• DocumentCode
    2793808
  • Title

    Improving Scalability of OpenMP Applications on Multi-core Systems Using Large Page Support

  • Author

    Noronha, Ranjit ; Panda, D.K.

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Ohio State Univ., Columbus, OH
  • fYear
    2007
  • fDate
    26-30 March 2007
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    Modern multi-core architectures have become popular because of the limitations of deep pipelines and heating and power concerns. Some of these multi-core architectures such as the Intel Xeon have the ability to run several threads on a single core. The OpenMP standard for compiler directive based shared memory programming allows the developer an easy path to writing multi-threaded programs and is a natural fit for multi-core architectures. The OpenMP standard uses loop parallelism as a basis for work division among multiple threads. These loops usually use arrays in their computation with different data distributions and access patterns. The performance of accesses to these arrays may be impacted by the underlying page size depending on the frequency and strides of these accesses. In this paper, we discuss the issues and potential benefits from using large pages for OpenMP applications. We design an OpenMP implementation capable of using large pages and evaluate the impact of using large page support available in most modern processors on the performance and scalability of parallel OpenMP applications. Results show an improvement in performance of up to 25% for some applications. It also helps improve the scalability of these applications.
  • Keywords
    message passing; multi-threading; pipeline processing; shared memory systems; loop parallelism; multi-core system; multi-threaded program; openMP application; pipeline processing; scalability; shared memory programming; Computer architecture; Distributed computing; Heating; Parallel processing; Pipelines; Program processors; Scalability; Standards development; Writing; Yarn;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel and Distributed Processing Symposium, 2007. IPDPS 2007. IEEE International
  • Conference_Location
    Long Beach, CA
  • Print_ISBN
    1-4244-0910-1
  • Electronic_ISBN
    1-4244-0910-1
  • Type

    conf

  • DOI
    10.1109/IPDPS.2007.370683
  • Filename
    4228411