Fast Combinational Architecture for a Vedic Divider

Parashar, Abhinav; Aggarwal, Gaurav; Dang, Radhika; Dalmia, Preyesh; Pandey, Neeta

doi:10.1109/indicon.2017.8487598

Cited by 7 publications

(1 citation statement)

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“…These iterative algorithms are implemented sequentially and have a long latency, a significant area overhead and consume a large amount of power compared to the other mathematical operations [34]. Therefore, many reduction approaches can reduce the number of division cycles, thus reducing power dissipation [35].…”

Section: Division Algorithmmentioning

confidence: 99%

Power optimization of binary division based on FPGA

Nasser

Hashim

2021

IJEECS

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In modern very large scale integrated (VLSI) digital systems, power consumption has become a critical concern of VLSI designers. As size shrinks and density increases in chips, it will be a challenge to design high performance and low-power digital systems. Therefore, VLSI designers are trying to reduce power dissipation in these systems by using power optimization techniques. Different mathematical operations can be found in the architectures of most digital systems. The focus of this paper is division. In comparison to other basic computational operations, division requires more iterations, takes a long time, covers a large area, and consumes more power from the digital system. As a result, the system's design requires high speed and a low-power divider in order to improve its overall performance. This paper focuses on dynamic power dissipation. In order to determine which design consumes the lowest dynamic power, different system designs of digit-recurrence division algorithms, such as restoring division and non-restoring division are suggested. An innovative power-optimization technique, the very hardware descriptions language (VHDL) technique, is utilized to the suggested system designs. The VHDL technique achieved the higher optimization in dynamic power, at 93.66% for non-restoring division with internal-loop iteration, than traditional approaches.

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Section: Division Algorithmmentioning

confidence: 99%