What question did this study set out to answer?

To accelerate the execution speed of the post-quantum cryptographic algorithm SMAUG-T on modern x86/64 CPUs using optimized number theoretic transforms.

August 19, 2026ETRI JournalOpen Access

Accelerating SMAUG‐T using the number theoretic transform on modern high‐end CPUs

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Authors

WKWooHyung KoKookmin University YKYoungBeom KimKookmin University SSSeog Chung SeoKookmin University

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Overview

Algorithmic study demonstrates accelerated matrix-vector multiplication for SMAUG-T on modern CPUs, suggesting viable high-speed post-quantum cryptography.

Key Points

To accelerate the execution speed of the post-quantum cryptographic algorithm SMAUG-T on modern x86/64 CPUs using optimized number theoretic transforms.
Integrated an NTT-friendly ring homomorphism designed for parallel processing into C(x86/64) and vector-extended (AVX2 and AVX-512) architectures.
Redesigned post-quantum cryptographic optimization techniques, including layer merging, lazy reduction, shuffle, and negative wrapping convolution for parallel execution.
Achieved performance improvements in matrix-vector multiplication for the C-based x86/64 implementation compared to the reference implementation.
Demonstrated superior matrix-vector multiplication execution speeds using AVX-512 assembly compared to AVX2 implementations.

Cite This Study

Ko et al. (2026) studied this question.

synapsesocial.com/papers/6a85636403308d306e2d68ac https://doi.org/10.4218/etrij.2025-0418

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August 19, 2026ETRI JournalOpen Access

Accelerating SMAUG‐T using the number theoretic transform on modern high‐end CPUs

View Full Paper

Ask AI

Bookmark

Authors

WKWooHyung KoKookmin University YKYoungBeom KimKookmin University SSSeog Chung SeoKookmin University

Discussion

Member takes

Overview

Algorithmic study demonstrates accelerated matrix-vector multiplication for SMAUG-T on modern CPUs, suggesting viable high-speed post-quantum cryptography.

Key Points

To accelerate the execution speed of the post-quantum cryptographic algorithm SMAUG-T on modern x86/64 CPUs using optimized number theoretic transforms.
Integrated an NTT-friendly ring homomorphism designed for parallel processing into C(x86/64) and vector-extended (AVX2 and AVX-512) architectures.
Redesigned post-quantum cryptographic optimization techniques, including layer merging, lazy reduction, shuffle, and negative wrapping convolution for parallel execution.
Achieved performance improvements in matrix-vector multiplication for the C-based x86/64 implementation compared to the reference implementation.
Demonstrated superior matrix-vector multiplication execution speeds using AVX-512 assembly compared to AVX2 implementations.

Cite This Study

Ko et al. (2026) studied this question.

synapsesocial.com/papers/6a85636403308d306e2d68ac https://doi.org/10.4218/etrij.2025-0418

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