  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.
