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ATLAS [20–22, 24, 25] is an ongoing research project that uses empirical tuning to optimize dense linear algebra software. The fruits of this research are embodied in an empirical tuning framework available as an open source/free software package (also referred to as “ATLAS”), which can be downloaded from the ATLAS homepage [23]. ATLAS generates optimized libraries which are also often collectively referred to as “ATLAS,” “ATLAS libraries,” or more precisely, “ATLAS-tuned libraries.” In particular, ATLAS provides a full implementation of the BLAS [6, 7, 10, 12] (Basic Linear Algebra Subprograms) API, and a subset of optimized LAPACK [1] (Linear Algebra PACKage) routines. Because dense linear algebra is rich in operand reuse, many routines can run tens or hundreds of times faster when tuned for the hardware than when written naively. Unfortunately, highly tuned codes are usually not performance portable (i.e., a code transformation that helps...
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Bibliography
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Whaley, R.C. (2011). ATLAS (Automatically Tuned Linear Algebra Software). In: Padua, D. (eds) Encyclopedia of Parallel Computing. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-09766-4_85
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