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 11 FHE accelerators -- cuHE/cuFHE, nuFHE, HEAT, HEAX, HEXL, HEXL-FPGA, 100$\times$, F1, CraterLake, BTS, and ARK. 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:完全基因加密(FHE)是方便隐私保存计算的关键技术。然而,FHE的根本挑战是效率低下,这主要是由于计算复杂程度高和极费时的密码维护操作等基本多元计算。为了应对这一挑战,研究和工业界最近提出了各种FHE加速器。本文首先对11个FHE加速器 -- -- CuHE/cuFHE、nuFHE、HEAT、HEAX、HEXL、HEXL-FGA、100美元/倍、F1、CraterLake、BTS和ARK -- -- 进行系统化研究。我们首先对这些现有FHE加速器的演变轨迹进行观察,以建立它们之间的质量连接。然后,我们对具有代表性的FHE开源加速器进行测试性评价,以提供它们的数量比较。最后,根据定性和定量研究获得的见解,我们讨论了为FHEA加速器的未来设计和实施提供信息的潜在方向。