Detail publikace

Parallel Optimization of Transistor Level Circuits using Cartesian Genetic Programming

MRÁZEK, V. VAŠÍČEK, Z.

Originální název

Parallel Optimization of Transistor Level Circuits using Cartesian Genetic Programming

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

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.

Klíčová slova

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

Autoři

MRÁZEK, V.; VAŠÍČEK, Z.

Vydáno

4. 7. 2017

Nakladatel

Association for Computing Machinery

Místo

Berlin

ISBN

978-1-4503-4939-0

Kniha

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

Strany od

1849

Strany do

1856

Strany počet

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/"
}