GPU Acceleration for KLSS Key Switching in Fully Homomorphic Encryption

Shutong Jin and Ray C. C. Cheung ()
Additional contact information
Shutong Jin: Department of Electrical Engineering, City University of Hong Kong, Tat Chee Avenue, Hong Kong SAR, China
Ray C. C. Cheung: Department of Electrical Engineering, City University of Hong Kong, Tat Chee Avenue, Hong Kong SAR, China

Mathematics, 2025, vol. 13, issue 23, 1-16

Abstract: Fully Homomorphic Encryption (FHE) enables privacy-preserving computation but is hindered by high computational overhead, with the key-switching operation being a primary performance bottleneck. This paper introduces the first CUDA-optimized GPU implementation of the Kim, Lee, Seo, and Son (KLSS) key-switching algorithm for three leading FHE schemes: BGV, BFV, and CKKS. Our solution achieves significant performance gains, delivering speedups of up to 181× against the original CPU implementation. Furthermore, we analyze the critical trade-off between the key-switching techniques on GPUs, providing insights for the choice between single- and double-decomposition methods. Our work provides a high-performance tool and offers clear guidelines on the trade-off between latency and hardware memory constraints.

Keywords: fully homomorphic encryption; key switching; GPU acceleration (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/13/23/3809/pdf (application/pdf)
https://www.mdpi.com/2227-7390/13/23/3809/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:13:y:2025:i:23:p:3809-:d:1804886

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().