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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM67675
Volume:
10 |
10 |
Oct 2026
Pages:
1-9
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Department of Electrical and Electronics Engineering,
Guru Jambheshwar University of Science and Technology, Hisar, Haryana, India
Department of Electrical and Electronics Engineering,
Guru Jambheshwar University of Science and Technology, Hisar, Haryana, India
Department of Electrical and Electronics Engineering,
Guru Jambheshwar University of Science and Technology, Hisar, Haryana, India
Department of Electrical and Electronics Engineering,
Guru Jambheshwar University of Science and Technology, Hisar, Haryana, India
Department of Electrical and Electronics Engineering,
Guru Jambheshwar University of Science and Technology, Hisar, Haryana, India
Approximate multiplication is attractive for error-resilient computer-vision datapaths because multiplication dominates many convolution, filtering, gradient, and feature-extraction kernels. This work experimentally compares four unsigned 8-bit multiplier architectures—an exact reference, an ordinary column-truncated multiplier, a fixed-bias truncated multiplier, and a three-boundary-column compensated (BWC-3) multiplier—under a common registered FPGA benchmark. All architectures are evaluated on a Xilinx Zynq-7000 XC7Z020-CLG484-1 device using a 14-point post-route timing sweep from 50 to 200 MHz. The reported implementation data show markedly different timing–area–power trade-offs. The exact design maintains non-negative slack through 180.995 MHz, whereas ordinary truncation and fixed bias close timing through 200 MHz; BWC-3 closes only through 133 MHz in the measured sweep because its adaptive correction logic lengthens the critical path. At 200 MHz, fixed bias requires 68 LUTs and 0.021 W dynamic power compared with 84 LUTs and 0.029 W for the exact reference. The results demonstrate that approximation quality and FPGA implementation efficiency must be considered jointly when selecting multiplier cores for vision-oriented hardware.
KEYWORDS
A unique14-point FPGA timing sweep was planned to compare the exact, ordinary truncated, fixed-bias, and BWC-3 8-bit multipliers using integrated wrapper. The measurements reveal a clear trade-off among timing robustness, and implementation hardware cost. The ordinary truncation multiplier is the smallest design and meets timing at 200 MHz, fixed bias also preserving 200-MHz timing closure and retaining lower LUT, dynamic-power, PDP, and ADP values compare with the exact reference. The BWC-3 architecture have the highest arithmetic accuracy, but its additional compensation logic limits measured timing closure to 133 MHz and increases LUT/ADP cost for hardware. For high-throughput vision architecture datapaths, the observed data thus identified fixed bias as a balanced implementation point, while BWC-3 is better for accuracy demanding operations.
[1] N. Petra, D. De Caro, V. Garofalo, E. Napoli, and A. G. M. Strollo, “Truncated binary multipliers with variable correction and minimum mean square error,” IEEE Trans. Circuits Syst. I, Reg. Papers, vol. 57, no. 6, pp. 1312–1325, Jun. 2010, doi: 10.1109/TCSI.2009.2033536. [2] V. Garofalo, N. Petra, and E. Napoli, “Analytical calculation of the maximum error for a family of truncated multipliers providing minimum mean square error,” IEEE Trans. Comput., vol. 60, no. 9, pp. 1366–1371, Sep. 2011, doi: 10.1109/TC.2010.236. [3] N. Petra, D. De Caro, V. Garofalo, E. Napoli, and A. G. M. Strollo, “Design of fixed-width multipliers with linear compensation function,” IEEE Trans. Circuits Syst. I, Reg. Papers, vol. 58, no. 5, pp. 947–960, May 2011, doi: 10.1109/TCSI.2010.2090572. [4] G. Zervakis, K. Tsoumanis, S. Xydis, D. Soudris, and K. Pekmestzi, “Design-efficient approximate multiplication circuits through partial product perforation,” IEEE Trans. Very Large Scale Integr. (VLSI) Syst., vol. 24, no. 10, pp. 3105–3117, Oct. 2016, doi: 10.1109/TVLSI.2016.2535398. [5] S. Vahdat, M. Kamal, A. Afzali-Kusha, and M. Pedram, “TOSAM: An energy-efficient truncation- and rounding-based scalable approximate multiplier,” IEEE Trans. Very Large Scale Integr. (VLSI) Syst., vol. 27, no. 5, pp. 1161–1173, May 2019, doi: 10.1109/TVLSI.2018.2890712. [7] Y. Wu, C. Chen, W. Xiao, X. Wang, C. Wen, J. Han, X. Yin, W. Qian, and C. Zhuo, “A survey on approximate multiplier designs for energy efficiency: From algorithms to circuits,” ACM Trans. Design Autom. Electron. Syst., vol. 29, no. 1, Art. no. 23, pp. 1–37, Jan. 2024, doi: 10.1145/3610291. [8] L. Sayadi, S. Timarchi, and A. Sheikh-Akbari, “Two efficient approximate unsigned multipliers by developing new configuration for approximate 4:2 compressors,” IEEE Trans. Circuits Syst. I, Reg. Papers, vol. 70, no. 4, pp. 1649–1659, Apr. 2023, doi: 10.1109/TCSI.2023.3242558. [9] S. Shakibhamedan, N. Amirafshar, A. S. Baroughi, H. S. Shahhoseini, and N. TaheriNejad, “ACE-CNN: Approximate carry disregard multipliers for energy-efficient CNN-based image classification,” IEEE Trans. Circuits Syst. I, Reg. Papers, vol. 71, no. 5, pp. 2280–2293, May 2024, doi: 10.1109/TCSI.2024.3369230. [10] Z. Li, S. Zheng, J. Zhang, Y. Lu, J. Gao, J. Tao, and L. Wang, “Adaptable approximate multiplier design based on input distribution and polarity,” IEEE Trans. Very Large Scale Integr. (VLSI) Syst., vol. 30, no. 12, pp. 1813–1826, Dec. 2022, doi: 10.1109/TVLSI.2022.3197229.
Publication Date
10/5/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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