• DocumentCode
    2055542
  • Title

    Genetic algorithm for ordering and reduction of BDDs for MIMO circuits

  • Author

    Bansal, Mayank ; Agarwal, Abhishek

  • Author_Institution
    Thapar Univ., Patiala, India
  • fYear
    2013
  • fDate
    29-31 Aug. 2013
  • Firstpage
    411
  • Lastpage
    414
  • Abstract
    Boolean function manipulation is an important component of many logic synthesis algorithms including logic optimization and logic verification of combinational and sequential circuits. Digital integrated circuits, often represented as Boolean functions, can be best-manipulated graphically in the form of Binary Decision Diagrams (BDD). Reduced-ordered binary decision diagrams (ROBDDs) are data structures for representation and manipulation of Boolean functions. The variable ordering largely influences the size of the BDD, varying from linear to exponential. In this paper, an evolutionary algorithm named genetic algorithm has been proposed for minimization of shared ordered BDDs by finding the optimal input variable ordering that aims to minimize the node count using Genetic algorithm. The proposed algorithm gives upto 79% less nodes for LGSynth93 Benchmark Circuits.
  • Keywords
    MIMO systems; binary decision diagrams; genetic algorithms; BDDs; LGSynth93 Benchmark Circuits; MIMO circuits; genetic algorithm; minimization; optimal input variable ordering; reduced-ordered binary decision diagrams; Biological cells; Boolean functions; Data structures; Genetic algorithms; Minimization; Sociology; Statistics; BDDs; Genetic Algorithm; LGSynth93. MIMO; Optimization; Variable Ordering;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Innovative Computing Technology (INTECH), 2013 Third International Conference on
  • Conference_Location
    London
  • Print_ISBN
    978-1-4799-0047-3
  • Type

    conf

  • DOI
    10.1109/INTECH.2013.6653717
  • Filename
    6653717