GPU Acceleration for FHEW/TFHE Bootstrapping

Abstract: Fully Homomorphic Encryption (FHE) allows computations to be performed directly on encrypted data without decryption. Despite its great theoretical potential, the computational overhead remains a major obstacle for practical applications. To address this challenge, hardware acceleration has emerged as a promising approach, aiming to achieve real-time computation across a wider range of scenarios. In line with this, our research focuses on designing and implementing a Graphic Processing Unit (GPU)-based accelerator for the third generation FHEW/TFHE bootstrapping scheme, which features smaller parameters and bootstrapping keys particularly suitable for GPU architectures compared to the other generations. In summary, our accelerator offers improved efficiency, scalability, and flexibility for extensions, e.g., functional bootstrapping (Liu et al., Asiacrypt 2022), compared to current state-of-the-art solutions. We evaluate our implementation and demonstrate substantial speedup in the.... https://ojs.ub.rub.de/index.php/TCHES/article/view/11931

Object Details

• Location: Deutsche Nationalbibliothek Frankfurt am Main
• Extent: Online-Ressource
• Language: Englisch

References and Relationships

• Bibliographic citation: GPU Acceleration for FHEW/TFHE Bootstrapping ; volume:2025 ; number:1 ; year:2024 ; IACR transactions on cryptographic hardware and embedded systems ; 2025, Heft 1 (2024)

Contributors, Places and Time

• Creator: Xiao, Yu ; Liu, Feng-Hao ; Ku, Yu-Te ; Ho, Ming-Chien ; Hsu, Chih-Fan ; Chang, Ming-Ching ; Hung, Shih-Hao ; Chen, Wei-Chao

Further information

• DOI: 10.46586/tches.v2025.i1.314-339
• URN: urn:nbn:de:101:1-2412181756220.692965686508
• Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
• Last update: 15.08.2025, 7:21 AM CEST