SAS - A Framework for Symmetry-based Approximate Synthesis

Jungnitz N, Keszöcze O (2024)

Publication Language: English

Publication Type: Conference contribution, Original article

Publication year: 2024

Event location: San Francisco US

DOI: 10.1145/3649329.3658495


Approximate Computing is a design paradigm that trades off computational accuracy for gains in non-functional aspects such as reduced area, increased computation speed, or power reduction. The latter is of special interest in the field of Internet of Things. In this paper we present SAS, a framework for symmetry-based approximate logic synthesis. Given a Boolean multi-output function, SAS approximates it by (partially) replacing its output functions by symmetric functions with minimal Hamming distance. The framework is capable of restricting the introduced error with respect to a parameterized error metric that covers many real-word use-cases.

Experimental results on common benchmark sets as well as large bit width arithmetic Boolean functions confirm the effectiveness of the proposed framework. SAS is capable of synthesizing Boolean functions with size reductions of up to ≈ 45% while, at the same time, respecting the specified threshold on the error metric. The framework is publicly available as open-source software on GitHub.

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How to cite


Jungnitz, N., & Keszöcze, O. (2024). SAS - A Framework for Symmetry-based Approximate Synthesis. In Proceedings of the Design Automation Conference. San Francisco, US.


Jungnitz, Niklas, and Oliver Keszöcze. "SAS - A Framework for Symmetry-based Approximate Synthesis." Proceedings of the Design Automation Conference, San Francisco 2024.

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