A General Approach for Improving RNS Montgomery Exponentiation Using Pre-processing

F. Gandino, F. Lamberti, P. Montuschi, J. Bajard
{"title":"A General Approach for Improving RNS Montgomery Exponentiation Using Pre-processing","authors":"F. Gandino, F. Lamberti, P. Montuschi, J. Bajard","doi":"10.1109/ARITH.2011.35","DOIUrl":null,"url":null,"abstract":"The hardware implementation of modular exponentiation for very large integers is a well-known topic in digital arithmetic. An effective approach for obtaining parallel and carry-free implementations consists in using the Montgomery exponentiation algorithm and executing the necessary operations in RNS. Two efficient methods for performing the RNS Montgomery exponentiation have been proposed by Kawamura et al. and by Bajard and Imbert. The above approaches mainly differ in the algorithm used for implementing the base extension. This paper presents a modified RNS Montgomery exponentiation algorithm, where several multiplications are moved outside the main execution loop and replaced by an effective pre-processing stage producing a significant saving on the overall delay with respect to state-of-the-art approaches. Since the proposed modification should be applied to both of the above algorithms, two versions are specifically discussed.","PeriodicalId":272151,"journal":{"name":"2011 IEEE 20th Symposium on Computer Arithmetic","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"26","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE 20th Symposium on Computer Arithmetic","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ARITH.2011.35","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 26

Abstract

The hardware implementation of modular exponentiation for very large integers is a well-known topic in digital arithmetic. An effective approach for obtaining parallel and carry-free implementations consists in using the Montgomery exponentiation algorithm and executing the necessary operations in RNS. Two efficient methods for performing the RNS Montgomery exponentiation have been proposed by Kawamura et al. and by Bajard and Imbert. The above approaches mainly differ in the algorithm used for implementing the base extension. This paper presents a modified RNS Montgomery exponentiation algorithm, where several multiplications are moved outside the main execution loop and replaced by an effective pre-processing stage producing a significant saving on the overall delay with respect to state-of-the-art approaches. Since the proposed modification should be applied to both of the above algorithms, two versions are specifically discussed.
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
一种利用预处理改进RNS Montgomery幂的通用方法
大整数模幂运算的硬件实现是数字算法中一个众所周知的课题。在RNS中使用Montgomery指数算法并执行必要的操作是实现并行和无携带实现的有效方法。Kawamura等人以及Bajard和Imbert提出了两种执行RNS Montgomery幂的有效方法。上述方法的主要区别在于实现基扩展所使用的算法。本文提出了一种改进的RNS Montgomery幂运算算法,其中几个乘法被移出主执行循环,并被一个有效的预处理阶段所取代,与最先进的方法相比,这大大节省了总体延迟。由于所提出的修改应适用于上述两种算法,因此具体讨论了两种版本。
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
Fused Multiply-Add Microarchitecture Comprising Separate Early-Normalizing Multiply and Add Pipelines A 1.5 Ghz VLIW DSP CPU with Integrated Floating Point and Fixed Point Instructions in 40 nm CMOS Flocq: A Unified Library for Proving Floating-Point Algorithms in Coq Teraflop FPGA Design Self Checking in Current Floating-Point Units
×
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