Faculty of Information Technology, BUT

Publication Details

Evolutionary Design of Large Approximate Adders Optimized for Various Error Criteria

MRÁZEK Vojtěch and VAŠÍČEK Zdeněk. Evolutionary Design of Large Approximate Adders Optimized for Various Error Criteria. In: Proceedings of the Genetic and Evolutionary Computation Conference Companion (GECCO '18). Kyoto: Association for Computing Machinery, 2018, pp. 294-295. ISBN 978-1-4503-5764-7.
Czech title
Evoluční návrh velkých aproximačních sčítaček optimalizovaných pro různé chyby
Type
conference paper
Language
english
Authors
Keywords
Approximate computing, genetic algorithm, equivalence checking
Abstract
As a promising approach to the design of energy efficient circuits, approximate circuits and approximate circuit design methodologies have attracted a significant attention of researchers as well as industry. Compared to the traditional design methods, it has been demonstrated that evolutionary approaches are able to discover approximate circuits exhibiting a good trade-off between the energy consumption and circuit quality. In this work, evolutionary design of large approximate adders is addressed. In order to improve scalability, the quality of the candidate solutions is analysed using a formal approach based on Binary Decision Diagrams. Compared to the common approach based on a parallel circuit simulator, the proposed method is able to evaluate 2-3 orders of magnitude more generations.
Published
2018
Pages
294-295
Proceedings
Proceedings of the Genetic and Evolutionary Computation Conference Companion (GECCO '18)
Conference
Genetic and Evolutionary Computations Conference 2018, Kyoto, JP
ISBN
978-1-4503-5764-7
Publisher
Association for Computing Machinery
Place
Kyoto, JP
DOI
BibTeX
@INPROCEEDINGS{FITPUB11637,
   author = "Vojt\v{e}ch Mr\'{a}zek and Zden\v{e}k Va\v{s}\'{i}\v{c}ek",
   title = "Evolutionary Design of Large Approximate Adders Optimized for Various Error Criteria",
   pages = "294--295",
   booktitle = "Proceedings of the Genetic and Evolutionary Computation Conference Companion (GECCO '18)",
   year = 2018,
   location = "Kyoto, JP",
   publisher = "Association for Computing Machinery",
   ISBN = "978-1-4503-5764-7",
   doi = "10.1145/3205651.3205678",
   language = "english",
   url = "https://www.fit.vut.cz/research/publication/11637"
}
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