• DocumentCode
    33974
  • Title

    Parallel Simulation of Pore Networks Using Multicore CPUs

  • Author

    Matadamas-Hernandez, J. ; Roman-Alonso, G. ; Rojas-Gonzalez, F. ; Castro-Garcia, M.A. ; Boukerche, Azzedine ; Aguilar-Cornejo, M. ; Cordero-Sanchez, S.

  • Author_Institution
    Dept. de Ing. Electr., Univ. Autonoma Metropolitana, Mexico City, Mexico
  • Volume
    63
  • Issue
    6
  • fYear
    2014
  • fDate
    Jun-14
  • Firstpage
    1513
  • Lastpage
    1525
  • Abstract
    Pore networks can be simulated in silico by using the dual site-bond Model. In this approach, a set of cavities (sites) are interconnected to each other by means of a set of throats (bonds), while considering that each site should be always larger than any of its delimiting bonds. The NoMISS greedy algorithm has been implemented recently in order to address this task; nevertheless, even if this procedure is relatively fast, there arises problems related to large memory consumption and long computing time, as pore networks become somewhat large. Here, three parallel methods are proposed to allow a proficient construction of large pore networks. The first method is a parallel Monte Carlo procedure, which applies a number of exchanges among pore sizes in order to obtain a valid pore network. The other two methods are parallel versions of the pioneering NoMISS greedy algorithm. The first version uses a static data partitioning to speed up the running time, whilst the second applies a dynamic data distribution policy to improve the pore network quality. The obtained results show the behavior of each proposed version with respect to their performance and quality, by employing the resources of a 125-core Linux cluster.
  • Keywords
    Linux; Monte Carlo methods; greedy algorithms; materials science computing; multiprocessing systems; multiprocessor interconnection networks; parallel algorithms; parallel memories; Linux cluster; NoMISS greedy algorithm; cavity interconnection; cubic pore network quality; delimiting bonds; dual site-bond model; dynamic data distribution policy; memory consumption; multicore CPU; parallel Monte Carlo procedure; parallel method; parallel simulation; static data partitioning; Algorithm design and analysis; Computational modeling; Greedy algorithms; Lattices; Media; Monte Carlo methods; Multicore processing; Parallel greedy algorithm; cubic pore networks; dual site-bond model; dynamic data distribution; multi-core cluster programming; parallel Monte Carlo method;
  • fLanguage
    English
  • Journal_Title
    Computers, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9340
  • Type

    jour

  • DOI
    10.1109/TC.2012.197
  • Filename
    6275436