Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/105036
Title: Efficient VLSI implementation of 2^n scaling of signed integer in RNS {2^n-1, 2^n, 2^n+1}
Authors: Tay, Thian Fatt
Chang, Chip-Hong
Low, Jeremy Yung Shern
Keywords: DRNTU::Engineering::Electrical and electronic engineering::Integrated circuits
Issue Date: 2013
Source: Tay, T. F., Chang, C.-H., & Low, J. Y. S. (2013). Efficient VLSI Implementation of 2^n scaling of signed integer in RNS {2^n-1, 2^n, 2^n+1}. IEEE transactions on very large scale integration (VLSI) systems, 21(10), 1936-1940.
Series/Report no.: IEEE transactions on very large scale integration (VLSI) systems
Abstract: Scaling is a problematic operation in residue number system (RNS) but a necessary evil in implementing many digital signal processing algorithms for which RNS is particularly good. Existing signed integer RNS scalers entail a dedicated sign detection circuit, which is as complex as the magnitude scaling operation preceding it. In order to correct the incorrectly scaled negative integer in residue form, substantial hardware overheads have been incurred to detect the range of the residues upon magnitude scaling. In this brief, a fast and area efficient 2n signed integer RNS scaler for the moduli set {2n-1, 2n, 2n+1} is proposed. A complex sign detection circuit has been obviated and replaced by simple logic manipulation of some bit-level information of intermediate magnitude scaling results. Compared with the latest signed integer RNS scalers of comparable dynamic ranges, the proposed architecture achieves at least 21.6% of area saving, 28.8% of speedup, and 32.5% of total power reduction for n ranging from 5 to 8.
URI: https://hdl.handle.net/10356/105036
http://hdl.handle.net/10220/25187
ISSN: 1063-8210
DOI: 10.1109/TVLSI.2012.2221752
Schools: School of Electrical and Electronic Engineering 
Rights: © 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: [http://dx.doi.org/10.1109/TVLSI.2012.2221752].
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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