• DocumentCode
    167444
  • Title

    Comparison of Parallel Programming Models on Intel MIC Computer Cluster

  • Author

    Chenggang Lai ; Zhijun Hao ; Miaoqing Huang ; Xuan Shi ; Haihang You

  • Author_Institution
    Univ. of Arkansas, Fayetteville, AK, USA
  • fYear
    2014
  • fDate
    19-23 May 2014
  • Firstpage
    925
  • Lastpage
    932
  • Abstract
    Coprocessors based on Intel Many Integrated Core (MIC) Architecture have been adopted in many high-performance computer clusters. Typical parallel programming models, such as MPI and OpenMP, are supported on MIC processors to achieve the parallelism. In this work, we conduct a detailed study on the performance and scalability of the MIC processors under different programming models using the Beacon computer cluster. Followings are our findings. (1) The native MPI programming model on the MIC processors is typically better than the offload programming model, which offloads the workload to MIC cores using OpenMP, on Beacon computer cluster. (2) On top of the native MPI programming model, multithreading inside each MPI process can further improve the performance for parallel applications on computer clusters with MIC coprocessors. (3) Given a fixed number of MPI processes, it is a good strategy to schedule these MPI processes to as few MIC processors as possible to reduce the cross-processor communication overhead. (4) The hybrid MPI programming model, in which data processing is distributed to both MIC cores and CPU cores, can outperform the native MPI programming model.
  • Keywords
    application program interfaces; coprocessors; multi-threading; Beacon computer cluster; Intel MIC computer cluster; MIC coprocessors; MPI programming model; OpenMP; high-performance computer clusters; many integrated core architecture; multi-threading; parallel programming models; Computational modeling; Computers; Coprocessors; Interpolation; Microwave integrated circuits; Performance evaluation; Programming; Intel MIC processor; MPI; OpenMP; parallel programming model; performance evaluation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel & Distributed Processing Symposium Workshops (IPDPSW), 2014 IEEE International
  • Conference_Location
    Phoenix, AZ
  • Print_ISBN
    978-1-4799-4117-9
  • Type

    conf

  • DOI
    10.1109/IPDPSW.2014.105
  • Filename
    6969481