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A projection-based decomposition for the scalability of evolvable hardware

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Abstract

Scalability is a main and urgent problem in evolvable hardware (EHW) field. For the design of large circuits, an EHW method with a decomposition strategy is able to successfully find a solution, but requires a large complexity and evolution time. This study aims to optimize the decomposition on large-scale circuits so that it provides a solution for the EHW method to scalability and improves the efficiency. This paper proposes a projection-based decomposition (PD), together with Cartesian genetic programming (CGP) as an EHW system namely PD-CGP, to design relatively large circuits. PD gradually decomposes a Boolean function by adaptively projecting it onto the property of variables, which makes the complexity and number of sub-logic blocks minimized. CGP employs an evolutionary strategy to search for the simple and compact solutions of these sub-blocks. The benchmark circuits from the MCNC library, \(n\)-parity circuits, and arithmetic circuits are used in the experiment to prove the ability of PD-CGP in solving scalability and efficiency. The results illustrate that PD-CGP is superior to 3SD-ES in evolving large circuits in terms of complexity reduction. PD-CGP also outperforms GDD+GA in evolving relatively large arithmetic circuits. Additionally, PD-CGP successfully evolves larger \(n\)-even-parity and arithmetic circuits, which have not done by other approaches.

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Acknowledgments

This research is supported by the National Science Fund of China(Grant No. 61272105), the Science Fund of the JiangSu Higher Education of China (Grant No. 13KJB520023), and the Youth Teacher Science Fund of Soochow University (Grant No. SD2013A16).

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Authors and Affiliations

  1. School of Urban Rail Transportation, Soochow University, Suzhou, 215137, China

    Yanyun Tao & Lijun Zhang

  2. The First Affiliated Hospital of Soochow University, Suzhou, 215006, China

    Yuzhen Zhang

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  1. Yanyun Tao
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  2. Lijun Zhang
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  3. Yuzhen Zhang
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Correspondence to Yuzhen Zhang.

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Communicated by R. Cerulli.

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Tao, Y., Zhang, L. & Zhang, Y. A projection-based decomposition for the scalability of evolvable hardware. Soft Comput 20, 2205–2218 (2016). https://doi.org/10.1007/s00500-015-1636-2

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  • DOI: https://doi.org/10.1007/s00500-015-1636-2

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