Publication detail

Parallel Optimization of Transistor Level Circuits using Cartesian Genetic Programming

MRÁZEK, V. VAŠÍČEK, Z.

Original Title

Parallel Optimization of Transistor Level Circuits using Cartesian Genetic Programming

Type

conference paper

Language

English

Original 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.

Keywords

Evolutionary optimization, transistor-level, parallel systems, digital circuits 

Authors

MRÁZEK, V.; VAŠÍČEK, Z.

Released

4. 7. 2017

Publisher

Association for Computing Machinery

Location

Berlin

ISBN

978-1-4503-4939-0

Book

GECCO Companion '17 Proceedings of the Companion Publication of the 2017 on Genetic and Evolutionary Computation Conference

Pages from

1849

Pages to

1856

Pages count

8

URL

https://www.fit.vut.cz/research/publication/11377/

BibTex

@inproceedings{BUT144422,
  author="Vojtěch {Mrázek} and Zdeněk {Vašíček}",
  title="Parallel Optimization of Transistor Level Circuits using Cartesian Genetic Programming",
  booktitle="GECCO Companion '17 Proceedings of the Companion Publication of the 2017 on Genetic and Evolutionary Computation Conference",
  year="2017",
  pages="1849--1856",
  publisher="Association for Computing Machinery",
  address="Berlin",
  doi="10.1145/3067695.3084212",
  isbn="978-1-4503-4939-0",
  url="https://www.fit.vut.cz/research/publication/11377/"
}