Fully Homomorphic Encryption~(FHE) is a key technology enabling privacy-preserving computing. However, the fundamental challenge of FHE is its inefficiency, due primarily to the underlying polynomial computations with high computation complexity and extremely time-consuming ciphertext maintenance operations. To tackle this challenge, various FHE accelerators have recently been proposed by both research and industrial communities. This paper takes the first initiative to conduct a systematic study on the 14 FHE accelerators -- cuHE/cuFHE, nuFHE, HEAT, HEAX, HEXL, HEXL-FPGA, 100$\times$, F1, CraterLake, BTS, ARK, Poseidon, FAB and TensorFHE. We first make our observations on the evolution trajectory of these existing FHE accelerators to establish a qualitative connection between them. Then, we perform testbed evaluations of representative open-source FHE accelerators to provide a quantitative comparison on them. Finally, with the insights learned from both qualitative and quantitative studies, we discuss potential directions to inform the future design and implementation for FHE accelerators.

翻译：全同态加密（FHE）是实现隐私保护计算的关键技术。然而，FHE面临的根本挑战在于其效率低下，这主要是由于底层多项式计算具有高计算复杂度，且密文维护操作极为耗时。为应对这一挑战，近年来学术界和工业界提出了多种FHE加速器。本文首次对14种FHE加速器——cuHE/cuFHE、nuFHE、HEAT、HEAX、HEXL、HEXL-FPGA、100×、F1、CraterLake、BTS、ARK、Poseidon、FAB和TensorFHE——进行系统性研究。我们首先观察这些现有FHE加速器的演进轨迹，建立它们之间的定性联系。随后，我们对代表性的开源FHE加速器开展测试平台评估，进行定量比较。最后，基于定性研究与定量研究所得洞见，我们探讨潜在发展方向，为未来FHE加速器的设计与实现提供参考。