Flexible GPU-Based Implementation of Number Theoretic Transform for Homomorphic Encryption

Phap Duong-Ngoc, Thang Xuan Pham, Hanho Lee, Tuy Tan Nguyen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

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.

Original languageEnglish (US)
Title of host publicationProceedings - International SoC Design Conference 2022, ISOCC 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages259-260
Number of pages2
ISBN (Electronic)9781665459716
DOIs
StatePublished - 2022
Externally publishedYes
Event19th International System-on-Chip Design Conference, ISOCC 2022 - Gangneung-si, Korea, Republic of
Duration: Oct 19 2022Oct 22 2022

Publication series

NameProceedings - International SoC Design Conference 2022, ISOCC 2022

Conference

Conference19th International System-on-Chip Design Conference, ISOCC 2022
Country/TerritoryKorea, Republic of
CityGangneung-si
Period10/19/2210/22/22

Keywords

  • butterfly unit
  • Graphic Processing Unit
  • lattice-based cryptography
  • Number theoretic transform (NTT)

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Hardware and Architecture
  • Safety, Risk, Reliability and Quality

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