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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 대한전자공학회 JOURNAL OF SEMICONDUCTOR TECHNOLOGY AND SCIENCE Journal of Semiconductor Technology and Science Vol.24 No.4
- 발행연도
- 2024.8
- 수록면
- 305 - 315 (11page)
- DOI
- 10.5573/JSTS.2024.24.4.305
이용수
초록· 키워드
오류제보하기
This paper introduces a novel and efficient approximate 4-2 compressor and multipliers that significantly improve overall computation accuracy with marginal hardware overhead. The proposed compressor incorporates an error recovery logic to rectify output errors under specific input conditions. As a result, the proposed multipliers, featuring this error recovery compressor, exhibit substantial improvements in normalized mean error distance (NMED) and mean relative error distance (MRED) by up to 89.8% and 97.1%, respectively, compared to existing approximate multipliers considered in this paper. Furthermore, when implemented in a 32-nm CMOS technology, the proposed designs enable noteworthy reductions of up to 25.2%, 22.9%, and 23.4% in area, power, and energy, respectively, in comparison to the alternative designs. The effectiveness of the proposed design is further validated through its application in a digital image processing algorithm.
목차
Abstract
I. INTRODUCTION
II. PROPOSED APPROXIMATE COMPRESSOR AND MULTIPLIER DESIGNS
III. EXPERIMENTAL RESULTS
IV. CASE STUDY: IMAGE PROCESSING
V. CONCLUSIONS
REFERENCES
참고문헌 (30)
참고문헌 신청
J. H. Kim, C. Kim, K. Kim, J. Lee. H.-J. Yoo, and J.-Y. Kim, “An Ultra-Low-Power Mixed-Mode Face Recognition Processor for Always-on User Authentication in Mobile Devices,” IEIE Journal of Semiconductor Technology and Science, Vol. 20, No. 6, pp. 499-509, Dec. 2020.
T. Moreau, A. Sampson, and L. Ceze, “Approximate Computing: Making Mobile Systems More Efficient,” IEEE Pervasive Computing, Vol. 14, No. 2, pp. 9-13, Apr.-Jun. 2015.
H. Seo, H. Seok, J. Lee, Y. Han, and Y. Kim, “Design of an Approximate Adder based on Modified Full Adder and Nonzero Truncation for Machine Learning,” IEIE Journal of Semiconductor Technology and Science, Vol. 23, No. 2, pp. 138-148, Apr. 2023.
S. Kim and Y. Kim, "Novel XNOR-Based Approximate Computing for Energy-Efficient Image Processors," IEIE Journal of Semiconductor Technology and Science, vol. 18, no. 5, pp. 602-608, Oct. 2018.
J. Lee, H. Seo, H. Seok, and Y. Kim, “A Novel Approximate Adder Design using Error Reduced Carry Prediction and Constant Truncation,” IEEE Access, Vol. 9, pp. 119939-119953, Aug. 2021.
T. Moreau, A. Sampson, and L. Ceze, “Approximate Computing: Making Mobile Systems More Efficient,” IEEE Pervasive Computing, Vol. 14, No. 2, pp. 9-13, Apr.-Jun. 2015.
H. Seo, H. Seok, J. Lee, Y. Han, and Y. Kim, “Design of an Approximate Adder based on Modified Full Adder and Nonzero Truncation for Machine Learning,” IEIE Journal of Semiconductor Technology and Science, Vol. 23, No. 2, pp. 138-148, Apr. 2023.
S. Kim and Y. Kim, "Novel XNOR-Based Approximate Computing for Energy-Efficient Image Processors," IEIE Journal of Semiconductor Technology and Science, vol. 18, no. 5, pp. 602-608, Oct. 2018.
J. Lee, H. Seo, H. Seok, and Y. Kim, “A Novel Approximate Adder Design using Error Reduced Carry Prediction and Constant Truncation,” IEEE Access, Vol. 9, pp. 119939-119953, Aug. 2021.
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