• DocumentCode
    12134
  • Title

    The Impact of Heterogeneous Computing on Workflows for Biomolecular Simulation and Analysis

  • Author

    Cheatham, Thomas E. ; Roe, Daniel R.

  • Author_Institution
    Univ. of Utah, Salt Lake City, UT, USA
  • Volume
    17
  • Issue
    2
  • fYear
    2015
  • fDate
    Mar.-Apr. 2015
  • Firstpage
    30
  • Lastpage
    39
  • Abstract
    The field of biomolecular simulation has matured to where detailed, accurate, and functionally relevant information that complements experimental data about the structure, dynamics, and interactions of biomolecules can now be routinely discovered. This has been enabled by access to large-scale and heterogeneous high-performance computing resources, including special-purpose hardware. The improved performance of modern simulation methods coupled with hardware advances is shifting the rate-limiting steps of common biomolecular simulations of small to moderately sized systems from the generation of data (for example, via production molecular dynamics simulations that used to take weeks or even months) to the pre- and postprocessing phases of the workflow, namely, simulation setup and data processing, management, and analysis. Because the computational resources that are optimal for generating data aren´t necessarily the same as for processing that data, access to heterogeneous computational resources enables a broader exploration of biomolecular structure and dynamics by facilitating distinct aspects of typical biomolecular simulation workflows, which might not be as efficient on a one-size-fits-all computational platform.
  • Keywords
    bioinformatics; molecular biophysics; parallel processing; biomolecular analysis; biomolecular simulation; biomolecular structure; biomolecule interaction; data analysis; data management; data processing; heterogeneous computational resources; heterogeneous high-performance computing resources; large-scale high-performance computing resources; modern simulation methods; molecular dynamics simulations; one-size-fits-all computational platform; Analytical models; Biological system modeling; Chemistry; Computational modeling; High performance computing; Molecular biophysics; Scientific computing; Biomolecular simulation; GPUs; HPC; analysis; enhanced sampling; heterogeneous computing; high-performance computing; molecular dynamics; scientific computing;
  • fLanguage
    English
  • Journal_Title
    Computing in Science & Engineering
  • Publisher
    ieee
  • ISSN
    1521-9615
  • Type

    jour

  • DOI
    10.1109/MCSE.2015.7
  • Filename
    7006387