Evolving reversible circuits for the even-parity problem
This work addresses the challenge of low-power reversible computing for digital circuit design, but it appears incremental as it applies an existing MEP method to a specific problem.
The paper tackled the problem of designing reversible digital circuits for the even-parity problem using a Multi Expression Programming (MEP) algorithm, achieving the ability to design circuits for up to the even-8-parity problem.
Reversible computing basically means computation with less or not at all electrical power. Since the standard binary gates are not usually reversible we use the Fredkin gate in order to achieve reversibility. An algorithm for designing reversible digital circuits is described in this paper. The algorithm is based on Multi Expression Programming (MEP), a Genetic Programming variant with a linear representation of individuals. The case of digital circuits for the even-parity problem is investigated. Numerical experiments show that the MEP-based algorithm is able to easily design reversible digital circuits for up to the even-8-parity problem.