The performances of R GPU implementations of the GMRES method

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15210%2F18%3A73587584" target="_blank" >RIV/61989592:15210/18:73587584 - isvavai.cz</a>

Výsledek na webu

<a href="http://www.revistadestatistica.ro/wp-content/uploads/2018/03/RRS_1_2018_A09.pdf" target="_blank" >http://www.revistadestatistica.ro/wp-content/uploads/2018/03/RRS_1_2018_A09.pdf</a>

DOI - Digital Object Identifier

—

Jazyk výsledku

angličtina

Název v původním jazyce

The performances of R GPU implementations of the GMRES method

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

The performances of R GPU implementations of the GMRES method

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

50202 - Applied Economics, Econometrics

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2018

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Romanian Statistical Review

ISSN

1018-046X

e-ISSN

—

Svazek periodika

2018

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

RO - Rumunsko

Počet stran výsledku

12

Strana od-do

121-132

Kód UT WoS článku

000429314700009

EID výsledku v databázi Scopus

—