• DocumentCode
    1350366
  • Title

    Accelerating Quantum Monte Carlo Simulations of Real Materials on GPU Clusters

  • Author

    Esler, K.P. ; Kim, Jeongnim ; Ceperley, D.M. ; Shulenburger, L.

  • Author_Institution
    Univ. of Illinois at Urbana-Champaign, Urbana, IL, USA
  • Volume
    14
  • Issue
    1
  • fYear
    2012
  • Firstpage
    40
  • Lastpage
    51
  • Abstract
    More accurate than mean-field methods and more scalable than quantum chemical methods, continuum quantum Monte Carlo (QMC) is an invaluable tool for predicting the properties of matter from fundamental principles. Because QMC algorithms offer multiple forms of parallelism, they´re ideal candidates for acceleration in the many-core paradigm.
  • Keywords
    Monte Carlo methods; graphics processing units; multiprocessing systems; parallel processing; quantum computing; GPU cluster; QMC algorithm; continuum quantum Monte Carlo simulation; many core paradigm; Computational modeling; Graphics processing unit; Mathematical model; Monte Carlo methods; Quantum methods; Wave functions; Component; Monte Carlo; graphics processors; physics; scientific computing;
  • fLanguage
    English
  • Journal_Title
    Computing in Science & Engineering
  • Publisher
    ieee
  • ISSN
    1521-9615
  • Type

    jour

  • DOI
    10.1109/MCSE.2010.122
  • Filename
    5601669
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1350366