Among all the arithmetic operations, division operation takes most of the clock cycles resulting in more path delay and higher power consumption. Many algorithms, including logarithmic division (LD), have been implemented to reduce the critical path delay and power consumption of division operation. However, there is a high possibility to further reduce these vital issues by using the novel approximate LD (ALD) algorithm. In the proposed ALD, a truncation adder is used for mantissa addition. Using this adder, the power delay product (PDP) and normalized mean error distance (NMED) are minimized. From the error analysis and hardware evaluation, it is observed that the proposed ALD using truncation adder (ALD‐TA) with an appropriate number of inexact bits achieve lower power consumption and higher accuracy than existing LDs with exact units. The normalized mean error distance of 8‐, 16‐, and 32‐bit ALD‐TA is compared with LDs of same bits and observed a decrease of up to 21%, 20%, and 21%, and the PDP has a reduction of up to 33%, 51%, and 72%, respectively. Application of ALD‐TA to image processing shows that high performance can be achieved by using ALDs than exact LDs.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.