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IMPACT: imprecise adders for low-power approximate computing

Published: 01 August 2011 Publication History

Abstract

Low-power is an imperative requirement for portable multimedia devices employing various signal processing algorithms and architectures. In most multimedia applications, the final output is interpreted by human senses, which are not perfect. This fact obviates the need to produce exactly correct numerical outputs. Previous research in this context exploits error-resiliency primarily through voltage over-scaling, utilizing algorithmic and architectural techniques to mitigate the resulting errors. In this paper, we propose logic complexity reduction as an alternative approach to take advantage of the relaxation of numerical accuracy. We demonstrate this concept by proposing various imprecise or approximate Full Adder (FA) cells with reduced complexity at the transistor level, and utilize them to design approximate multi-bit adders. In addition to the inherent reduction in switched capacitance, our techniques result in significantly shorter critical paths, enabling voltage scaling. We design architectures for video and image compression algorithms using the proposed approximate arithmetic units, and evaluate them to demonstrate the efficacy of our approach. Post-layout simulations indicate power savings of up to 60% and area savings of up to 37% with an insignificant loss in output quality, when compared to existing implementations.

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  • (2021)A Reconfigurable Multiplier for Signed Multiplications with Asymmetric Bit-WidthsACM Journal on Emerging Technologies in Computing Systems10.1145/344621317:4(1-16)Online publication date: 30-Jun-2021
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    cover image ACM Conferences
    ISLPED '11: Proceedings of the 17th IEEE/ACM international symposium on Low-power electronics and design
    August 2011
    434 pages
    ISBN:9781612846606

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    Published: 01 August 2011

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    Author Tags

    1. approximate computing
    2. low-power
    3. mirror adder

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    Overall Acceptance Rate 325 of 965 submissions, 34%

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    • (2022)Ax-BxP: Approximate Blocked Computation for Precision-reconfigurable Deep Neural Network AccelerationACM Transactions on Design Automation of Electronic Systems10.1145/349273327:3(1-20)Online publication date: 28-Jan-2022
    • (2021)Towards Fine-Grained Online Adaptive Approximation Control for Dense SLAM on Embedded GPUsACM Transactions on Design Automation of Electronic Systems10.1145/348661227:2(1-19)Online publication date: 2-Nov-2021
    • (2021)A Reconfigurable Multiplier for Signed Multiplications with Asymmetric Bit-WidthsACM Journal on Emerging Technologies in Computing Systems10.1145/344621317:4(1-16)Online publication date: 30-Jun-2021
    • (2021)UNOProceedings of the ACM/IEEE International Symposium on Low Power Electronics and Design10.1109/ISLPED52811.2021.9502473(1-6)Online publication date: 26-Jul-2021
    • (2019)HEAPProceedings of the 30th International Workshop on Rapid System Prototyping (RSP'19)10.1145/3339985.3358495(36-42)Online publication date: 17-Oct-2019
    • (2019)XBioSiPProceedings of the 56th Annual Design Automation Conference 201910.1145/3316781.3317933(1-6)Online publication date: 2-Jun-2019
    • (2019)ApproxLPProceedings of the 56th Annual Design Automation Conference 201910.1145/3316781.3317774(1-6)Online publication date: 2-Jun-2019
    • (2019)ApproxSymate: path sensitive program approximation using symbolic executionProceedings of the 20th ACM SIGPLAN/SIGBED International Conference on Languages, Compilers, and Tools for Embedded Systems10.1145/3316482.3326341(148-162)Online publication date: 23-Jun-2019
    • (2019)Approximate loop unrollingProceedings of the 16th ACM International Conference on Computing Frontiers10.1145/3310273.3323841(94-105)Online publication date: 30-Apr-2019
    • (2019)Security Threats in Approximate Computing SystemsProceedings of the 2019 Great Lakes Symposium on VLSI10.1145/3299874.3319453(387-392)Online publication date: 13-May-2019
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