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BLASYS: approximate logic synthesis using boolean matrix factorization

Published:24 June 2018Publication History

ABSTRACT

Approximate computing is an emerging paradigm where design accuracy can be traded off for benefits in design metrics such as design area, power consumption or circuit complexity. In this work, we present a novel paradigm to synthesize approximate circuits using Boolean matrix factorization (BMF). In our methodology the truth table of a sub-circuit of the design is approximated using BMF to a controllable approximation degree, and the results of the factorization are used to synthesize a less complex subcircuit. To scale our technique to large circuits, we devise a circuit decomposition method and a subcircuit design-space exploration technique to identify the best order for subcircuit approximations. Our method leads to a smooth trade-off between accuracy and full circuit complexity as measured by design area and power consumption. Using an industrial strength design flow, we extensively evaluate our methodology on a number of testcases, where we demonstrate that the proposed methodology can achieve up to 63% in power savings, while introducing an average relative error of 5%. We also compare our work to previous works in Boolean circuit synthesis and demonstrate significant improvements in design metrics for same accuracy targets.

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  • Published in

    cover image ACM Conferences
    DAC '18: Proceedings of the 55th Annual Design Automation Conference
    June 2018
    1089 pages
    ISBN:9781450357005
    DOI:10.1145/3195970

    Copyright © 2018 ACM

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    New York, NY, United States

    Publication History

    • Published: 24 June 2018

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