Faculty of Information Technology, BUT

Publication Details

Parallel Optimization of Transistor Level Circuits using Cartesian Genetic Programming

MRÁZEK Vojtěch and VAŠÍČEK Zdeněk. Parallel Optimization of Transistor Level Circuits using Cartesian Genetic Programming. In: GECCO Companion '17 Proceedings of the Companion Publication of the 2017 on Genetic and Evolutionary Computation Conference. Berlin: Association for Computing Machinery, 2017, pp. 1849-1856. ISBN 978-1-4503-4939-0.
Czech title
Paralelní optimalizace obvodů popsaných na úrovni tranzistorů pomocí kartézského genetického programování
Type
conference paper
Language
english
Authors
Keywords
Evolutionary optimization, transistor-level, parallel systems, digital circuits 
Abstract
The aim of the paper is to introduce a new parallel approach to evolutionary optimization of digital circuits described on transistor level. The evolutionary optimization is guided by the fitness function employing a simulator of candidate circuits. A new discrete simulator was introduced to achieve a good trade-off between precision and cost of circuit evaluations. The simulator is based on event-driven simulation. Precise numeric SPICE simulator is regularly called to validate simulation results. To increase the speed of evolution, three parallel approaches were proposed: (i) thread level parallelism, (ii) multiple computing nodes which collectively communicate and distribute the best solution, and (iii) client-server architecture eliminating a limited count of SPICE simulator instances.
Published
2017
Pages
1849-1856
Proceedings
GECCO Companion '17 Proceedings of the Companion Publication of the 2017 on Genetic and Evolutionary Computation Conference
Conference
Genetic and Evolutionary Computations Conference 2017, Berlin, DE
ISBN
978-1-4503-4939-0
Publisher
Association for Computing Machinery
Place
Berlin, DE
DOI
BibTeX
@INPROCEEDINGS{FITPUB11377,
   author = "Vojt\v{e}ch Mr\'{a}zek and Zden\v{e}k Va\v{s}\'{i}\v{c}ek",
   title = "Parallel Optimization of Transistor Level Circuits using Cartesian Genetic Programming",
   pages = "1849--1856",
   booktitle = "GECCO Companion '17 Proceedings of the Companion Publication of the 2017 on Genetic and Evolutionary Computation Conference",
   year = 2017,
   location = "Berlin, DE",
   publisher = "Association for Computing Machinery",
   ISBN = "978-1-4503-4939-0",
   doi = "10.1145/3067695.3084212",
   language = "english",
   url = "https://www.fit.vut.cz/research/publication/11377"
}
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