Detail publikace

Multiobjective evolution of approximate multiple constant multipliers

Originální název

Multiobjective evolution of approximate multiple constant multipliers

Anglický název

Multiobjective evolution of approximate multiple constant multipliers

Jazyk

en

Originální abstrakt

Multiple constant multiplier (MCM) is a digital circuit which multiplies its single input by N constants. As MCMs are composed of adders and shifters, their implementation cost is relatively low. In this paper, we propose a method for design of approximate multiple constant multipliers where the requirement on functional equivalence between the specification and implementation is relaxed in order to further reduce the area on a chip or minimize delay. The proposed method is based on multiobjective Cartesian Genetic Programming. It provides many trade-off solutions among accuracy, area and delay. 

Anglický abstrakt

Multiple constant multiplier (MCM) is a digital circuit which multiplies its single input by N constants. As MCMs are composed of adders and shifters, their implementation cost is relatively low. In this paper, we propose a method for design of approximate multiple constant multipliers where the requirement on functional equivalence between the specification and implementation is relaxed in order to further reduce the area on a chip or minimize delay. The proposed method is based on multiobjective Cartesian Genetic Programming. It provides many trade-off solutions among accuracy, area and delay. 

BibTex


@inproceedings{BUT103446,
  author="Jiří {Petrlík} and Lukáš {Sekanina}",
  title="Multiobjective evolution of approximate multiple constant multipliers",
  annote="Multiple constant multiplier (MCM) is a digital circuit which multiplies its
single input by N constants. As MCMs are composed of adders and shifters, their
implementation cost is relatively low. In this paper, we propose a method for
design of approximate multiple constant multipliers where the requirement on
functional equivalence between the specification and implementation is relaxed in
order to further reduce the area on a chip or minimize delay. The proposed method
is based on multiobjective Cartesian Genetic Programming. It provides many
trade-off solutions among accuracy, area and delay. ",
  address="IEEE Computer Society",
  booktitle="IEEE International Symposium on Design and Diagnostics of Electronic Circuits and Systems 2013",
  chapter="103446",
  doi="10.1109/DDECS.2013.6549800",
  edition="NEUVEDEN",
  howpublished="print",
  institution="IEEE Computer Society",
  year="2013",
  month="april",
  pages="116--119",
  publisher="IEEE Computer Society",
  type="conference paper"
}