• DocumentCode
    329836
  • Title

    Framework for hardware/software partitioning utilizing Bayesian belief networks

  • Author

    Olson, John T. ; Rozenblit, Jerzy W.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Arizona Univ., Tucson, AZ, USA
  • Volume
    4
  • fYear
    1998
  • fDate
    11-14 Oct 1998
  • Firstpage
    3983
  • Abstract
    In heterogeneous systems design, partitioning of the functional specifications into hardware and software components is an important procedure. Often, a hardware platform is chosen and the software is mapped onto the existing partial solution, or the actual partitioning is performed in an ad hoc manner. The partitioning approach presented is novel in that it uses Bayesian belief networks (BBNs) to categorize functional components into hardware and software classifications. First, the motivation and background material are presented. Then, a case study of a programmable thermostat is developed to illustrate the BBN approach. The outcomes of the partitioning process are discussed and placed in a larger design context, called model-based co-design
  • Keywords
    Bayes methods; belief networks; formal specification; intelligent design assistants; systems analysis; Bayesian belief networks; directed acyclic graph; functional specifications; hardware partitioning; heterogeneous systems; model-based design; software partitioning; Bayesian methods; Context modeling; Equations; Hardware; Random variables; Software design; Software performance; Thermostats;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics, 1998. 1998 IEEE International Conference on
  • Conference_Location
    San Diego, CA
  • ISSN
    1062-922X
  • Print_ISBN
    0-7803-4778-1
  • Type

    conf

  • DOI
    10.1109/ICSMC.1998.726711
  • Filename
    726711