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...
| Main Authors: | , , , , |
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| Format: | Proceeding Paper |
| Language: | English |
| Published: |
ACM
2009
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/28264/ http://irep.iium.edu.my/28264/1/A_BBN-based_Framework_for_Adaptive_IP-Reuse.pdf |
| _version_ | 1848779942893977600 |
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| 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 |
| building | IIUM Repository |
| collection | Online Access |
| 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. |
| first_indexed | 2025-11-14T15:25:48Z |
| format | Proceeding Paper |
| id | iium-28264 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T15:25:48Z |
| publishDate | 2009 |
| publisher | ACM |
| recordtype | eprints |
| repository_type | Digital Repository |
| 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 Proceeding Paper 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 |
| 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 |
| title | 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_short | A BBN-based framework for adaptive IP-reuse |
| title_sort | bbn-based framework for adaptive ip-reuse |
| topic | T Technology (General) |
| 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 |