| Autor: |
Frison, Gianluca, Kouzoupis, Dimitris, Sartor, Tommaso, Zanelli, Andrea, Diehl, Moritz |
| Rok vydání: |
2017 |
| Předmět: |
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| Zdroj: |
ACM Transactions on Mathematical Software (TOMS): Volume 44 Issue 4, August 2018 |
| Druh dokumentu: |
Working Paper |
| DOI: |
10.1145/3210754 |
| Popis: |
BLASFEO is a dense linear algebra library providing high-performance implementations of BLAS- and LAPACK-like routines for use in embedded optimization. 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 aiming 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 one hundred the high-performance implementation of BLASFEO is about 20-30% faster than the corresponding level 3 BLAS routines and 2-3 times faster than the corresponding LAPACK routines. |
| Databáze: |
arXiv |
| Externí odkaz: |
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