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的基本挑战在于其低效性，这主要源于底层多项式计算的高计算复杂度以及极为耗时的密文维护操作。为应对这一挑战，学术界和工业界近期提出了多种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加速器的演化轨迹，建立它们之间的定性关联；随后，通过对代表性开源FHE加速器进行测试床评估，实现定量对比；最后，基于定性与定量研究的见解，探讨未来FHE加速器设计与实现的潜在方向。