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Paper 2018/1018

Faster multiplication in $\mathbb{Z}_{2^m}[x]$ on Cortex-M4 to speed up NIST PQC candidates

Matthias J. Kannwischer and Joost Rijneveld and Peter Schwabe

Abstract

In this paper we optimize multiplication of polynomials in $\mathbb{Z}_{2^m}[x]$ on the ARM Cortex-M4 microprocessor. We use these optimized multiplication routines to speed up the NIST post-quantum candidates RLizard, NTRU-HRSS, NTRUEncrypt, Saber, and Kindi. For most of those schemes the only previous implementation that executes on the Cortex-M4 is the reference implementation submitted to NIST; for some of those schemes our optimized software is more than factor of 20 faster. One of the schemes, namely Saber, has been optimized on the Cortex-M4 in a CHES 2018 paper; the multiplication routine for Saber we present here outperforms the multiplication from that paper by 37%, yielding speedups of 17% for key generation, 15% for encapsulation and 18% for decapsulation. Out of the five schemes optimized in this paper, the best performance for encapsulation and decapsulation is achieved by NTRU-HRSS. Specifically, encapsulation takes just over 430 000 cycles, which is more than twice as fast as for any other NIST candidate that has previously been optimized on the ARM Cortex-M4.

Metadata
Available format(s)
PDF
Category
Implementation
Publication info
Preprint. MINOR revision.
Keywords
ARM Cortex-M4KaratsubaToomlattice-based KEMsNTRU
Contact author(s)
joost @ joostrijneveld nl
History
2019-04-09: revised
2018-10-24: received
See all versions
Short URL
https://ia.cr/2018/1018
License
Creative Commons Attribution
CC BY
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