Abstract
In order to solve the hardware/software bi-partitioning problems in embedded system and System-on-a-Chip co-design, we put forward a novel bi-partitioning algorithm, which is based on the dynamic combination of Genetic Algorithm (GA) and Ant System Algorithm (ASA). The basic idea is: 1).Firstly, we use Genetic Algorithm to generate preliminary partitioning results, which are then converted into initial pheromone required by Ant System Algorithm, and finally we use Ant System Algorithm to search for the optimal partitioning scheme; 2).While the Genetic Algorithm is running, we determine the best combination time of GA and ASA dynamically, thus, the Genetic Algorithm avoids too early or too late termination. Experiments show that our algorithm excels GA and ASA in performance; moreover, we discover that the bigger partitioning problems are, the better our algorithm performs.
Supported by National Nature of Science Foundation of China (90207019) and 863 Program (2002AA1Z1480).
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Kastner, R.: Synthesis techniques and optimizations for reconfigurable systems. University of California, Los Angeles (2002)
Gupta, R., Micheli, G.D.: System-level synthesis using re-programmable components. In: Proc. of the Euro. Conf. on Design Automation, pp. 2–7 (1992)
Ernst, R., Henkel, J., Benner, T.: Hardware-software co-synthesis for microcontrollers. IEEE Design and Test of Computers 10, 64–75 (1993)
Vahid, F., Jie, G., Gajski, D.D.: A binary-constraint search algorithm for minimizing hardware during hardware/software partitioning. In: Proc. of the Euro. Conf. on Design Automation, pp. 214–219 (1994)
Niemann, R., Marwedel, P.: Hardware/software partitioning using integer programming. In: Proc. of the Euro. Design and Test Conf. (1996)
Kalavade, A., Lee, E.A.: The extended partitioning problem: hardware/software mapping, scheduling, and implementation-bin selection. Design Automation for Embedded Systems 2, 125–163 (1997)
Saha, D., Mitra, R.S., Basu, A.: Hardware Software Partitioning using Genetic Algorithm. In: Proc. of the 10th Int’l Conf. on VLSI Design, pp. 155–160 (1997)
Wiangtong, T., Cheung, P., Luk, W.: Comparing three heuristic search methods for functional partitioning in hardware-software codesign. Journal of Design Automation for Embedded Systems 6, 425–449 (2002)
Dorigo, M., Maniezzo, V., Colorni, A.: Ant system: optimization by a colony of cooperating agents. IEEE Trans. on Systems, Man and Cybernetics, Part-B 26, 29–41 (1996)
Wang, G., Gong, W.R., Kastner, R.: A new approach for task level computational resource bi-partitioning. In: Proc. of IASTED Int’l Conf. on Parallel and Distributed Computing and Systems (2003)
Holland, J.H.: Adaptation in natural and artificial systems. Michigan University Press (1975)
Pan, Z.J., Kang, L.S., Chen, Y.P.: Evolutionary Computation. Tsinghua University Press, Beijing (1998)
Stutzle, T., Hoos, H.: MAX-MIN ant system. Future Generation Computer System 16, 889–914 (2000)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Xiong, Z., Li, S., Chen, J., Zhang, M. (2005). Use Dynamic Combination of Two Meta-heuristics to Do Bi-partitioning. In: Wu, Z., Chen, C., Guo, M., Bu, J. (eds) Embedded Software and Systems. ICESS 2004. Lecture Notes in Computer Science, vol 3605. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11535409_30
Download citation
DOI: https://doi.org/10.1007/11535409_30
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28128-3
Online ISBN: 978-3-540-31823-1
eBook Packages: Computer ScienceComputer Science (R0)