Low Power RAM based CAM with Run Time Calculation of Last Index

Meharban Khan, Masroor Ali, Qazi Muddussir
{"title":"Low Power RAM based CAM with Run Time Calculation of Last Index","authors":"Meharban Khan, Masroor Ali, Qazi Muddussir","doi":"10.1109/ICET.2015.7389168","DOIUrl":null,"url":null,"abstract":"This paper proposes a method to overcome extra hardware by calculating the last index in run time, and reduce high power consumption using bank selection technique to divide the whole memory into 4 partitions, which reduce the power consumption, thereby eliminating the disadvantage of searching an input data in all the memory addresses. Although [1] configure RAM as a CAM is there to provide searching operation, however this method has disadvantages like high power consumption and extra memory for saving the value of last index. The proposed method logically dissects the memory into 4 partitions. Each partition is accessed through the first two bits of the input word, search operation is only performed in that particular partition (one quarter of whole memory), which saves the searching time and power consumption. To validate and justify our approach, a 16×16 memory is divided into four 4×16 memory chunks and implemented on Xilinx Virtex-6 FPGA.","PeriodicalId":166507,"journal":{"name":"2015 International Conference on Emerging Technologies (ICET)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Emerging Technologies (ICET)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICET.2015.7389168","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

This paper proposes a method to overcome extra hardware by calculating the last index in run time, and reduce high power consumption using bank selection technique to divide the whole memory into 4 partitions, which reduce the power consumption, thereby eliminating the disadvantage of searching an input data in all the memory addresses. Although [1] configure RAM as a CAM is there to provide searching operation, however this method has disadvantages like high power consumption and extra memory for saving the value of last index. The proposed method logically dissects the memory into 4 partitions. Each partition is accessed through the first two bits of the input word, search operation is only performed in that particular partition (one quarter of whole memory), which saves the searching time and power consumption. To validate and justify our approach, a 16×16 memory is divided into four 4×16 memory chunks and implemented on Xilinx Virtex-6 FPGA.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于低功耗RAM的最后索引运行时间计算CAM
本文提出了一种通过在运行时计算最后一个索引来克服额外硬件的方法,并利用bank选择技术将整个内存划分为4个分区,从而降低了高功耗,从而消除了在所有内存地址中搜索输入数据的缺点。虽然[1]将RAM配置为CAM来提供搜索操作,但是这种方法存在功耗高和用于保存最后一个索引值的额外内存等缺点。所提出的方法在逻辑上将内存划分为4个分区。通过输入字的前两位访问每个分区,只在该特定分区(占整个内存的四分之一)中执行搜索操作,节省了搜索时间和功耗。为了验证和证明我们的方法,将16×16内存分为四个4×16内存块,并在Xilinx Virtex-6 FPGA上实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
A comparative study of target tracking with Kalman filter, extended Kalman filter and particle filter using received signal strength measurements Optimizing NEURON brain simulator with Remote Memory Access on distributed memory systems Theoretical and empirical based extinction coefficients for fog attenuation in terms of visibility at 850 nm Effort estimation of ETL projects using Forward Stepwise Regression An evaluation of software fault tolerance techniques for optimality
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1