Neo: Towards Efficient Fully Homomorphic Encryption Acceleration using Tensor Core
Dian Jiao, Xianglong Deng, Zhiwei Wang, Shengyu Fan, Yi Chen, Dan Meng, Rui Hou, Mingzhe Zhang · 2025
Fully Homomorphic Encryption (FHE) is an emerging cryptographic technique for privacy-preserving computation, which enables computations on the encrypted data.Nonetheless, the massive computational demands of FHE prevent its further application to real-world workloads.To tackle this problem, several studies focus on the ASIC-based acceleration for FHE.However, the rapid evolution of FHE algorithms poses challenges to the generality of ASIC accelerator design.By contrast, a number of works rely on GPGPUs for FHE accelerations, due to the high parallelism and flexibility provided by GPGPUs.In this work, we propose a GPGPU-based acceleration solution that supports the Cheon-Kim-Kim-Song (CKKS) scheme by further exploiting Tensor Core(TCU) capabilities.In our study, we * Both author contributed equally to this research.