Abstract
This paper proposes a multiobjective Cartesian Genetic Programming with an adaptive population size to design approximate digital circuits via evolutionary algorithms, analyzing the trade-off between the most often used objectives: error, area, power dissipation, and delay. Combinational digital circuits such as adders, multipliers, and arithmetic logic units (ALUs) with up to 16 inputs and 370 logic gates are considered in the computational experiments. The proposed method was able to produce approximate circuits with good operational characteristics when compared with other methods from the literature.
Keywords
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsNotes
- 1.
The symbol “\(\setminus \)” represents the operator of set difference.
- 2.
- 3.
- 4.
The source-code of CGPMO+APS is available at https://github.com/ciml.
References
Aggarwal, S., Meher, P.K., Khare, K.: Concept, design, and implementation of reconfigurable cordic. IEEE Trans. Large Scale Integr. (VLSI) Syst. 24(4), 1588–1592 (2016)
Chandrakasan, A.P., Brodersen, R.W.: Minimizing power consumption in digital CMOS circuits. Proc. IEEE 83(4), 498–523 (1995)
Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.: A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans. Evol. Comput. 6(2), 182–197 (2002)
Hrbacek, R., Mrazek, V., Vasicek, Z.: Automatic design of approximate circuits by means of multi-objective evolutionary algorithms. In: International Conference on Design and Technology of Integrated Systems in Nanoscale Era (DTIS), pp. 1–6 (2016)
Julio, R.O., Soares, L.B., Costa, E.A.C., Bampi, S.: Energy-efficient gaussian filter for image processing using approximate adder circuits. In: 2015 IEEE International Conference on Electronics, Circuits, and Systems (ICECS), pp. 450–453 (2015)
Kaufmann, P., Knieper, T., Platzner, M.: A novel hybrid evolutionary strategy and its periodization with multi-objective genetic optimizers. In: IEEE Congress on Evolutionary Computation, pp. 1–8 (2010)
Miller, J.F.: Cartesian Genetic Programming. Springer, Berlin (2011). https://doi.org/10.1007/978-3-642-17310-3
Roeva, O., Fidanova, S., Paprzycki, M.: Influence of the population size on the genetic algorithm performance in case of cultivation process modelling. In: Federated Conference on Computer Science and Information Systems, pp. 371–376 (2013)
Stepney, S., Adamatzky, A.: Inspired by Nature. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-67997-6
Vasicek, Z., Sekanina, L.: Evolutionary approach to approximate digital circuits design. IEEE Trans. Evol. Comput. 19(3), 432–444 (2015)
Venkataramani, S., Sabne, A., Kozhikkottu, V., Roy, K., Raghunathan, A.: SALSA: systematic logic synthesis of approximate circuits. In: DAC Design Automation Conference, vol. 2012, p. 796–801 (2012)
Acknowledgments
We thanks the support provided by CNPq (312337/2017-5 and 312682/2018-2), FAPEMIG (APQ-00337-18), PPGCC, and PPGMC.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
1 Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Lima, L.S., Bernardino, H.S., Barbosa, H.J.C. (2019). Designing Combinational Circuits Using a Multi-objective Cartesian Genetic Programming with Adaptive Population Size. In: Nicosia, G., Pardalos, P., Umeton, R., Giuffrida, G., Sciacca, V. (eds) Machine Learning, Optimization, and Data Science. LOD 2019. Lecture Notes in Computer Science(), vol 11943. Springer, Cham. https://doi.org/10.1007/978-3-030-37599-7_49
Download citation
DOI: https://doi.org/10.1007/978-3-030-37599-7_49
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-37598-0
Online ISBN: 978-3-030-37599-7
eBook Packages: Computer ScienceComputer Science (R0)