A BBN-based framework for adaptive IP-reuse

Azman, Amelia Wong and Bigdeli, Abbas and Biglari-Abhari, Morteza and Mohd Mustafah, Yasir and Lovell, Brian (2009) A BBN-based framework for adaptive IP-reuse. In: Proceedings of the 6th FPGAworld Conference, 9 Sept. 2009, Kista, Stockholm, Sweden.

PDF - Published Version Restricted to Repository staff only Download (816kB) | Request a copy

Abstract

The complexity of implementing vision algorithm on embedded systems can greatly benefit from research in HW/SW partitioning and IP-reuse. This paper presents a novel research work of a hybrid HW/SW partitioning method that combines heuristic and knowledge-based approaches to satisfy user-defined constraints. In order to achieve this objective, Bayesian Belief Network (BBN) is utilised and incorporated into the framework to produce a reliable HW/SW partitioning for a given vision algorithm. To provide a better convergence, software weight is incorporated into the link matrices. The outcome of the framework will be the partitioned modules that satisfy the user-defined timing and resource constraints. In this paper, we also report on comparison of our proposed framework with the previous work reported in the literature including: BBN by University of Arizona, the exhaustive algorithm and the greedy algorithm.

Item Type:	Conference or Workshop Item (Full Paper)
Additional Information:	4858/28264
Uncontrolled Keywords:	BBN-based framework
Subjects:	T Technology > T Technology (General)
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering
Depositing User:	Dr Yasir Mohd Mustafah
Date Deposited:	17 Sep 2013 17:14
Last Modified:	17 Sep 2013 17:14
URI:	http://irep.iium.edu.my/id/eprint/28264

Actions (login required)

View Item