Accelerating R with high performance linear algebra libraries

TL;DR

This paper evaluates the performance of R's matrix computations using various linear algebra libraries, finding MKL offers the best speed improvements over standard and other high-performance libraries.

Contribution

It demonstrates how integrating high-performance libraries like MKL can significantly accelerate R's matrix operations.

Findings

MKL outperforms OpenBLAS and GotoBLAS in R matrix computations

High-performance libraries improve R's computational speed

Benchmark results guide library selection for R users

Abstract

Linear algebra routines are basic building blocks for the statistical software. In this paper we analyzed how can we can 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 the best results are obtained with the MKL library, the other two libraries having similar performances, but lower than MKL