Abstract
Recent research in the area of evolvable design clearly indicates its advantage in the electronics system domain. This biologically inspired approach for design automation and reconfiguration is required for the hardware that needs online adaptation. The Cartesian Genetic Programming (CGP) represents a circuit genotype in the form of grid of nodes. In satellite for safe mode detection, a threshold comparator circuit is used. The comparator circuit can be evolved using CGP architecture by evolutionary algorithm. An evolutionary algorithm (EA) is designed and applied on the CGP pattern of comparator. The evolved comparator in the cascaded form can be further implemented on embryonic fabric. The embryonic fabric has cellular structure that makes it suitable for self-healing and self-replication. The CGP approach to generate configuration data for embryonic array is better than the LUT based data generation approach. In this paper a 2-bit comparator is evolved using customized evolutionary algorithm. The implementation of cascaded 8-bit threshold comparator on the embryonic array is also demonstrated. This comparator design needs configuration data for 2-bit and the data can be cloned to next cells for scalable design on embryonic fabric.
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References
Tempesti, G., Mange, D., Stauffer, A.: Toward robust integrated circuits: the embryonics approach. Proc. IEEE 88, 516–543 (2000)
Mange, D., Sipper, M., Stauffer, A., Tempesti, G.: Bio-inspired computing architectures: the embryonics approach. In: Proceedings of the Seventh International Workshop on Computer Architecture for Machine Perception (CAMP) (2005)
Miller, J.F., Thomson, P.: Cartesian genetic programming. In: Proceedings of the Third European Conference on Genetic Programming (EuroGP2000), vol. 1802, pp. 121–132 (2000)
Yang, S., Wang, Y.: A new self-repairing digital circuit based on embryonic cellular array. In: IEEE (2006)
Chong, K.H., Aris, I.B., Sinan, M.A., Hamiruce, B.M.: Digital circuit structure design via evolutionary algorithm method. J. Appl. Sci. 7(3), 380–385 (2007)
Prodan, L., Tempesti, G., Mange, D., Stauffer, A.: Biology meets electronics: the path to a bio-inspired FPGA. In: ICES 2000. LNCS, vol. 1801, pp. 187–196 (2000)
Malhotra, G., Nagalakshmi, A.M., Sudhakar, S., Udupa, S.: Switch box configuration for generic embryonic cells routing. In: Proceedings of the World Congress on Engineering and Computer Science (WCECS 2015), pp. 414–417 (2015)
Malhotra, G., Becker, J., Ortmanns, M.: Novel field programmable embryonic cell for adder and multiplier. In: 9th Conference on Ph.D. Research in Microelectronics and Electronics (PRIME-2013), pp. 153–156 (2013)
Zhu, Z., Mulvaney, D., Chouliaras, V.: A novel genetic algorithm designed for hardware implementation. Int. J. Comput. Intell. 3(4), 281–288 (2007)
Zhuo, Q., Qian, Y., Li, Y., Wang, N., Li, T.: Embryonic electronics: state of the art and future perspective. In: The 11th IEEE International Conference on Electronic Measurement and Instruments, ICEMI (2013)
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Malhotra, G., Lekshmi, V., Sudhakar, S., Udupa, S. (2019). Implementation of Threshold Comparator Using Cartesian Genetic Programming on Embryonic Fabric. In: Abraham, A., Gandhi, N., Pant, M. (eds) Innovations in Bio-Inspired Computing and Applications. IBICA 2018. Advances in Intelligent Systems and Computing, vol 939. Springer, Cham. https://doi.org/10.1007/978-3-030-16681-6_10
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DOI: https://doi.org/10.1007/978-3-030-16681-6_10
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