{"title":"Analysis and Hardware Optimization of Lattice Post-Quantum Cryptography Workloads","authors":"Sandhya Koteshwara, M. Kumar, P. Pattnaik","doi":"10.1145/3458903.3458905","DOIUrl":null,"url":null,"abstract":"The mathematical constructs, nature of computations and challenges in optimizing lattice post-quantum cryptographic algorithms on modern many-core processors are discussed in this paper. Identification of time-consuming functions and subsequent hardware optimization using vector units and hardware accelerators of one of the candidates, CRYSTALS-Kyber, leads to performance improvement of around 52% for its SHA3 variant and 83% for its AES variant. Detailed Cycles-per-Instruction (CPI) stack breakdown before and after optimization indicates a CPI of around 0.5 and dominance of load/store operations in these workloads.","PeriodicalId":141766,"journal":{"name":"Hardware and Architectural Support for Security and Privacy","volume":"62 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Hardware and Architectural Support for Security and Privacy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3458903.3458905","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
The mathematical constructs, nature of computations and challenges in optimizing lattice post-quantum cryptographic algorithms on modern many-core processors are discussed in this paper. Identification of time-consuming functions and subsequent hardware optimization using vector units and hardware accelerators of one of the candidates, CRYSTALS-Kyber, leads to performance improvement of around 52% for its SHA3 variant and 83% for its AES variant. Detailed Cycles-per-Instruction (CPI) stack breakdown before and after optimization indicates a CPI of around 0.5 and dominance of load/store operations in these workloads.
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