Energy Efficient Self-Adaptive Dual Mode Logic Address Decoder

Author:

Vicuña KevinORCID,Mosquera CristhopherORCID,Musello ArianaORCID,Benedictis SaraORCID,Rendón MateoORCID,Garzón EstebanORCID,Prócel Luis MiguelORCID,Trojman LionelORCID,Taco RamiroORCID

Abstract

This paper presents a 1024-bit self-adaptive memory address decoder based on Dual Mode Logic (DML) design style to allow working in two modes of operation (i.e., dynamic for high-performance and static for energy-saving). The main novelty of this work relies on the design of a controlling mechanism that mixes both of these modes of operation to simultaneously benefit from their inherent advantages. When performance is the primary target, the mixed operating mode is enabled, and the self-adjustment mechanism identifies at run time the logic gates that have to work in the energy-efficient mode (i.e., static mode), while those belonging to the critical path operate in the faster dynamic mode. Moreover, our address decoder can run in the fully static mode for the lowest energy consumption when speed is not a primary concern. A 65 nm CMOS technology was exploited to simulate and compare our solution with other logically equivalent dynamic and static designs. Operated in the mixed mode, the proposed circuit exhibits negligible speed reduction (8.7%) in comparison with a dynamic logic based design while presenting significantly reduced energy consumption (28%). On the contrary, further energy is saved (29%) with respect to conventional logic styles when our design runs in its energy efficient mode.

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3