• DocumentCode
    8718
  • Title

    GPU-Enabled Macromolecular Simulation: Challenges and Opportunities

  • Author

    Taufer, Michela ; Ganesan, Narayan ; Patel, Surabhi

  • Author_Institution
    Dept. of Comput. & Inf. Sci., Univ. of Delaware, Newark, DE, USA
  • Volume
    15
  • Issue
    1
  • fYear
    2013
  • fDate
    Jan.-Feb. 2013
  • Firstpage
    56
  • Lastpage
    65
  • Abstract
    GPU-enabled simulation of fully atomistic macromolecular systems is rapidly gaining momentum, enabled by massive parallelism and the parallelizability of various components of the underlying algorithms and methodologies. Here, we consider key aspects required for obtaining realistic macromolecular systems specifically adapted to GPUs; these aspects include realistic mathematical models and valid simulations.
  • Keywords
    biology computing; graphics processing units; macromolecules; mathematical analysis; GPU-enabled macromolecular simulation; atomistic macromolecular systems; realistic macromolecular systems; realistic mathematical models; Adaptation models; Biological system modeling; Computational modeling; Graphics processing unit; Lattices; Mathematical model; Scientific computing; GPU computing; biomacromolecular structure and function; molecular dynamics; scientific computing;
  • fLanguage
    English
  • Journal_Title
    Computing in Science & Engineering
  • Publisher
    ieee
  • ISSN
    1521-9615
  • Type

    jour

  • DOI
    10.1109/MCSE.2012.42
  • Filename
    6180155