Publication Details
Evolutionary approximation of complex digital circuits
digital circuit, approximate computing, binary decision diagram, evolutionary
design
Circuit approximation has been developed in recent years as a viable method for
constructing energy efficient electronic systems. An open problem is how to
effectively obtain approximate circuits showing good compromises between key
circuit parameters - the error, power consumption, area and delay. The use of
evolutionary algorithms in the task of circuit approximation has led to promising
results; however, only relative simple circuit instances have been
tackled because of the scalability problems of the evolutionary design method. We
propose to replace the most time consuming part of the evolutionary design
algorithm, i.e. the fitness calculation exponentially depending on the number of
circuit inputs, by an equivalence checking algorithm operating over Binary
Decision Diagrams (BDDs). Approximate circuits are evolved using Cartesian
genetic programming which calls a BDD solver to calculate the fitness value of
candidate circuits. The method enables to obtain approximate circuits
consisting of tens of inputs and hundreds of gates and showing desired
trade-off between key circuit parameters.
@inproceedings{BUT119815,
author="Zdeněk {Vašíček} and Lukáš {Sekanina}",
title="Evolutionary approximation of complex digital circuits",
booktitle="Proceedings of the Companion Publication of the 2015 on Genetic and Evolutionary Computation Conference",
year="2015",
pages="1505--1506",
publisher="Association for Computing Machinery",
address="New York",
doi="10.1145/2739482.2764657",
isbn="978-1-4503-3488-4"
}