Abstract
The current trend in Embedded Systems (ES) design is moving towards the integration of increasingly complex applications on a single chip. An Embedded System has to satisfy both performance constraints and cost limits; it is composed of both dedicated elements, i.e. hardware (HW) components, and programmable units, i.e. software (SW) components, Hardware (HW) and software (SW) components have to interact with each other for accomplishing a specific task. One of the aims of codesign is to support the exploration of the most significant architectural alternatives in terms of decomposition between hardware (HW) and software (SW) components. In this paper, we propose a novel approach to support the exploration of feasible hardware-software (HW-SW) configurations. The approach exploits the learning classifier system XCS both to identify existing relationships among the system components and to support HW-SW partitioning decisions. We validate the approach by applying it to the design of a Digital Sound Spatializer.
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
Ascia, G., Catania, V., Palesi, M.: Parameterized system design based on genetic algorithms. In: Proceedings of the Ninth International Workshop on Hardware/ Software Codesign (April 2001)
Eles, P., Kuchcinski, K., Peng, Z., Doboli, A.: System level hardware/software partitioning based on simulated annealing and tabu search. Journal on Design Automation for Embedded Systems 2, 5–32 (1997)
Ferrandi, F., Lanzi, P.L., Sciuto, D.: Mining Interesting Patterns from Hardware-Software Codesign Data with the Learning Classifier System XCS. In: Proceedings of the 2003 Congress on Evolutionary Computation (CEC 2003), Canberra, Australia, December 9-12, pp. 1486–1492. IEEE, Los Alamitos (2003)
Gupta, R.K., De Micheli, G.: Hardware-software cosynthesis for digital systems. Design & Test of Computers, IEEE 10, 29–41 (1993)
Henkel, J., Ernst, R.: An approach to automated hardware/software partitioning using a flexible granularity that is driven by high-level estimation techniques. IEEE Transactions on Very Large Scale Integration (VLSI) Systems 9, 273–289 (2001)
De Micheli, G.: Synthesis and Optimization of Digital Circuits. McGraw-Hill, New York (1994)
Palesi, M., Givargis, T.: Multi-objective design space exploration using genetic algorithms. In: Proceedings of the Tenth International Workshop on Hardware/Software Codesign, May 2002, pp. 67–72 (2002)
Quan, G., Hu, X., Greenwood, G.: Preference-driven hierarchical hardware/ software partitioning. In: International Conference on Computer Design (ICCD 1999), pp. 652–657 (1999)
Sciuto, D., Ferrandi, F., Lanzi, P.L., Tanelli, M.: Systemlevel metrics for hardware/software architectural mapping. In: Proceedings of the 2nd IEEE International Workshop on Electronics Design, Test and Applications (DELTA 2004), Burswood Resort, Perth, Australia (January 2004)
Vahid, F., Gajski, D.D.: Closeness metrics for system-level functional partitioning. In: Proceedings EURO-DAC 1995 Design Automation Conference with EUROVHDL, September 1995, pp. 328–333 (1995)
Wilson, S.W.: Classifier Fitness Based on Accuracy. Evolutionary Computation 3(2), 149–175 (1995), http://prediction-dynamics.com/
Wilson, S.W.: Function approximation with a classifier system. In: Spector, L., Goodman, E.D., Wu, A., Langdon, W.B., Voigt, H.-M., Gen, M., Sen, S., Dorigo, M., Pezeshk, S., Garzon, M.H., Burke, E. (eds.) Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2001), San Francisco, California, USA, July 7-11, pp. 974–981. Morgan Kaufmann, San Francisco (2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ferrandi, F., Lanzi, P.L., Sciuto, D. (2004). System Level Hardware–Software Design Exploration with XCS. In: Deb, K. (eds) Genetic and Evolutionary Computation – GECCO 2004. GECCO 2004. Lecture Notes in Computer Science, vol 3103. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24855-2_91
Download citation
DOI: https://doi.org/10.1007/978-3-540-24855-2_91
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22343-6
Online ISBN: 978-3-540-24855-2
eBook Packages: Springer Book Archive