Presentation
SAS - A Framework for Symmetry-based Approximate Synthesis
DescriptionApproximate 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 approximately 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.
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 approximately 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.
Event Type
Research Manuscript
TimeTuesday, June 255:15pm - 5:30pm PDT
Location3008, 3rd Floor
Design
Design of Cyber-physical Systems and IoT