Paper 2024/1543 Original: eprint.iacr.org/2024/1543 ↗

HEonGPU: a GPU-based Fully Homomorphic Encryption Library 1.0

Abstract

HEonGPU is a high-performance library designed to optimize Fully Homomorphic Encryption (FHE) operations on Graphics Processing Unit (GPU). By leveraging the parallel processing capac- ity of GPUs, HEonGPU significantly reduces the computational overhead typically associated with FHE by executing complex operation concurrently. This allows for faster execution of homomorphic computations on encrypted data, enabling real-time applications in privacy-preserving machine learn- ing and secure data processing. A key advantage of HEonGPU lies in its multi-stream architecture, which not only allows parallel processing of tasks to improve throughput but also eliminates the over- head of data transfers between the host device (i.e., CPU) and GPU. By efficiently managing data within the GPU using multi-streams, HEonGPU minimizes the need for repeated memory transfers, further enhancing performance. HEonGPU’s GPU-optimized design makes it ideal for large-scale encrypted computations, providing users with reduced latency and higher performance across various FHE schemes.