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
Link To Document :
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