Publication Details

autoAx: An Automatic Design Space Exploration and Circuit Building Methodology utilizing Libraries of Approximate Components

MRÁZEK Vojtěch, HANIF Muhammad A., VAŠÍČEK Zdeněk, SEKANINA Lukáš and SHAFIQUE Muhammad. autoAx: An Automatic Design Space Exploration and Circuit Building Methodology utilizing Libraries of Approximate Components. In: The 56th Annual Design Automation Conference 2019 (DAC '19). Las Vegas: Association for Computing Machinery, 2019, pp. 1-6. ISBN 978-1-4503-6725-7. Available from: https://arxiv.org/abs/1902.10807
Czech title
autoAx: Automatická metodologie pro vytváření obvodů s využitím knihoven aproximačních komponent
Type
conference paper
Language
english
Authors
Mrázek Vojtěch, Ing., Ph.D. (DCSY FIT BUT)
Hanif Muhammad A. (TU-Wien)
Vašíček Zdeněk, doc. Ing., Ph.D. (DCSY FIT BUT)
Sekanina Lukáš, prof. Ing., Ph.D. (DCSY FIT BUT)
Shafique Muhammad (TU-Wien)
URL
Keywords
approximate computing, design space exploration, approximate components, machine learning
Abstract
Approximate computing is an emerging paradigm for developing highly energy-efficient computing systems such as various accelerators. In the literature, many libraries of elementary approximate circuits have already been proposed to simplify the design process of approximate accelerators. Because these libraries contain from tens to thousands of approximate implementations for a single arithmetic operation it is intractable to find an optimal combination of approximate circuits in the library even for an application consisting of a few operations. An open problem is "how to effectively combine circuits from these libraries to construct complex approximate accelerators''. This paper proposes a novel methodology for searching, selecting and combining the most suitable approximate circuits from a set of available libraries to generate an approximate accelerator for a given application. To enable fast design space generation and exploration, the methodology utilizes machine learning techniques to create  computational models estimating the overall quality of processing and hardware cost without performing full synthesis at the accelerator  level. Using the methodology, we construct hundreds of approximate accelerators (for a Sobel edge detector) showing different but relevant tradeoffs between the quality of processing and hardware cost and identify a corresponding Pareto-frontier. Furthermore, when searching for  approximate implementations of a generic Gaussian filter consisting of 17 arithmetic operations, the proposed approach allows us to identify approximately 10^3 highly relevant implementations from 10^23 possible solutions in a few hours, while the exhaustive search would take four months on a high-end processor.
Published
2019
Pages
1-6
Proceedings
The 56th Annual Design Automation Conference 2019 (DAC '19)
Conference
Design Automation Conference, Las Vegas, US
ISBN
978-1-4503-6725-7
Publisher
Association for Computing Machinery
Place
Las Vegas, US
DOI
BibTeX
@INPROCEEDINGS{FITPUB11862,
   author = "Vojt\v{e}ch Mr\'{a}zek and A. Muhammad Hanif and Zden\v{e}k Va\v{s}\'{i}\v{c}ek and Luk\'{a}\v{s} Sekanina and Muhammad Shafique",
   title = "autoAx: An Automatic Design Space Exploration and Circuit Building Methodology utilizing Libraries of Approximate Components",
   pages = "1--6",
   booktitle = "The 56th Annual Design Automation Conference 2019 (DAC '19)",
   year = 2019,
   location = "Las Vegas, US",
   publisher = "Association for Computing Machinery",
   ISBN = "978-1-4503-6725-7",
   doi = "10.1145/3316781.3317781",
   language = "english",
   url = "https://www.fit.vut.cz/research/publication/11862"
}
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