基于DVFS的LDPC解码器早期终止电源管理

Reza Ghanaatian, A. Burg
{"title":"基于DVFS的LDPC解码器早期终止电源管理","authors":"Reza Ghanaatian, A. Burg","doi":"10.1109/SiPS.2017.8109981","DOIUrl":null,"url":null,"abstract":"Low-density parity check (LDPC) codes are a mature coding scheme in telecommunications and the low power implementation of corresponding decoders is an issue of significant importance for receivers with stringent power budgets. This paper presents a power reduction technique for LDPC decoders that further extends their energy-proportional behavior, obtained with early-termination (ET), by predicting the required number of iterations and by applying dynamic voltage and frequency scaling (DVFS). The number of expected iterations and the associated voltage/frequency settings are predicted with a novel algorithm that is based on the offline statistical analysis of the number of decoding iterations. This algorithm systematically trades the error-correcting performance up to a predefined approximation level for the achieved amount of power reduction beyond ET. Simulation and postlayout implementation results in a 28 nm FD-SOI technology prove that the proposed algorithm, when integrated with an LDPC decoder, can significantly reduce the power consumption with negligible overhead.","PeriodicalId":251688,"journal":{"name":"2017 IEEE International Workshop on Signal Processing Systems (SiPS)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"DVFS based power management for LDPC decoders with early termination\",\"authors\":\"Reza Ghanaatian, A. Burg\",\"doi\":\"10.1109/SiPS.2017.8109981\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Low-density parity check (LDPC) codes are a mature coding scheme in telecommunications and the low power implementation of corresponding decoders is an issue of significant importance for receivers with stringent power budgets. This paper presents a power reduction technique for LDPC decoders that further extends their energy-proportional behavior, obtained with early-termination (ET), by predicting the required number of iterations and by applying dynamic voltage and frequency scaling (DVFS). The number of expected iterations and the associated voltage/frequency settings are predicted with a novel algorithm that is based on the offline statistical analysis of the number of decoding iterations. This algorithm systematically trades the error-correcting performance up to a predefined approximation level for the achieved amount of power reduction beyond ET. Simulation and postlayout implementation results in a 28 nm FD-SOI technology prove that the proposed algorithm, when integrated with an LDPC decoder, can significantly reduce the power consumption with negligible overhead.\",\"PeriodicalId\":251688,\"journal\":{\"name\":\"2017 IEEE International Workshop on Signal Processing Systems (SiPS)\",\"volume\":\"63 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE International Workshop on Signal Processing Systems (SiPS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SiPS.2017.8109981\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE International Workshop on Signal Processing Systems (SiPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SiPS.2017.8109981","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

低密度奇偶校验码(LDPC)是一种成熟的通信编码方案,对于具有严格功率预算的接收机来说,低功耗解码器的实现是一个非常重要的问题。本文提出了一种LDPC解码器的功耗降低技术,通过预测所需的迭代次数和应用动态电压和频率缩放(DVFS),进一步扩展了LDPC解码器的能量比例行为,该行为是由早期终止(ET)获得的。使用基于解码迭代次数的离线统计分析的新算法预测预期迭代次数和相关电压/频率设置。该算法系统地将纠错性能提高到预定义的近似水平,以达到超过ET的功耗降低量。在28 nm FD-SOI技术上的仿真和布局后实现结果证明,当与LDPC解码器集成时,该算法可以显着降低功耗,开销可以忽略不计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
DVFS based power management for LDPC decoders with early termination
Low-density parity check (LDPC) codes are a mature coding scheme in telecommunications and the low power implementation of corresponding decoders is an issue of significant importance for receivers with stringent power budgets. This paper presents a power reduction technique for LDPC decoders that further extends their energy-proportional behavior, obtained with early-termination (ET), by predicting the required number of iterations and by applying dynamic voltage and frequency scaling (DVFS). The number of expected iterations and the associated voltage/frequency settings are predicted with a novel algorithm that is based on the offline statistical analysis of the number of decoding iterations. This algorithm systematically trades the error-correcting performance up to a predefined approximation level for the achieved amount of power reduction beyond ET. Simulation and postlayout implementation results in a 28 nm FD-SOI technology prove that the proposed algorithm, when integrated with an LDPC decoder, can significantly reduce the power consumption with negligible overhead.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Analysing the performance of divide-and-conquer sequential matrix diagonalisation for large broadband sensor arrays Design space exploration of dataflow-based Smith-Waterman FPGA implementations Hardware error correction using local syndromes A stochastic number representation for fully homomorphic cryptography Statistical analysis of Post-HEVC encoded videos
×
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