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The performances of R GPU implementations of the GMRES method

The result's identifiers

  • Result code in 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>

  • Result on the web

    <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

Alternative languages

  • Result language

    angličtina

  • Original language name

    The performances of R GPU implementations of the GMRES method

  • Original language 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.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    50202 - Applied Economics, Econometrics

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2018

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    Romanian Statistical Review

  • ISSN

    1018-046X

  • e-ISSN

  • Volume of the periodical

    2018

  • Issue of the periodical within the volume

    1

  • Country of publishing house

    RO - ROMANIA

  • Number of pages

    12

  • Pages from-to

    121-132

  • UT code for WoS article

    000429314700009

  • EID of the result in the Scopus database