Detail publikace

Scalable Construction of Approximate Multipliers With Formally Guaranteed Worst Case Error

MRÁZEK, V. VAŠÍČEK, Z. SEKANINA, L. JIANG, H. HAN, J.

Originální název

Scalable Construction of Approximate Multipliers With Formally Guaranteed Worst Case Error

Typ

článek v časopise ve Web of Science, Jimp

Jazyk

angličtina

Originální abstrakt

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.

Klíčová slova

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

Autoři

MRÁZEK, V.; VAŠÍČEK, Z.; SEKANINA, L.; JIANG, H.; HAN, J.

Vydáno

1. 11. 2018

ISSN

1063-8210

Periodikum

IEEE Trans. on VLSI Systems.

Ročník

26

Číslo

11

Stát

Spojené státy americké

Strany od

2572

Strany do

2576

Strany počet

5

URL

https://www.fit.vut.cz/research/publication/11678/

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/"
}