• DocumentCode
    1772631
  • Title

    A scalable and compact systolic architecture for linear solvers

  • Author

    Ong, Kevin S. H. ; Fahmy, Suhaib A. ; Keck-Voon Ling

  • Author_Institution
    Sch. of Comput. Eng., Nanyang Technol. Univ., Singapore, Singapore
  • fYear
    2014
  • fDate
    18-20 June 2014
  • Firstpage
    186
  • Lastpage
    187
  • Abstract
    We present a scalable design for accelerating the problem of solving a dense linear system of equations using LU Decomposition. A novel systolic array architecture that can be used as a building block in scientific applications is described and prototyped on a Xilinx Virtex 6 FPGA. This solver has a throughput of around 3.2 million linear systems per second for matrices of size N=4 and around 80 thousand linear systems per second for matrices of size N=16. In comparison with similar work, our design offers up to a 12-fold improvement in speed whilst requiring up to 50% less hardware resources. As a result, a linear system of size N=64 can be implemented on a single FPGA, whereas previous work was limited to a size of N=12 and resorted to complex multi-FPGA architectures to scale. Finally, the scalable design can be adapted to different sized problems with minimum effort.
  • Keywords
    field programmable gate arrays; reconfigurable architectures; systolic arrays; LU decomposition; Xilinx Virtex 6 FPGA; compact systolic architecture; complex multiFPGA architectures; dense linear system; hardware resources; linear solvers; scalable systolic architecture; single FPGA; systolic array architecture; Arrays; Digital signal processing; Educational institutions; Field programmable gate arrays; Hardware; Linear systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Application-specific Systems, Architectures and Processors (ASAP), 2014 IEEE 25th International Conference on
  • Conference_Location
    Zurich
  • Type

    conf

  • DOI
    10.1109/ASAP.2014.6868658
  • Filename
    6868658