• DocumentCode
    589671
  • Title

    ORCA: An offloading framework for I/O-intensive applications on clusters

  • Author

    Ji Zhang ; Xunfei Jiang ; Yun Tian ; Xiao Qin ; Alghamdi, Mohammed I. ; Assaf, M.A. ; Meikang Qiu

  • Author_Institution
    Auburn Univ., Auburn, AL, USA
  • fYear
    2012
  • fDate
    1-3 Dec. 2012
  • Firstpage
    81
  • Lastpage
    90
  • Abstract
    This paper presents an offloading framework - ORCA - to map I/O-intensive code to a cluster that consists of computing and storage nodes. To reduce data transmission among computing and storage nodes. our offloading framework partitions and schedules CPU-bound and I/O-bound modules to computing nodes and active storage nodes, respectively. From developer´s perspective, ORCA helps them to deal with execution-path control, offloading executable code, and data sharing over a network. Powered by the offloading APIs, developers without any I/O offloading or network programming experience are allowed to write new I/O-intensive code running efficiently on clusters. We implement the ORCA framework on a cluster to quantitatively evaluate performance improvements offered by our approach. We run five real-world applications on both homogeneous and heterogeneous computing environments. Experimental results show ORCA speeds up the performance of all the five tested applications by a factor of up to 90.1% with an average of 75.5%. Moreover, the results confirm that ORCA reduces network burden imposed by I/O-intensive applications by a factor of anywhere between 35 to 68.
  • Keywords
    application program interfaces; input-output programs; workstation clusters; CPU-bound modules; IO-bound modules; IO-intensive applications; IO-intensive code; ORCA; clusters; data transmission; execution-path control; network programming experience; offloading API; offloading framework; Computational modeling; Computer architecture; Computer languages; Educational institutions; Hardware; Performance analysis; I/O intensive; offloading;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Performance Computing and Communications Conference (IPCCC), 2012 IEEE 31st International
  • Conference_Location
    Austin, TX
  • ISSN
    1097-2641
  • Print_ISBN
    978-1-4673-4881-2
  • Type

    conf

  • DOI
    10.1109/PCCC.2012.6407741
  • Filename
    6407741