Designing Function Configuration Decoders for the PAnDA architecture using Multi-objective Cartesian Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4333

  author =       "James Alfred Walker and Martin A. Trefzer and 
                 Andy M. Tyrrell",
  title =        "Designing Function Configuration Decoders for the
                 {PAnDA} architecture using Multi-objective Cartesian
                 Genetic Programming",
  booktitle =    "IEEE International Conference on Evolvable Systems,
                 ICES 2013",
  year =         "2013",
  editor_ssci-2013 = "P. N. Suganthan",
  editor =       "Andy M. Tyrrell and Pauline C. Haddow",
  pages =        "96--103",
  address =      "Singapore",
  month =        "16-19 " # apr,
  keywords =     "genetic algorithms, genetic programming, Cartesian
                 Genetic Programming",
  DOI =          "doi:10.1109/ICES.2013.6613288",
  size =         "8 pages",
  abstract =     "The Programmable Analogue and Digital Array (PAnDA) is
                 a novel reconfigurable architecture, which allows
                 variability aware design and rapid prototyping of
                 digital systems. Exploiting the configuration options
                 of the architecture allows the post-fabrication
                 correction and optimisation of circuits directly in
                 hardware using bio-inspired techniques. In order to
                 reduce the overhead of extra configuration memory and
                 area consumption, a portion of the configuration memory
                 required to configure the logic functionality of the
                 Configurable Analogue Blocks (CABs) in the PAnDA
                 architecture is replaced by Function Configuration
                 Decoders (FCDs). In the past, bio-inspired approaches
                 based on Cartesian Genetic Programming have been
                 demonstrated as a suitable method for designing such
                 circuit topologies. As the area of the FCDs is a
                 primary concern, in addition to performance, a form of
                 CGP which uses a multi-objective strategy (MOCGP) is
                 used to evolve FCD designs for the two types of CAB
                 present in the PAnDA architecture. The results show
                 that MOCGP is capable of evolving and optimising FCDs
                 that are optimal for area and performance for both
                 CABs. A PAnDA prototype chip containing FCDs is
                 currently being fabricated. Also, when compared with
                 designs produced by a commercial synthesis tool, the
                 MO-CGP designs are smaller, faster, and more power
  notes =        "ICES 2013
                 also known as \cite{6613288}",

Genetic Programming entries for James Alfred Walker Martin A Trefzer Andrew M Tyrrell