The migration of computation to the cloud has raised concerns regarding the security and privacy of sensitive data, as their need to be decrypted before processing, renders them susceptible to potential breaches. Fully Homomorphic Encryption (FHE) serves as a countermeasure to this issue by enabling computation to be executed directly on encrypted data. Nevertheless, the execution of FHE is orders of magnitude slower compared to unencrypted computation, thereby impeding its practicality and adoption. Therefore, enhancing the performance of FHE is crucial for its implementation in real-world scenarios. In this study, we elaborate on our endeavors to design, implement, fabricate, and post-silicon validate CoFHEE, a co-processor for low-level polynomial operations targeting Fully Homomorphic Encryption execution. With a compact design area of $12mm^2$, CoFHEE features ASIC implementations of fundamental polynomial operations, including polynomial addition and subtraction, Hadamard product, and Number Theoretic Transform, which underlie most higher-level FHE primitives. CoFHEE is capable of natively supporting polynomial degrees of up to $n = 2^{14}$ with a coefficient size of 128 bits, and has been fabricated and silicon-verified using 55nm CMOS technology. To evaluate it, we conduct performance and power experiments on our chip, and compare it to state-of-the-art software implementations and other ASIC designs.

翻译：计算向云端的迁移引发了对敏感数据安全与隐私的担忧，因为数据在处理前需解密，使其易受潜在泄露风险影响。全同态加密（FHE）通过在加密数据上直接执行计算，为此问题提供了一种应对方案。然而，与未加密计算相比，FHE的执行速度慢数个数量级，从而阻碍了其实用性与普及。因此，提升FHE的性能对其实现在真实场景中的应用至关重要。在本研究中，我们详细阐述了设计、实现、制造及硅后验证CoFHEE的探索过程——这是一款针对全同态加密执行的底层多项式运算协处理器。CoFHEE采用紧凑的$12mm^2$设计面积，集成了基础多项式运算的ASIC实现，包括多项式加法和减法、Hadamard积以及数论变换，这些运算构成了大多数高阶FHE原语的基础。CoFHEE能原生支持最高$n = 2^{14}$的多项式次数（系数大小为128比特），并已采用55nm CMOS技术完成制造与硅验证。为评估其性能，我们对芯片进行了功耗与性能实验，并将其与最先进的软件实现及其他ASIC设计进行对比。