer Sciences, Univ. of TN, Knoxville, TN 37996, [email protected] Dept. of Computer Sciences, Univ. of TN, Knoxville, TN 37996, [email protected] Dept. of Computer Sciences, Univ. of TN, Knoxville, TN 37996, and Mathematical Sciences Section, ORNL, Oak Ridge, TN 37831, [email protected]