A technique for efficiently multiplying two signed numbers using limited area and high speed is presented in this paper. This work uses both the Booth and Vedic multiplication sutra methodologies to enhance the speed and reduction in the area by using two VLSI architectures of radix encoding techniques-Radix-4 and Radix-8-with the Vedic multiplier. The functionality of the proposed methods is tested using an Artix-7 Field Programmable Gate Array (FPGA-XC7A100T-CSG324) in Xilinx Vivado 2019.1 and ASIC 45 nm technology. Two methods of Booth encoding using Vedic multiplier (Urdhva-Tiryakbhyam sutra) were used to develop, and examine the benefits of rapid computational multiplier. The results of the proposed multiplier for Booth-Vedic-Radix-4 encoding (BVR-4) decrease area by 89% and improve Area-Delay Product (ADP) by 72% for a 16-bit multiplier when subjected to other existing multipliers. The Booth-Vedic-Radix-8 (BVR-8) method shows that there will be an 89% reduction in area and an improvement in ADP by 72% for the 16-bit multiplier. The performance is evaluated regarding area occupancy (i.e., LUTs number) and propagation delay (output time). In terms of resource utilization, the proposed BVR-4 and BVR-8 multipliers outperform all the current designs with a marginal effect on speed and area for narrower bit-width ranges.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10725507 | PMC |
http://dx.doi.org/10.1038/s41598-023-49913-5 | DOI Listing |
Heliyon
May 2024
School of Electrical Engineering, University of Johannesburg, Johannesburg 2006, South Africa.
Multipliers are essential components within digital signal processing, arithmetic operations, and various computational tasks, making their design and optimization crucial for improving the efficiency and performance of integrated circuits. Among multiplier architectures, Vedic multipliers stand out due to their inherent efficiency and speed, derived from ancient Indian mathematical principles. This study presents a comprehensive analysis and comparison of 4-bit Vedic multiplier designs utilizing Gate Diffusion Input (GDI), Complementary Metal-Oxide-Semiconductor (CMOS), and Transmission Gate (TG) technologies, utilizing different adder architectures such as Ripple Carry Adder (RCA), and Carry Lookahead Adder (CLA), Carry Skip Adder (CSA).
View Article and Find Full Text PDFSci Rep
April 2024
Department of ECE, Sri Eshwar College of Engineering, Coimbatore, India.
In signal processing applications, the multipliers are essential component of arithmetic functional units in many applications, like digital signal processors, image/video processing, Machine Learning, Cryptography and Arithmetic & Logical units (ALU). In recent years, Profuse multipliers are there. In that, Vedic multiplier is one of the high-performance multiplications and it is used to signal/image processing applications.
View Article and Find Full Text PDFSci Rep
December 2023
Department of ECE, Sona College of Technology, Salem, India.
A technique for efficiently multiplying two signed numbers using limited area and high speed is presented in this paper. This work uses both the Booth and Vedic multiplication sutra methodologies to enhance the speed and reduction in the area by using two VLSI architectures of radix encoding techniques-Radix-4 and Radix-8-with the Vedic multiplier. The functionality of the proposed methods is tested using an Artix-7 Field Programmable Gate Array (FPGA-XC7A100T-CSG324) in Xilinx Vivado 2019.
View Article and Find Full Text PDFCurr Med Imaging
October 2021
Department of Electronics and Communication Engineering, Government College of Engineering Bargur, Krishnagiri- 635104, India.
Aim: FIR filter is the most widely used device in DSP applications, which is also applicable to integrate with image processing approaches. The ALU based FIR structure is applicable for various devices to increase the performance. The ALU design operation includes accumulation, subtraction, shifting, multiplication and filtering.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!