Publication Details
Impact of subcircuit selection on the efficiency of CGP-based optimization of gate-level circuits
Cartesian Genetic Programming, Logic Synthesis, CombinationalCircuits
Various EA-based methods have been applied to design and optimize logic circuits
since the early nineties. The unconventional methods, however, typically suffer
from various scalability issues preventing them to be adopted in practice. Recent
improvement in the fitness computation procedure connected with the introduction
of formal methods in the fitness evaluation such as SAT solvers or BDDs enabled
pushing of the limits forward and approaching the complexity of industrial
problems. It was demonstrated that EAs can be applied to optimize gate-level
circuits consisting of thousands of gates without introducing any decomposition
technique. Despite that, the efficiency decreases with increasing the circuit
complexity. This problem can be managed by adopting the concept of the so-called
iterative resynthesis based on the extraction of smaller sub-circuits from
a complex circuit, their local optimization followed by the implantation back to
the original circuit. Recently, a method based on the computation of so-called
cuts was proposed. In this paper, we propose an alternative approach which is
able to select more complex sub-graphs consisting of more nodes and more inputs.
Compared to the previous method, the proposed approach allows to improve the
efficiency of the optimization. More than 9% and 20% reduction was observed on
the highly optimized logic and arithmetic circuits, respectively.
@inproceedings{BUT158075,
author="Jitka {Kocnová} and Zdeněk {Vašíček}",
title="Impact of subcircuit selection on the efficiency of CGP-based optimization of gate-level circuits",
booktitle="GECCO '19 Proceedings of the Genetic and Evolutionary Computation Conference Companion",
year="2019",
pages="377--378",
publisher="Association for Computing Machinery",
address="New York",
doi="10.1145/3319619.3321926",
isbn="978-1-4503-6748-6",
url="https://www.fit.vut.cz/research/publication/11921/"
}