Publication Details
Evolutionary Design of Complex Approximate Combinational Circuits
Approximate circuit, Cartesian genetic programming, Binary decision
diagram, Fitness function
Functional approximation is one of the methods allowing designers to approximate
circuits at the level of logic behavior. By introducing a suitable functional
approximation, power consumption, area or delay of a circuit can be reduced if
some errors are acceptable in a particular application. As the error
quantification is usually based on an arithmetic error metric in existing
approximation methods, these methods are primarily suitable for the approximation
of arithmetic and signal processing circuits. This paper deals with the
approximation of general logic (such as pattern matching circuits and complex
encoders) in which no additional information is usually available to establish
a suitable error metric and hence the error of approximation is expressed in
terms of Hamming distance between the output values produced by a candidate
approximate circuit and the accurate circuit. We propose a circuit approximation
method based on Cartesian genetic programming in which gate-level circuits are
internally represented using directed acyclic graphs. In order to eliminate the
well-known scalability problems of evolutionary circuit design, the error of
approximation is determined by binary decision diagrams. The method is analyzed
in terms of computational time and quality of approximation. It is able to
deliver detailed Pareto fronts showing various compromises between the area,
delay and error. Results are presented for 16 circuits (with 27-50 inputs) that
are too complex to be approximated by means of existing evolutionary circuit
design methods.
@article{BUT130910,
author="Zdeněk {Vašíček} and Lukáš {Sekanina}",
title="Evolutionary Design of Complex Approximate Combinational Circuits",
journal="Genetic Programming and Evolvable Machines",
year="2016",
volume="17",
number="2",
pages="169--192",
doi="10.1007/s10710-015-9257-1",
issn="1389-2576",
url="http://dx.doi.org/10.1007/s10710-015-9257-1"
}