A BBN-based framework for adaptive IP-reuse

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 con...

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Main Authors: Azman, Amelia Wong, Bigdeli, Abbas, Biglari-Abhari, Morteza, Mohd Mustafah, Yasir, Lovell, Brian
Format: Conference or Workshop Item
Language:English
Published: ACM 2009
Subjects:
Online Access:http://irep.iium.edu.my/28264/
http://irep.iium.edu.my/28264/
http://irep.iium.edu.my/28264/1/A_BBN-based_Framework_for_Adaptive_IP-Reuse.pdf
id iium-28264
recordtype eprints
spelling iium-282642013-09-17T09:14:49Z http://irep.iium.edu.my/28264/ A BBN-based framework for adaptive IP-reuse Azman, Amelia Wong Bigdeli, Abbas Biglari-Abhari, Morteza Mohd Mustafah, Yasir Lovell, Brian T Technology (General) 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. ACM 2009 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/28264/1/A_BBN-based_Framework_for_Adaptive_IP-Reuse.pdf 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. http://doi.acm.org/10.1145/1667520.1667521
repository_type Digital Repository
institution_category Local University
institution International Islamic University Malaysia
building IIUM Repository
collection Online Access
language English
topic T Technology (General)
spellingShingle T Technology (General)
Azman, Amelia Wong
Bigdeli, Abbas
Biglari-Abhari, Morteza
Mohd Mustafah, Yasir
Lovell, Brian
A BBN-based framework for adaptive IP-reuse
description 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.
format Conference or Workshop Item
author Azman, Amelia Wong
Bigdeli, Abbas
Biglari-Abhari, Morteza
Mohd Mustafah, Yasir
Lovell, Brian
author_facet Azman, Amelia Wong
Bigdeli, Abbas
Biglari-Abhari, Morteza
Mohd Mustafah, Yasir
Lovell, Brian
author_sort Azman, Amelia Wong
title A BBN-based framework for adaptive IP-reuse
title_short A BBN-based framework for adaptive IP-reuse
title_full A BBN-based framework for adaptive IP-reuse
title_fullStr A BBN-based framework for adaptive IP-reuse
title_full_unstemmed A BBN-based framework for adaptive IP-reuse
title_sort bbn-based framework for adaptive ip-reuse
publisher ACM
publishDate 2009
url http://irep.iium.edu.my/28264/
http://irep.iium.edu.my/28264/
http://irep.iium.edu.my/28264/1/A_BBN-based_Framework_for_Adaptive_IP-Reuse.pdf
first_indexed 2023-09-18T20:41:45Z
last_indexed 2023-09-18T20:41:45Z
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