research-article

SEALS: sensitivity-driven efficient approximate logic synthesis

Authors:

Weikang QianAuthors Info & Claims

DAC '22: Proceedings of the 59th ACM/IEEE Design Automation Conference

Pages 439 - 444

https://doi.org/10.1145/3489517.3530464

Published: 23 August 2022 Publication History

Abstract

Approximate computing is an emerging computing paradigm to design energy-efficient systems. Many greedy approximate logic synthesis (ALS) methods have been proposed to automatically synthesize approximate circuits. They typically need to consider all local approximate changes (LACs) in each iteration of the ALS flow to select the best one, which is time-consuming. In this paper, we propose SEALS, a Sensitivity-driven Efficient ALS method to speed up a greedy ALS flow. SEALS centers around a newly proposed concept called sensitivity, which enables a fast and accurate error estimation method and an efficient method to filter out unpromising LACs. SEALS can handle any statistical error metric. The experimental results show that it outperforms a state-of-the-art ALS method in runtime by 12X to 15X without reducing circuit quality.

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Cited By

Ye YChen TGao YYan HYu BShi L(2024)Timing-Driven Technology Mapping Approximation Based on Reinforcement LearningIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2024.337901643:9(2755-2768)Online publication date: Sep-2024
https://doi.org/10.1109/TCAD.2024.3379016
Zhao BQiu LLao Y(2023)Data-Driven Feature Selection Framework for Approximate Circuit DesignIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2023.326016042:11(3519-3531)Online publication date: 21-Mar-2023
https://dl.acm.org/doi/10.1109/TCAD.2023.3260160
Wang XYan ZMeng CShi YQian W(2023)DASALS: Differentiable Architecture Search-Driven Approximate Logic Synthesis2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD)10.1109/ICCAD57390.2023.10323820(1-9)Online publication date: 28-Oct-2023
https://doi.org/10.1109/ICCAD57390.2023.10323820

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cover image ACM Conferences

DAC '22: Proceedings of the 59th ACM/IEEE Design Automation Conference

July 2022

1462 pages

ISBN:9781450391429

DOI:10.1145/3489517

General Chair:
Rob Oshana
NXP

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New York, NY, United States

Publication History

Published: 23 August 2022

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National Key R&D Program of China

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DAC '22

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SIGDA

DAC '22: 59th ACM/IEEE Design Automation Conference

July 10 - 14, 2022

California, San Francisco

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Overall Acceptance Rate 1,770 of 5,499 submissions, 32%

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62nd ACM/IEEE Design Automation Conference

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Cited By

Ye YChen TGao YYan HYu BShi L(2024)Timing-Driven Technology Mapping Approximation Based on Reinforcement LearningIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2024.337901643:9(2755-2768)Online publication date: Sep-2024
https://doi.org/10.1109/TCAD.2024.3379016
Zhao BQiu LLao Y(2023)Data-Driven Feature Selection Framework for Approximate Circuit DesignIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2023.326016042:11(3519-3531)Online publication date: 21-Mar-2023
https://dl.acm.org/doi/10.1109/TCAD.2023.3260160
Wang XYan ZMeng CShi YQian W(2023)DASALS: Differentiable Architecture Search-Driven Approximate Logic Synthesis2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD)10.1109/ICCAD57390.2023.10323820(1-9)Online publication date: 28-Oct-2023
https://doi.org/10.1109/ICCAD57390.2023.10323820
Wang XTao SZhu JShi YQian W(2023)AccALS: Accelerating Approximate Logic Synthesis by Selection of Multiple Local Approximate Changes2023 60th ACM/IEEE Design Automation Conference (DAC)10.1109/DAC56929.2023.10247856(1-6)Online publication date: 9-Jul-2023
https://doi.org/10.1109/DAC56929.2023.10247856

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