AutoAx: An automatic design space exploration and circuit building methodology utilizing libraries of approximate components

Vojtech Mrazek, Muhammad Abdullah Hanif, Zdenek Vasicek, Lukas Sekanina, Muhammad Shafique

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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 103 highly relevant implementations from 1023 possible solutions in a few hours, while the exhaustive search would take four months on a high-end processor.

Original languageEnglish (US)
Title of host publicationProceedings of the 56th Annual Design Automation Conference 2019, DAC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781450367257
DOIs
StatePublished - Jun 2 2019
Event56th Annual Design Automation Conference, DAC 2019 - Las Vegas, United States
Duration: Jun 2 2019Jun 6 2019

Publication series

NameProceedings - Design Automation Conference
ISSN (Print)0738-100X

Conference

Conference56th Annual Design Automation Conference, DAC 2019
CountryUnited States
CityLas Vegas
Period6/2/196/6/19

ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Modeling and Simulation

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