• DocumentCode
    625592
  • Title

    Virtual Systolic Array for QR Decomposition

  • Author

    Kurzak, Jakub ; Luszczek, Piotr ; Gates, Mark ; Yamazaki, Ichitaro ; Dongarra, Jack

  • Author_Institution
    Univ. of Tennessee, Knoxville, TN, USA
  • fYear
    2013
  • fDate
    20-24 May 2013
  • Firstpage
    251
  • Lastpage
    260
  • Abstract
    Systolic arrays offer a very attractive, data-centric, execution model as an alternative to the von Neumann architecture. Hardware implementations of systolic arrays turned out not to be viable solutions in the past. This article shows how the systolic design principles can be applied to a software solution to deliver an algorithm with unprecedented strong scaling capabilities. Systolic array for the QR decomposition is developed and a virtualization layer is used for mapping of the algorithm to a large distributed memory system. Strong scaling properties are discovered, superior to existing solutions.
  • Keywords
    data flow computing; distributed memory systems; mathematics computing; matrix decomposition; parallel algorithms; systolic arrays; QR decomposition; data-centric execution model; distributed memory system; hardware implementation; software solution; strong scaling capabilities; systolic design principles; virtual systolic array; virtualization layer; Arrays; Hardware; Kernel; Program processors; Tiles; QR decomposition; dataflow programming; message passing; multi-core; roofline model; systolic array;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel & Distributed Processing (IPDPS), 2013 IEEE 27th International Symposium on
  • Conference_Location
    Boston, MA
  • ISSN
    1530-2075
  • Print_ISBN
    978-1-4673-6066-1
  • Type

    conf

  • DOI
    10.1109/IPDPS.2013.119
  • Filename
    6569816