BLASFEO: Basic Linear Algebra Subroutines for Embedded Optimization

• Published in: ACM transactions on mathematical software 2018-12, Vol.44 (4), p.1-30
• Main Authors: Frison, Gianluca, Kouzoupis, Dimitris, Sartor, Tommaso, Zanelli, Andrea, Diehl, Moritz
• Format: Article
• Language: English
• ISSN: 0098-3500; 1557-7295
• DOI: 10.1145/3210754

Basic Linear Algebra Subroutines for Embedded Optimization (BLASFEO) is a dense linear algebra library providing high-performance implementations of BLAS- and LAPACK-like routines for use in embedded optimization and small-scale high-performance computing, in general. A key difference with respect to existing high-performance implementations of BLAS is that the computational performance is optimized for small- to medium-scale matrices, i.e., for sizes up to a few hundred. BLASFEO comes with three different implementations: a high-performance implementation aimed at providing the highest performance for matrices fitting in cache, a reference implementation providing portability and embeddability and optimized for very small matrices, and a wrapper to standard BLAS and LAPACK providing high performance on large matrices. The three implementations of BLASFEO together provide high-performance dense linear algebra routines for matrices ranging from very small to large. Compared to both open-source and proprietary highly tuned BLAS libraries, for matrices of size up to about 100, the high-performance implementation of BLASFEO is about 20--30% faster than the corresponding level 3 BLAS routines and two to three times faster than the corresponding LAPACK routines.