• DocumentCode
    1446677
  • Title

    FPGA-Based High-Performance and Scalable Block LU Decomposition Architecture

  • Author

    Jaiswal, Manish Kumar ; Chandrachoodan, Nitin

  • Author_Institution
    ICFAI Univ., Dehradun, India
  • Volume
    61
  • Issue
    1
  • fYear
    2012
  • Firstpage
    60
  • Lastpage
    72
  • Abstract
    Decomposition of a matrix into lower and upper triangular matrices (LU decomposition) is a vital part of many scientific and engineering applications, and the block LU decomposition algorithm is an approach well suited to parallel hardware implementation. This paper presents an approach to speed up implementation of the block LU decomposition algorithm using FPGA hardware. Unlike most previous approaches reported in the literature, the approach does not assume the matrix can be stored entirely on chip. The memory accesses are studied for various FPGA configurations, and a schedule of operations for scaling well is shown. The design has been synthesized for FPGA targets and can be easily retargeted. The design outperforms previous hardware implementations, as well as tuned software implementations including the ATLAS and MKL libraries on workstations.
  • Keywords
    field programmable gate arrays; logic design; matrix decomposition; FPGA configurations; FPGA-based high-performance; lower triangular matrices; matrix decomposition; scalable block LU decomposition architecture; upper triangular matrices; Algorithm design and analysis; Field programmable gate arrays; Hardware; Matrix decomposition; Memory management; Parallel processing; ATLAS; FPGA; GPU.; Intel-MKL; LU decomposition; block LU; floating point arithmetics; hardware acceleration; scaling; single/double precision;
  • fLanguage
    English
  • Journal_Title
    Computers, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9340
  • Type

    jour

  • DOI
    10.1109/TC.2011.24
  • Filename
    5710875