• DocumentCode
    3000373
  • Title

    Parallelizing the Computation of Green Functions for Computational Electromagnetism Problems

  • Author

    Pérez-Alcaraz, Carlos ; Giménez, Domingo ; Álvarez-Melcón, Alejandro ; Quesada, Fernando D.

  • Author_Institution
    Dept. de Inf. y Sist., Univ. of Murcia, Murcia, Spain
  • fYear
    2012
  • fDate
    21-25 May 2012
  • Firstpage
    1370
  • Lastpage
    1377
  • Abstract
    Green functions are used in various fields to solve non homogeneous integral equations with boundary conditions. In some cases it is necessary to obtain these functions in real time or they are used for big problems with a large execution time which should be reduced. To do so, efficient algorithms for the available computational systems must be developed. With the evolution of technology, the computational systems are now parallel, with multicore laptops or desktops with programmable graphic processing units, and with clusters or supercomputers composed by multicore nodes. In this paper, algorithms for Green functions using different parallelism paradigms are developed and compared. The Green functions used are from computational electromagnetism, and important reductions in the execution time are obtained for typical problems with the implemented algorithms.
  • Keywords
    graphics processing units; greedy algorithms; integral equations; computational electromagnetism problems; computational systems; green functions; multicore desktops; multicore laptops; nonhomogeneous integral equations; parallelism paradigms; programmable graphic processing units; Algorithm design and analysis; Graphics processing unit; Green function; Instruction sets; Observers; Parallel processing; Spectral analysis; GPU; Green function; computational electromagnetism; hybrid parallelism; message-passing; parallel computing; shared-memory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel and Distributed Processing Symposium Workshops & PhD Forum (IPDPSW), 2012 IEEE 26th International
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4673-0974-5
  • Type

    conf

  • DOI
    10.1109/IPDPSW.2012.174
  • Filename
    6270804