Accelerating R with high performance linear algebra libraries

被引:0
作者
Oancea, Bogdan [1 ,2 ]
Andrei, Tudorel [2 ,3 ]
Dragoescu, Raluca Mariana [3 ]
机构
[1] Nicolae Titulescu Univ Bucharest, Bucharest, Romania
[2] Natl Stat Inst Romania, Bucharest, Romania
[3] Bucharest Univ Econ Studies, Bucharest, Romania
关键词
linear algebra; BLAS; high performance computing;
D O I
暂无
中图分类号
O1 [数学]; C [社会科学总论];
学科分类号
03 ; 0303 ; 0701 ; 070101 ;
摘要
Linear algebra routines are basic building blocks for the statistical software. In this paper we analyzed how can we improve R performance for matrix computations. We benchmarked few matrix operations using the standard linear algebra libraries included in the R distribution and high performance libraries like OpenBLAS, GotoBLAS and MKL. Our tests showed the best results are obtained with the MKL library, the other two libraries having similar performances, but lower than MKL.
引用
收藏
页码:109 / 117
页数:9
相关论文
共 50 条
  • [31] SUPERTROPICAL LINEAR ALGEBRA
    Izhakian, Zur
    Knebusch, Manfred
    Rowen, Louis
    PACIFIC JOURNAL OF MATHEMATICS, 2013, 266 (01) : 43 - 75
  • [32] VOBLA: A Vehicle for Optimized Basic Linear Algebra
    Beaugnon, Ulysse
    Kravets, Alexey
    van Haastregt, Sven
    Baghdadi, Riyadh
    Tweed, David
    Absar, Javed
    Lokhmotov, Anton
    ACM SIGPLAN NOTICES, 2014, 49 (05) : 115 - 124
  • [33] Computability in linear algebra
    Ziegler, M
    Brattka, V
    THEORETICAL COMPUTER SCIENCE, 2004, 326 (1-3) : 187 - 211
  • [34] Homotopy linear algebra
    Galvez-Carrillo, Imma
    Kock, Joachim
    Tonks, Andrew
    PROCEEDINGS OF THE ROYAL SOCIETY OF EDINBURGH SECTION A-MATHEMATICS, 2018, 148 (02) : 293 - 325
  • [35] Reliable Generation of High-Performance Matrix Algebra
    Nelson, Thomas
    Belter, Geoffrey
    Siek, Jeremy G.
    Jessup, Elizabeth
    Norris, Boyana
    ACM TRANSACTIONS ON MATHEMATICAL SOFTWARE, 2015, 41 (03):
  • [36] An introduction to linear algebra
    Wise, BM
    Gallagher, NB
    CRITICAL REVIEWS IN ANALYTICAL CHEMISTRY, 1998, 28 (01) : 1 - 19
  • [37] High-performance computing in accelerating structure design and analysis
    Li, ZH
    Folwell, N
    Ge, LX
    Guetz, A
    Ivanov, V
    Kowalski, M
    Lee, LQ
    Ng, CK
    Schussman, G
    Stingelin, L
    Uplenchwar, R
    Wolf, M
    Xiao, LL
    Ko, K
    NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT, 2006, 558 (01) : 168 - 174
  • [38] BLASFEO: Basic Linear Algebra Subroutines for Embedded Optimization
    Frison, Gianluca
    Kouzoupis, Dimitris
    Sartor, Tommaso
    Zanelli, Andrea
    Diehl, Moritz
    ACM TRANSACTIONS ON MATHEMATICAL SOFTWARE, 2018, 44 (04):
  • [39] LINEAR ALGEBRA APPROACH TO NEURAL ASSOCIATIVE MEMORIES AND NOISE PERFORMANCE OF NEURAL CLASSIFIERS
    CHERKASSKY, V
    FASSETT, K
    VASSILAS, N
    IEEE TRANSACTIONS ON COMPUTERS, 1991, 40 (12) : 1429 - 1435
  • [40] Improving the performance of classical linear algebra iterative methods via hybrid parallelism
    Martinez-Ferrer, Pedro J.
    Arslan, Tufan
    Beltran, Vicenc
    JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING, 2023, 179