Evaluation of Open-Source Linear Algebra Libraries targeting ARM and RISC-V Architectures
Christian Fibich, Stefan Tauner, Peter Rössler, Martin Horauer
DOI: http://dx.doi.org/10.15439/2020F145
Citation: Proceedings of the 2020 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 21, pages 663–672 (2020)
Abstract. Basic Linear Algebra Subprograms (BLAS) has emerged as a de-facto standard interface for libraries providing linear algebra functionality. The advent of powerful devices for Internet of Things (IoT) nodes enables the reuse of existing BLAS implementations in these systems. This calls for a discerning evaluation of the properties of these libraries on embedded processors.
References
- BLAST Forum, “Basic Linear Algebra Subprograms Technical Forum Standard,” https://netlib.org/blas/blast-forum/blas-report.pdf, 2020-06-27, University of Tennessee, Knoxville, Tennessee, Tech. Rep., 2001.
- M. Koehler and J. Saak, “FlexiBLAS - a flexible BLAS library with runtime exchangeable backends,” https://www.netlib.org/lapack/lawnspdf/lawn284.pdf, 2020-06-27, LAPACK Working Notes, Tech. Rep., 2013.
- F. G. Van Zee and R. A. Van de Geijn, “BLIS: A framework for rapidly instantiating BLAS functionality,” ACM Transactions on Mathematical Software, vol. 41, no. 3, pp. 1–33, 2015. http://dx.doi.org/10.1145/2764454
- D. G. Spampinato and M. Püschel, “A basic linear algebra compiler,” in Proceedings of Annual IEEE/ACM International Symposium on Code Generation and Optimization, ser. CGO ’14. New York, NY, USA: Association for Computing Machinery, 2014. doi: 10.1145/2544137.2544155 p. 23–32.
- N. Kyrtatas and D. G. Spampinato, “A Basic Linear Algebra Compiler for Embedded Processors,” 2015 Design, Automation Test in Europe Conference Exhibition (DATE), pp. 1054–1059, 2015. http://dx.doi.org/10.3929/ethz-a-010144458
- G. Frison, D. Kouzoupis, T. Sartor, A. Zanelli, and M. Diehl, “BLAS-FEO: Basic linear algebra subroutines for embedded optimization,” ACM Trans. Math. Softw., vol. 44, no. 4, pp. 42:1–42:30, Jul. 2018. doi: 10.1145/3210754
- G. Frison, T. Sartor, A. Zanelli, and M. Diehl, “The BLAS API of BLAS-FEO: Optimizing performance for small matrices,” ACM Transactions on Mathematical Software, vol. 46, no. 2, May 2020. http://dx.doi.org/10.1145/3378671
- C. Fibich, S. Tauner, P. Rössler, M. Horauer, M. Krapfenbauer, M. Linauer, M. Matschnig, and H. Taucher, “Evaluation of open-source linear algebra libraries in embedded applications,” in 2019 8th Mediterranean Conference on Embedded Computing (MECO), June 2019. http://dx.doi.org/10.1109/MECO.2019.8760041 pp. 1–6.
- M. Gautschi, P. D. Schiavone, A. Traber, I. Loi, A. Pullini, D. Rossi, E. Flamand, F. K. Gürkaynak, and L. Benini, “Near-threshold RISC-V core with DSP extensions for scalable IoT endpoint devices,” IEEE Transactions on Very Large Scale Integration (VLSI) Systems, vol. 25, no. 10, pp. 2700–2713, Oct. 2017. http://dx.doi.org/10.1109/TVLSI.2017.2654506
- R. C. Whaley, A. Petitet, and J. J. Dongarra, “Automated empirical optimizations of software and the ATLAS project,” Parallel Computing, vol. 27, no. 1, pp. 3–35, 2001. http://dx.doi.org/10.1016/S0167-8191(00)00087-9
- K. Goto and R. A. v. d. Geijn, “Anatomy of high-performance matrix multiplication,” ACM Transactions on Mathematical Software, vol. 34, no. 3, pp. 12:1–12:25, May 2008. http://dx.doi.org/10.1145/1356052.1356053
- Altera Corporation, “cv 5v4: Cyclone V Hard Processor System Technical Reference Manual,” https://www.intel.com/content/dam/www/programmable/us/en/pdfs/literature/hb/cyclone-v/cv 5v4.pdf, 2020-06-27, July 2018.