@inproceedings{eccee4183db34753889382bf7b7029c2,
title = "Flexible GPU-Based Implementation of Number Theoretic Transform for Homomorphic Encryption",
abstract = "This paper proposes a flexible implementation of Number Theoretic Transform (NTT) on GPU platforms. The proposed method introduces an adjustable number (i.e., NTT_core) of butterfly units that are simultaneously implemented in each NTT computational stage. The NTT implementation of a large polynomial was experimented on an NVIDIA GeForce RTX 3070 GPU card and showed at least 21× acceleration compared with that on the CPU. The proposed approach is worthy to parallelize NTT computations of multiple polynomials in expensive homomorphic functions with high circuit depth.",
keywords = "butterfly unit, Graphic Processing Unit, lattice-based cryptography, Number theoretic transform (NTT)",
author = "Phap Duong-Ngoc and Pham, {Thang Xuan} and Hanho Lee and Nguyen, {Tuy Tan}",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 19th International System-on-Chip Design Conference, ISOCC 2022 ; Conference date: 19-10-2022 Through 22-10-2022",
year = "2022",
doi = "10.1109/ISOCC56007.2022.10031464",
language = "English (US)",
series = "Proceedings - International SoC Design Conference 2022, ISOCC 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "259--260",
booktitle = "Proceedings - International SoC Design Conference 2022, ISOCC 2022",
}