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Multi-objective Q-bit Coding Genetic Algorithm for Hardware-Software Co-synthesis of Embedded Systems

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Simulated Evolution and Learning (SEAL 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4247))

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Abstract

One of the key tasks in Hardware-Software Co-design is to optimally allocate, assign, and schedule resources to achieve a good balance among performance, cost, power consumption, etc. So it’s a typical multi-objective optimization problem. In this paper, a Multi-objective Q-bit coding genetic algorithm (MoQGA) is proposed to solve HW-SW co-synthesis problem in HW-SW co-design of embedded systems. The algorithm utilizes the Q-bit probability representation to model the promising area of solution space, uses multiple Q-bit models to perform search in a parallel manner, uses modified Q-bit updating strategy and quantum crossover operator to implement the efficient global search, uses an archive to preserve and select pareto optima, uses Timed Task Graph to describe the system functions, introduces multi-PRI scheduling strategy and PE slot-filling strategy to improve the time performance of system. Experimental results show that the proposed algorithm can solve the multi-objective co-synthesis problem effectively and efficiently.

Supported by the National Natural Science Foundation of China (No.60401015, No. 60572012), and the Nature Science Foundation of Anhui province (No. 050420201).

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Wen-long, W., Bin, L., Yi, Z., Zhen-quan, Z. (2006). Multi-objective Q-bit Coding Genetic Algorithm for Hardware-Software Co-synthesis of Embedded Systems. In: Wang, TD., et al. Simulated Evolution and Learning. SEAL 2006. Lecture Notes in Computer Science, vol 4247. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11903697_109

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  • DOI: https://doi.org/10.1007/11903697_109

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-47331-2

  • Online ISBN: 978-3-540-47332-9

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