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Boolean Decomposition for AIG Optimization

Published: 10 May 2017 Publication History

Abstract

Restructuring techniques for And-Inverter Graphs (AIG), such as rewriting and refactoring, are powerful, scalable and fast, achieving highly optimized AIGs after few iterations. However, these techniques are biased by the original AIG structure and limited by single output optimizations. This paper investigates AIG optimization for area, exploring how far Boolean methods can reduce AIG nodes through local optimization.Boolean division is applied for multi-output functions using two-literal divisors and Boolean decomposition is introduced as a method for AIG optimization. Multi-output blocks are extracted from the AIG and optimized, achieving a further AIG node reduction of 7.76% on average for ITC99 and MCNC benchmarks.

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Cited By

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  • (2021)Resubstitution method for big size Boolean logic design targeting look‐up‐table implementationInternational Journal of Circuit Theory and Applications10.1002/cta.308649:8(2411-2424)Online publication date: 15-Jun-2021
  • (2019)Distributed Indication in LUT-Based Asynchronous LogicIFAC-PapersOnLine10.1016/j.ifacol.2019.12.64852:27(257-264)Online publication date: 2019

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cover image ACM Conferences
GLSVLSI '17: Proceedings of the Great Lakes Symposium on VLSI 2017
May 2017
516 pages
ISBN:9781450349727
DOI:10.1145/3060403
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 10 May 2017

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Author Tags

  1. aig
  2. boolean decomposition
  3. kl-cuts
  4. local optimization

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  • Research-article

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GLSVLSI '17
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GLSVLSI '17: Great Lakes Symposium on VLSI 2017
May 10 - 12, 2017
Alberta, Banff, Canada

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GLSVLSI '17 Paper Acceptance Rate 48 of 197 submissions, 24%;
Overall Acceptance Rate 312 of 1,156 submissions, 27%

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Cited By

View all
  • (2021)Resubstitution method for big size Boolean logic design targeting look‐up‐table implementationInternational Journal of Circuit Theory and Applications10.1002/cta.308649:8(2411-2424)Online publication date: 15-Jun-2021
  • (2019)Distributed Indication in LUT-Based Asynchronous LogicIFAC-PapersOnLine10.1016/j.ifacol.2019.12.64852:27(257-264)Online publication date: 2019

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