Evolutionary Approach to Approximate Digital Circuits Design

Created by W.Langdon from gp-bibliography.bib Revision:1.4549

  author =       "Zdenek Vasicek and Lukas Sekanina",
  title =        "Evolutionary Approach to Approximate Digital Circuits
  journal =      "IEEE Transactions on Evolutionary Computation",
  year =         "2015",
  volume =       "19",
  number =       "3",
  pages =        "432--444",
  month =        jun,
  keywords =     "genetic algorithms, genetic programming, Cartesian
                 Genetic Programming, Approximate Computing, Digital
                 circuits, Population Seeding",
  ISSN =         "1089-778X",
  DOI =          "doi:10.1109/TEVC.2014.2336175",
  size =         "13 pages",
  abstract =     "In approximate computing, the requirement of perfect
                 functional behaved can be relaxed because some
                 applications are inherently error resilient.
                 Approximate circuits, which fall into the approximate
                 computing paradigm, are designed in such a way that
                 they do not fully implement the logic behavior given by
                 the specification and hence their accuracy can be
                 exchanged for lower area, delay or power consumption.
                 In order to automate the design process, we propose to
                 evolve approximate digital circuits which show a
                 minimal error for a supplied amount of resources. The
                 design process which is based on Cartesian Genetic
                 Programming (CGP) can be repeated many times in order
                 to obtain various tradeoffs between the accuracy and
                 area. A heuristic seeding mechanism is introduced to
                 CGP which allows for improving not only the quality of
                 evolved circuits, but also reducing the time of
                 evolution. The efficiency of the proposed method is
                 evaluated for the gate as well as the functional level
                 evolution. In particular, approximate multipliers and
                 median circuits which show very good parameters in
                 comparison with other available implementations were
                 constructed by means of the proposed method.",
  notes =        "also known as \cite{6848841}",

Genetic Programming entries for Zdenek Vasicek Lukas Sekanina