Framework for hardware/software partitioning utilizing Bayesian belief networks

John T. Olson, Jerzy W. Rozenblit

Research output: Contribution to journalConference articlepeer-review

3 Scopus citations

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 here 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 codesign.

Original languageEnglish (US)
Pages (from-to)3983-3988
Number of pages6
JournalProceedings of the IEEE International Conference on Systems, Man and Cybernetics
Volume4
StatePublished - 1998
EventProceedings of the 1998 IEEE International Conference on Systems, Man, and Cybernetics. Part 3 (of 5) - San Diego, CA, USA
Duration: Oct 11 1998Oct 14 1998

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Hardware and Architecture

Fingerprint

Dive into the research topics of 'Framework for hardware/software partitioning utilizing Bayesian belief networks'. Together they form a unique fingerprint.

Cite this