Publication Details

Scalable Construction of Approximate Multipliers With Formally Guaranteed Worst Case Error

MRÁZEK, V.; VAŠÍČEK, Z.; SEKANINA, L.; JIANG, H.; HAN, J. Scalable Construction of Approximate Multipliers With Formally Guaranteed Worst Case Error. IEEE Trans. on VLSI Systems., 2018, vol. 26, no. 11, p. 2572-2576. ISSN: 1063-8210.
Czech title
Škálovatelná konstrukce aproximativních násobiček s formálně garantovanou maximální chybou
Type
journal article
Language
English
Authors
Keywords

Approximate computing circuits and systems, circuit synthesis, circuits,
computers and information processing

Abstract

Approximate computing exploits the fact that many applications are inherently
error resilient. In order to reduce power consumption, approximate circuits such
as multipliers have been employed in these applications. However, most current
approximate multipliers are based on ad-hoc circuit structures and, for automated
circuit approximation methods, large efficient designs are difficult to find due
to the increased search space. Moreover, existing design methods do not typically
provide sufficient formal guarantees in terms of error if large approximate
multipliers are constructed. To address these challenges, this brief introduces
a general and efficient method for constructing large high-quality approximate
multipliers with respect to the objectives formulated in terms of the power-delay
product and a provable error bound. This is demonstrated by means of
a comparative evaluation of approximate 16-bit multipliers constructed by the
proposed method and other methods in the literature.

Published
2018
Pages
2572–2576
Journal
IEEE Trans. on VLSI Systems., vol. 26, no. 11, ISSN 1063-8210
DOI
UT WoS
000448911900033
EID Scopus
BibTeX
@article{BUT155014,
  author="MRÁZEK, V. and VAŠÍČEK, Z. and SEKANINA, L. and JIANG, H. and HAN, J.",
  title="Scalable Construction of Approximate Multipliers With Formally Guaranteed Worst Case Error",
  journal="IEEE Trans. on VLSI Systems.",
  year="2018",
  volume="26",
  number="11",
  pages="2572--2576",
  doi="10.1109/TVLSI.2018.2856362",
  issn="1063-8210",
  url="https://www.fit.vut.cz/research/publication/11678/"
}
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