AEKA:为基于环二进制-LWE 的轻量级 PQC 实现面积效率高的 Karatsuba 加速器的 FPGA 实现

IF 3.1 4区 计算机科学 Q2 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE ACM Transactions on Reconfigurable Technology and Systems Pub Date : 2023-12-11 DOI:10.1145/3637215
Tianyou Bao, Pengzhou He, Jiafeng Xie, H S. Jacinto
{"title":"AEKA:为基于环二进制-LWE 的轻量级 PQC 实现面积效率高的 Karatsuba 加速器的 FPGA 实现","authors":"Tianyou Bao, Pengzhou He, Jiafeng Xie, H S. Jacinto","doi":"10.1145/3637215","DOIUrl":null,"url":null,"abstract":"<p>Lightweight PQC-related research and development have gradually gained attention from the research community recently. Ring-Binary-Learning-with-Errors (RBLWE)-based encryption scheme (RBLWE-ENC), a promising lightweight PQC based on small parameter sets to fit related applications (but not in favor of deploying popular fast algorithms like number theoretic transform). To solve this problem, in this paper, we present a novel implementation of hardware acceleration for RBLWE-ENC based on Karatsuba algorithm, particularly on the field-programmable gate array (FPGA) platform. In detail, we have proposed an area-efficient Karatsuba Accelerator (AEKA) for RBLWE-ENC, based on three layers of innovative efforts. First of all, we reformulate the signal processing sequence within the major arithmetic component of the KA-based polynomial multiplication for RBLWE-ENC to obtain a new algorithm. Then, we have designed the proposed algorithm into a new hardware accelerator with several novel algorithm-to-architecture mapping techniques. Finally, we have conducted thorough complexity analysis and comparison to demonstrate the efficiency of the proposed accelerator, e.g., it involves 62.5% higher throughput and 60.2% less area-delay product (ADP) than the state-of-the-art design for <i>n</i> = 512 (Virtex-7 device, similar setup). The proposed AEKA design strategy is highly efficient on the FPGA devices, i.e., small resource usage with superior timing, which can be integrated with other necessary systems for lightweight-oriented high-performance applications (e.g., servers). The outcome of this work is also expected to generate impacts for lightweight PQC advancement.</p>","PeriodicalId":49248,"journal":{"name":"ACM Transactions on Reconfigurable Technology and Systems","volume":"12 1","pages":""},"PeriodicalIF":3.1000,"publicationDate":"2023-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"AEKA: FPGA Implementation of Area-Efficient Karatsuba Accelerator for Ring-Binary-LWE-based Lightweight PQC\",\"authors\":\"Tianyou Bao, Pengzhou He, Jiafeng Xie, H S. Jacinto\",\"doi\":\"10.1145/3637215\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Lightweight PQC-related research and development have gradually gained attention from the research community recently. Ring-Binary-Learning-with-Errors (RBLWE)-based encryption scheme (RBLWE-ENC), a promising lightweight PQC based on small parameter sets to fit related applications (but not in favor of deploying popular fast algorithms like number theoretic transform). To solve this problem, in this paper, we present a novel implementation of hardware acceleration for RBLWE-ENC based on Karatsuba algorithm, particularly on the field-programmable gate array (FPGA) platform. In detail, we have proposed an area-efficient Karatsuba Accelerator (AEKA) for RBLWE-ENC, based on three layers of innovative efforts. First of all, we reformulate the signal processing sequence within the major arithmetic component of the KA-based polynomial multiplication for RBLWE-ENC to obtain a new algorithm. Then, we have designed the proposed algorithm into a new hardware accelerator with several novel algorithm-to-architecture mapping techniques. Finally, we have conducted thorough complexity analysis and comparison to demonstrate the efficiency of the proposed accelerator, e.g., it involves 62.5% higher throughput and 60.2% less area-delay product (ADP) than the state-of-the-art design for <i>n</i> = 512 (Virtex-7 device, similar setup). The proposed AEKA design strategy is highly efficient on the FPGA devices, i.e., small resource usage with superior timing, which can be integrated with other necessary systems for lightweight-oriented high-performance applications (e.g., servers). The outcome of this work is also expected to generate impacts for lightweight PQC advancement.</p>\",\"PeriodicalId\":49248,\"journal\":{\"name\":\"ACM Transactions on Reconfigurable Technology and Systems\",\"volume\":\"12 1\",\"pages\":\"\"},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2023-12-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM Transactions on Reconfigurable Technology and Systems\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1145/3637215\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Transactions on Reconfigurable Technology and Systems","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1145/3637215","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE","Score":null,"Total":0}
引用次数: 0

摘要

与轻量级 PQC 相关的研究和开发近来逐渐受到研究界的关注。基于环二进制学习与错误(RBLWE)的加密方案(RBLWE-ENC),是一种基于小参数集的轻量级 PQC,适合相关应用(但不支持部署流行的快速算法,如数论变换),前景广阔。为了解决这个问题,我们在本文中提出了一种基于 Karatsuba 算法的 RBLWE-ENC 硬件加速新实现,特别是在现场可编程门阵列(FPGA)平台上。具体而言,我们基于三层创新努力,为 RBLWE-ENC 提出了一种面积效率高的 Karatsuba 加速器(AEKA)。首先,我们在基于 KA 的 RBLWE-ENC 多项式乘法的主要算术部分中重新制定了信号处理序列,从而获得了一种新算法。然后,我们利用几种新颖的算法到架构映射技术,将所提出的算法设计到一个新的硬件加速器中。最后,我们进行了全面的复杂性分析和比较,以证明所提加速器的效率,例如,在 n = 512(Virtex-7 器件,类似设置)的情况下,它的吞吐量比最先进的设计高 62.5%,面积-延迟积(ADP)比最先进的设计低 60.2%。所提出的 AEKA 设计策略在 FPGA 器件上具有很高的效率,即资源使用量小,时序性能优越,可与其他必要系统集成,用于面向轻量级的高性能应用(如服务器)。这项工作的成果也有望对轻量级 PQC 的发展产生影响。
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
AEKA: FPGA Implementation of Area-Efficient Karatsuba Accelerator for Ring-Binary-LWE-based Lightweight PQC

Lightweight PQC-related research and development have gradually gained attention from the research community recently. Ring-Binary-Learning-with-Errors (RBLWE)-based encryption scheme (RBLWE-ENC), a promising lightweight PQC based on small parameter sets to fit related applications (but not in favor of deploying popular fast algorithms like number theoretic transform). To solve this problem, in this paper, we present a novel implementation of hardware acceleration for RBLWE-ENC based on Karatsuba algorithm, particularly on the field-programmable gate array (FPGA) platform. In detail, we have proposed an area-efficient Karatsuba Accelerator (AEKA) for RBLWE-ENC, based on three layers of innovative efforts. First of all, we reformulate the signal processing sequence within the major arithmetic component of the KA-based polynomial multiplication for RBLWE-ENC to obtain a new algorithm. Then, we have designed the proposed algorithm into a new hardware accelerator with several novel algorithm-to-architecture mapping techniques. Finally, we have conducted thorough complexity analysis and comparison to demonstrate the efficiency of the proposed accelerator, e.g., it involves 62.5% higher throughput and 60.2% less area-delay product (ADP) than the state-of-the-art design for n = 512 (Virtex-7 device, similar setup). The proposed AEKA design strategy is highly efficient on the FPGA devices, i.e., small resource usage with superior timing, which can be integrated with other necessary systems for lightweight-oriented high-performance applications (e.g., servers). The outcome of this work is also expected to generate impacts for lightweight PQC advancement.

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
ACM Transactions on Reconfigurable Technology and Systems
ACM Transactions on Reconfigurable Technology and Systems COMPUTER SCIENCE, HARDWARE & ARCHITECTURE-
CiteScore
4.90
自引率
8.70%
发文量
79
审稿时长
>12 weeks
期刊介绍: TRETS is the top journal focusing on research in, on, and with reconfigurable systems and on their underlying technology. The scope, rationale, and coverage by other journals are often limited to particular aspects of reconfigurable technology or reconfigurable systems. TRETS is a journal that covers reconfigurability in its own right. Topics that would be appropriate for TRETS would include all levels of reconfigurable system abstractions and all aspects of reconfigurable technology including platforms, programming environments and application successes that support these systems for computing or other applications. -The board and systems architectures of a reconfigurable platform. -Programming environments of reconfigurable systems, especially those designed for use with reconfigurable systems that will lead to increased programmer productivity. -Languages and compilers for reconfigurable systems. -Logic synthesis and related tools, as they relate to reconfigurable systems. -Applications on which success can be demonstrated. The underlying technology from which reconfigurable systems are developed. (Currently this technology is that of FPGAs, but research on the nature and use of follow-on technologies is appropriate for TRETS.) In considering whether a paper is suitable for TRETS, the foremost question should be whether reconfigurability has been essential to success. Topics such as architecture, programming languages, compilers, and environments, logic synthesis, and high performance applications are all suitable if the context is appropriate. For example, an architecture for an embedded application that happens to use FPGAs is not necessarily suitable for TRETS, but an architecture using FPGAs for which the reconfigurability of the FPGAs is an inherent part of the specifications (perhaps due to a need for re-use on multiple applications) would be appropriate for TRETS.
期刊最新文献
End-to-end codesign of Hessian-aware quantized neural networks for FPGAs DyRecMul: Fast and Low-Cost Approximate Multiplier for FPGAs using Dynamic Reconfiguration Dynamic-ACTS - A Dynamic Graph Analytics Accelerator For HBM-Enabled FPGAs NC-Library: Expanding SystemC Capabilities for Nested reConfigurable Hardware Modelling PQA: Exploring the Potential of Product Quantization in DNN Hardware Acceleration
×
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