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
来源：
ROMANIAN STATISTICAL REVIEW | 2015年 / 03期
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
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