Cartesian Genetic Programming as Local Optimizer of Logic Networks

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F14%3APU111924" target="_blank" >RIV/00216305:26230/14:PU111924 - isvavai.cz</a>

Výsledek na webu

<a href="http://www.fit.vutbr.cz/research/pubs/all.php?id=10504" target="_blank" >http://www.fit.vutbr.cz/research/pubs/all.php?id=10504</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/CEC.2014.6900326" target="_blank" >10.1109/CEC.2014.6900326</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Cartesian Genetic Programming as Local Optimizer of Logic Networks

Popis výsledku v původním jazyce

Logic synthesis and optimization methods work either globally on the whole logic network or locally on preselected subnetworks. Evolutionary design methods have already been applied to evolve and optimize logic circuits at the global level. In this paper, we propose a new method based on Cartesian genetic programming (CGP) as a local area optimizer in combinational logic networks. First, a subcircuit is extracted from a complex circuit, then the subcircuit is optimized by CGP and finally the optimized subcircuit replaces the original one. The procedure is repeated until a termination criterion is satisfied. We present a performance comparison of local and global evolutionary optimization methods with a conventional approach based on ABC and analyze these methods using differently pre-optimized benchmark circuits. If a sufficient time is available, the proposed locally optimizing CGP gives better results than other locally operating methods reported in the literature; however, its performance is significantly worse than the evolutionary global optimization.

Název v anglickém jazyce

Cartesian Genetic Programming as Local Optimizer of Logic Networks

Popis výsledku anglicky

Logic synthesis and optimization methods work either globally on the whole logic network or locally on preselected subnetworks. Evolutionary design methods have already been applied to evolve and optimize logic circuits at the global level. In this paper, we propose a new method based on Cartesian genetic programming (CGP) as a local area optimizer in combinational logic networks. First, a subcircuit is extracted from a complex circuit, then the subcircuit is optimized by CGP and finally the optimized subcircuit replaces the original one. The procedure is repeated until a termination criterion is satisfied. We present a performance comparison of local and global evolutionary optimization methods with a conventional approach based on ABC and analyze these methods using differently pre-optimized benchmark circuits. If a sufficient time is available, the proposed locally optimizing CGP gives better results than other locally operating methods reported in the literature; however, its performance is significantly worse than the evolutionary global optimization.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20206 - Computer hardware and architecture

Projekt

<a href="/cs/project/GA14-04197S" target="_blank" >GA14-04197S: Pokročilé metody evolučního návrhu složitých číslicových obvodů</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2014

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

2014 IEEE Congress on Evolutionary Computation

ISBN

978-1-4799-1488-3

ISSN

—

e-ISSN

—

Počet stran výsledku

8

Strana od-do

2901-2908

Název nakladatele

IEEE Computational Intelligence Society

Místo vydání

Beijing

Místo konání akce

Beijing

Datum konání akce

6. 7. 2014

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000356684604023