An Efficient Floating-Point Multiplier For Low Power Single Precision FPGA Implementation

PDF (400KB), PP.1-9

Author(s)

Thangamani C 1 Poovarasan R 1,*

1. K.S.Rangasamy College of Technology,Tiruchengode, Namakkal,Tamilnadu, India.

* Corresponding author.

DOI: ijitcs/10.96856/2025

Received: 27 Oct. 2024 / Revised: 29 Dec. 2024 / Accepted: 25 Jan. 2025 / Published: 28 Apr. 2025

Abstract

A rapid and energy-efficient floating point unit is constantly required for significant applications such as digital signal processing, image processing, real-time data processing, and multimedia applications. This project suggests using a single-precision Floating Point Multiplier engine to speed FPGA applications. The engine has a modified approach for virtual zeropadding to conserve memory space, and it also includes customizable settings for filter and picture size. To improve the suggested multiplier design, a low power multiplier with lower dynamic power, notably while acting on pixels, has been presented, as well as a quicker increment by one circuit based on gates. Finally, the project displays the post-synthesis power dissipation, area estimation, and picture quality comparison achieved from the suggested architecture's RTL simulation.

Cite This Paper

Thangamani C, Poovarasan R, "An Efficient Floating-Point Multiplier For Low Power Single Precision FPGA Implementation", International Journal of Information Technology and Computer Science(IJITCS), Vol.17, No.2, pp.1-9, 2025. DOI:ijitcs/10.96856/2025

Reference

[1] Towhidy, Ahmad, Reza Omidi, and Karim Mohammadi. " On the Plan of Iterative Inexact Drifting Point Multipliers." IEEE Computer Transactions, 2022. Zhou, Bin, Guangsen Wang, Guisheng Jie, Qing Liu, and Zhiwei Wang are the second group. A rapid drifting point duplicate collector in view of fpgas." IEEE Exchanges for Exceptionally Enormous Scope Combination (VLSI) Frameworks 29, no. 10 (2021), 1782–1789. [3] Lyu, Fei, Yan Xia, Yuheng Chen, Yanxu Wang, Yuanyong Luo, and Yu Wang. " High-throughput low-inactivity pipelined divider for singleaccuracy drifting point numbers." IEEE Exchanges for Extremely Huge Scope Mix (VLSI) Frameworks 30, no. 4 (2022): 544-548. [4] Hao, Seok-Bum Ko, and Zhang. Proficient Estimated Place Multipliers for Profound Learning Calculation." IEEE Journal on Emerging and Selected Topics in Circuits and Systems, Volume 13.1 in the year 2022: 201-211. [5] Haroon Waris, Weiqiang Liu, Fabrizio Lombardi, Chen, Ke, Yue Gao, and Inexact Softmax Capabilities for Energy-Proficient Profound Brain Organizations." The 31st issue of IEEE Transactions on Very Large Scale Integration (VLSI) Systems 1 (2022), pp. 4-16. [6] "Fast Data Delivery for Many-Core Processors," IEEE Transactions on Computers, by M. Bakhshalipour, P. Lotfi-Kamran, A. Mazloumi, F. Samandi, M. Naderan, M. Modaresi, and H. Sarbazi-Azad, IEEE Transactions on Computers, 2018. [7] "Multipliers-Driven Perturbation of Coefficients for Low Power Operation in Reconfiguration FIR Filters," by Andrea Bonetti, Adam Teman, Philippe Flatresse, and Andreas Burg, IEEE Trans. 2017. [8] E. Viegas, A. O. Santin, A. Franc¸a, R. Jasinski, V. A. Pedroni, and L. S. Oliveira. " IEEE Transactions on Computers (TC) published "Towards An Energy-Efficient Anomaly-Based Intrusion Detection Engine for Embedded Systems" in 2017. [9] M. Salehi, A. Ejlali, and B. M. Al-Hashimi, "Two-Stage Low-Energy N-Measured Overt repetitiveness for Hard Constant Multi-Center Frameworks," IEEE Exchanges on Equal and Disseminated Frameworks (2016). [10] Y. Huan and others IEEE Transactions on Computers, vol. 5, 2005), "A 101.4 GOPS/W reconfigurable and scalable controlcentric embedded processor for domain-specific applications." Circuit Framework. I, Reg. Volume of papers. 63, no. 12, pp. 2245-2256, December 2016.