Publication Details
autoAx: An Automatic Design Space Exploration and Circuit Building Methodology utilizing Libraries of Approximate Components
HANIF, M.
Vašíček Zdeněk, doc. Ing., Ph.D. (DCSY)
Sekanina Lukáš, prof. Ing., Ph.D. (DCSY)
Shafique Muhammad
approximate computing, design space exploration, approximate components, machine
learning
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.
@inproceedings{BUT158069,
author="MRÁZEK, V. and HANIF, M. and VAŠÍČEK, Z. and SEKANINA, L. and SHAFIQUE, M.",
title="autoAx: An Automatic Design Space Exploration and Circuit Building Methodology utilizing Libraries of Approximate Components",
booktitle="The 56th Annual Design Automation Conference 2019 (DAC '19)",
year="2019",
pages="1--6",
publisher="Association for Computing Machinery",
address="Las Vegas",
doi="10.1145/3316781.3317781",
isbn="978-1-4503-6725-7",
url="https://arxiv.org/abs/1902.10807"
}