Boltzmann Machine Incorporated Hybrid Neural Fuzzy System for Hardware/Software Partitioning in Embedded System Design

Authors:
Yue Huang;Yong-Soo Kim
Affiliations:
Department of Computer Science in Kyungwon University, Sujeong-Gu, Seongnam-Si, Gyeonggi-Do, 461-701, Korea;Department of Computer Science in Kyungwon University, Sujeong-Gu, Seongnam-Si, Gyeonggi-Do, 461-701, Korea
Venue:
MDAI '07 Proceedings of the 4th international conference on Modeling Decisions for Artificial Intelligence
Year:
2007

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Abstract

Nowadays one of the most vital problems in embedded system co-design is Hardware/Software (HW/SW) partitioning. Due to roughly assumed parameters in design specification and imprecise benchmarks for judging the solution's quality, embedded system designers have been working on finding a more efficient method for HW/SW partitioning for years. We propose an application of a hybrid neural fuzzy system incorporating Boltzmann machine to the HW/SW partitioning problem. Its architecture and performance estimation against other popular algorithm are evaluated. The simulation result shows the proposed system outperforms other algorithm both in cost and performance.