The performances of R GPU implementations of the GMRES method

Although the performance of commodity computers has improved drastically with the introduction of multicore processors and GPU computing, the standard R distribution is still based on single-threaded model of computation, using only a small fraction of the computational power available now for most...

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Bibliographic Details
Main Authors: Bogdan Oancea, Richard Pospisil
Format: Article
Language:English
Published: Romanian National Institute of Statistics 2018-03-01
Series:Revista Română de Statistică
Subjects:
R
GPU
Online Access:http://www.revistadestatistica.ro/wp-content/uploads/2018/03/RRS_1_2018_A09.pdf
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spelling doaj-44e9af5ceee5416db215338df15df4f82020-11-25T02:17:16ZengRomanian National Institute of StatisticsRevista Română de Statistică1018-046X1844-76942018-03-01661121132The performances of R GPU implementations of the GMRES methodBogdan Oancea0Richard Pospisil 1University of BucharestPalacky University of OlomoucAlthough the performance of commodity computers has improved drastically with the introduction of multicore processors and GPU computing, the standard R distribution is still based on single-threaded model of computation, using only a small fraction of the computational power available now for most desktops and laptops. Modern statistical software packages rely on high performance implementations of the linear algebra routines there are at the core of several important leading edge statistical methods. In this paper we present a GPU implementation of the GMRES iterative method for solving linear systems. We compare the performance of this implementation with a pure single threaded version of the CPU. We also investigate the performance of our implementation using different GPU packages available now for R such as gmatrix, gputools or gpuR which are based on CUDA or OpenCL frameworks.http://www.revistadestatistica.ro/wp-content/uploads/2018/03/RRS_1_2018_A09.pdfRGPUstatistical softwareGMRES
collection DOAJ
language English
format Article
sources DOAJ
author Bogdan Oancea
Richard Pospisil
spellingShingle Bogdan Oancea
Richard Pospisil
The performances of R GPU implementations of the GMRES method
Revista Română de Statistică
R
GPU
statistical software
GMRES
author_facet Bogdan Oancea
Richard Pospisil
author_sort Bogdan Oancea
title The performances of R GPU implementations of the GMRES method
title_short The performances of R GPU implementations of the GMRES method
title_full The performances of R GPU implementations of the GMRES method
title_fullStr The performances of R GPU implementations of the GMRES method
title_full_unstemmed The performances of R GPU implementations of the GMRES method
title_sort performances of r gpu implementations of the gmres method
publisher Romanian National Institute of Statistics
series Revista Română de Statistică
issn 1018-046X
1844-7694
publishDate 2018-03-01
description Although the performance of commodity computers has improved drastically with the introduction of multicore processors and GPU computing, the standard R distribution is still based on single-threaded model of computation, using only a small fraction of the computational power available now for most desktops and laptops. Modern statistical software packages rely on high performance implementations of the linear algebra routines there are at the core of several important leading edge statistical methods. In this paper we present a GPU implementation of the GMRES iterative method for solving linear systems. We compare the performance of this implementation with a pure single threaded version of the CPU. We also investigate the performance of our implementation using different GPU packages available now for R such as gmatrix, gputools or gpuR which are based on CUDA or OpenCL frameworks.
topic R
GPU
statistical software
GMRES
url http://www.revistadestatistica.ro/wp-content/uploads/2018/03/RRS_1_2018_A09.pdf
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