Accelerating R with high performance linear algebra libraries

Bogdan Oancea, Tudorel Andrei () and Raluca Mariana Dragoescu
Additional contact information
Raluca Mariana Dragoescu: The Bucharest University of Economic Studies

Romanian Statistical Review, 2015, vol. 63, issue 3, 109-117

Abstract: 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.

Keywords: R; linear algebra; BLAS; high performance computing (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.revistadestatistica.ro/wp-content/uploads/2015/07/RRS3_2015_A10.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:rsr:journl:v:63:y:2015:i:3:p:109-117

Access Statistics for this article

More articles in Romanian Statistical Review from Romanian Statistical Review Contact information at EDIRC.
Bibliographic data for series maintained by Adrian Visoiu ().