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HEADiv: A High-accuracy Energy-efficient Approximate Divider with Error Compensation

Published: 31 May 2023 Publication History

Abstract

The circuit complexity of dividers is more considerable than the basic arithmetic units like adders and multipliers. However, the performance of the divider has a significant impact on the system performance, leading to degradation if not appropriately implemented. As a promising design methodology, approximate computing has demonstrated its effectiveness in reducing power consumption and improving performance with good-enough accuracy. This paper proposes an approximate divider HEADiv based on Taylor expansion with error compensation to reduce hardware consumption. The proposed approximate divider is evaluated and analyzed using error and hardware metrics. Compared to other state-of-the-art approximate divider designs, the proposed approximate divider showed 70% and 45% improvement in accuracy for 8-bit and 16-bit dividers, respectively. Besides, the proposed 16-bit approximate divider reduced the area and power consumption by 9% and 42%, respectively. Finally, the experiments illustrate that the proposed approximate divider can improve the PSNR by up to 55% in image processing applications.

References

[1]
Setareh Behroozi et al. "SAADI: A Scalable Accuracy Approximate Divider for Dynamic Energy-Quality Scaling". In: Proceedings of the 24th Asia and South Pacific Design Automation Conference. ACM, 2019, pp. 481--486.
[2]
Ke Chen et al. "Profile-Based Output Error Compensation for Approximate Arithmetic Circuits". In: IEEE Transactions on Circuits and Systems I: Regular Papers 67.12 (2020), pp. 4707--4718.
[3]
Yue Gao, Weiqiang Liu, and Fabrizio Lombardi. "Design and Implementation of an Approximate Softmax Layer for Deep Neural Networks". In: 2020 IEEE International Symposium on Circuits and Systems (ISCAS). IEEE, 2020, pp. 1--5.
[4]
Xue Geng et al. "Hardware-Aware Softmax Approximation for Deep Neural Networks". In: Computer Vision - ACCV 2018. Ed. by C.V. Jawahar et al. Vol. 11364. Springer International Publishing, 2019, pp. 107--122.
[5]
Honglan Jiang et al. "Approximate Arithmetic Circuits: A Survey, Characterization, and Recent Applications". In: Proceedings of the IEEE 108.12 (2020), pp. 2108--2135.
[6]
Weiqiang Liu, Fabrizio Lombardi, and Michael Shulte. "A Retrospective and Prospective View of Approximate Computing [Point of View}". In: Proceedings of the IEEE 108.3 (2020), pp. 394--399.
[7]
Nangate 45nm Open Cell Library. https://si2.org/open-cell-library/.
[8]
S.F. Obermann and M.J. Flynn. "Division Algorithms and Implementations". In: IEEE Transactions on Computers 46.8 (Aug./1997), pp. 833--854.
[9]
B. Parhami. Computer Arithmetic: Algorithms and Hardware Designs. Computer arithmetic: algorithms and hardware designs, 1999.
[10]
Shaghayegh Vahdat et al. "TruncApp: A Truncation-Based Approximate Divider for Energy Efficient DSP Applications". In: Design, Automation & Test in Europe Conference & Exhibition (DATE), 2017. IEEE, 2017, pp. 1635--1638.
[11]
Zhou Wang et al. "Image Quality Assessment: From Error Visibility to Structural Similarity". In: IEEE Transactions on Image Processing 13.4 (2004), pp. 600--612.
[12]
Reza Zendegani et al. "SEERAD: A High Speed yet Energy-Efficient Rounding-based Approximate Divider". In: Proceedings of the 2016 Design, Automation & Test in Europe Conference & Exhibition (DATE). Research Publishing Services, 2016, pp. 1481--1484.

Cited By

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  • (2024)Approximate Computing: Concepts, Architectures, Challenges, Applications, and Future DirectionsIEEE Access10.1109/ACCESS.2024.346737512(146022-146088)Online publication date: 2024
  • (2023)Approximate Computing: Hardware and Software Techniques, Tools and Their ApplicationsJournal of Circuits, Systems and Computers10.1142/S021812662430001033:04Online publication date: 20-Sep-2023

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  1. HEADiv: A High-accuracy Energy-efficient Approximate Divider with Error Compensation

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    cover image ACM Conferences
    NANOARCH '22: Proceedings of the 17th ACM International Symposium on Nanoscale Architectures
    December 2022
    140 pages
    ISBN:9781450399388
    DOI:10.1145/3565478
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Published: 31 May 2023

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    Author Tags

    1. approximate computing
    2. divider
    3. error compensation
    4. image processing

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    NANOARCH '22 Paper Acceptance Rate 25 of 31 submissions, 81%;
    Overall Acceptance Rate 55 of 87 submissions, 63%

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    • (2024)Approximate Computing: Concepts, Architectures, Challenges, Applications, and Future DirectionsIEEE Access10.1109/ACCESS.2024.346737512(146022-146088)Online publication date: 2024
    • (2023)Approximate Computing: Hardware and Software Techniques, Tools and Their ApplicationsJournal of Circuits, Systems and Computers10.1142/S021812662430001033:04Online publication date: 20-Sep-2023

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