Polynomial multiplication on embedded vector architectures

Autor: Hanno Becker, Jose Maria Bermudo Mera, Angshuman Karmakar, Joseph Yiu, Ingrid Verbauwhede
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Transactions on Cryptographic Hardware and Embedded Systems, Vol 2022, Iss 1 (2021)
Druh dokumentu: article
ISSN: 2569-2925
DOI: 10.46586/tches.v2022.i1.482-505
Popis: High-degree, low-precision polynomial arithmetic is a fundamental computational primitive underlying structured lattice based cryptography. Its algorithmic properties and suitability for implementation on different compute platforms is an active area of research, and this article contributes to this line of work: Firstly, we present memory-efficiency and performance improvements for the Toom-Cook/Karatsuba polynomial multiplication strategy. Secondly, we provide implementations of those improvements on Arm® Cortex®-M4 CPU, as well as the newer Cortex-M55 processor, the first M-profile core implementing the M-profile Vector Extension (MVE), also known as Arm® Helium™ technology. We also implement the Number Theoretic Transform (NTT) on the Cortex-M55 processor. We show that despite being singleissue, in-order and offering only 8 vector registers compared to 32 on A-profile SIMD architectures like Arm® Neon™ technology and the Scalable Vector Extension (SVE), by careful register management and instruction scheduling, we can obtain a 3× to 5× performance improvement over already highly optimized implementations on Cortex-M4, while maintaining a low area and energy profile necessary for use in embedded market. Finally, as a real-world application we integrate our multiplication techniques to post-quantum key-encapsulation mechanism Saber
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