Please use this identifier to cite or link to this item: https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/2285
Title: Power-Efficient Mloa For Error Resilient Applications
Authors: Guturu, Sahith
Uppugunduru, Anil Kumar
Thota, Sridhar
Ahmed, Syed Ershad
Keywords: Approximate Adder
Approximate Computing
Image Sharpening
Low Power
Issue Date: 2021
Publisher: 2021 IEEE International Symposium on Smart Electronic Systems (iSES), iSES 2021
Citation: pp. 79-83
Abstract: Approximate Computing is a paradigm shift to meet the future demands of compute-intensive tasks such as media processing, data mining, and recognition. These applications can tolerate errors up to a specific limit. In such applications, addition is one unit that is power-hungry by approximating the adder savings in area, power, and delay can be achieved. This paper presents a technique of approximating the least significant portion in an adder while improvement in accuracy is achieved using OR-based logic. This results in a reduction of area and power without significant compromise in accuracy. Based on the approximation region, we propose three designs with a tradeoff in computation complexity and accuracy. The results prove the efficacy of the proposed designs and an improvement up to 51.39%, improvement in power w.r.t existing designs. © 2021 IEEE.All rights reserved.
URI: https://doi.org/10.1109/iSES52644.2021.00029
http://gnanaganga.inflibnet.ac.in:8080/jspui/handle/123456789/2285
ISBN: 9781728187532
9781665416184
Appears in Collections:Conference Papers

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