Hardware/Software Partitioning using Bayesian Belief Networks

John T. Olson, Jerzy Rozenblit, Witold Jacak, Claudio Talarico

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)

Abstract

In heterogeneous system design, partitioning of the functional specifications into hardware (HW) and software (SW) components is an important procedure. Often, an HW platform is chosen, and the SW is mapped onto the existing partial solution, or the actual partitioning is performed in an ad hoc manner. The partitioning approach presented here is novel in that it uses Bayesian belief networks (BBNs) to categorize functional components into HW and SW classifications. The BBN's ability to propagate evidence permits the effects of a classification decision that is made about one function to be felt throughout the entire network. In addition, because BBNs have a belief of hypotheses as their core, a quantitative measurement as to the correctness of a partitioning decision is achieved. A methodology for automatically generating the qualitative structural portion of BBN and the quantitative link matrices is given. 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, which is called model-based codesign.

Original languageEnglish
Pages (from-to)655-668
Number of pages14
JournalIEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS
Volume37
Issue number5
DOIs
Publication statusPublished - Sept 2007

Keywords

  • Hardware and software partitioning
  • heterogenous systems desgn
  • codesign
  • Model-based codesign
  • Hardware/software partitioning
  • Heterogenous system design

Fingerprint

Dive into the research topics of 'Hardware/Software Partitioning using Bayesian Belief Networks'. Together they form a unique fingerprint.

Cite this