• DocumentCode
    3581250
  • Title

    Parallel execution of SVM using Symmetrical Multi-Processor (LIBSVM-OMP)

  • Author

    Md Salleh, Nur Shakirah ; Bin Mohamad Shariff, Amirul Shafiq ; Bin Kamsani, Muhammad Ikhwan Afiq ; Nazeri, Surizal

  • Author_Institution
    Dept. of Syst. & Networking, Univ. Tenaga Nasional, Kajang, Malaysia
  • fYear
    2014
  • Firstpage
    93
  • Lastpage
    96
  • Abstract
    Parallel computing is a simultaneous use of multiple compute resources such as processors to solve difficult computational problems. It has been used in high-end computing areas such as pattern recognition, defense, web search engine, and medical diagnosis. This paper focuses on the implementation of pattern classification technique, Support Vector Machine (SVM) using Symmetric Multi-Processor (SMP) approach. We have carried out a performance analysis to benchmark the sequential SVM program against the SMP approach. The result shows that the parallelization of SVM training achieves a better performance than the sequential code speed-ups by 15.9s.
  • Keywords
    multiprocessing systems; parallel processing; pattern classification; support vector machines; LIBSVM-OMP; SMP approach; SVM program; classification technique; parallel computing; parallel execution; support vector machine; symmetrical multiprocessor; Algorithms; Computational modeling; Instruction sets; Message systems; Parallel processing; Support vector machines; Training; MNIST dataset; OpenMP; Parallel Computing; Support Vector Machine; Symmetrical Multi-Processing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Technology and Multimedia (ICIMU), 2014 International Conference on
  • Type

    conf

  • DOI
    10.1109/ICIMU.2014.7066610
  • Filename
    7066610