Accelerating Finite-Field and Torus Fully Homomorphic Encryption via Compute-Enabled (S)RAM

Fully Homomorphic Encryption (FHE) allows outsourced computation on clients’ encrypted data while preserving data privacy. FHE's high computational intensity incurs high overhead from data transfer with hardware such as CPU, GPU, and FPGA, due to the inherent separation between computing and data. To overcome this limitation, Compute-Enabled RAM (CE-RAM) has been explored; however, prior work using CE-RAM to accelerate FHE only explores a simple implementation of a finite-field FHE scheme and did not explore algorithmic optimizations. In this paper, we investigate CE-RAM acceleration FHE more deeply, implementing both the finite-field B/FV and torus-based TFHE cryptosystems in CE-RAM with common FHE optimizations. This is the first work to explore using CE-RAM to accelerate TFHE. For B/FV, we explore parameter-specific algorithmic optimizations specifically designed for CE-RAM friendliness. We evaluate our implementation as compared to prior work in CE-RAM FHE acceleration and other hardware acceleration strategies. We demonstrate speedups of up to 784x for B/FV homomorphic multiplication and 38x for TFHE bootstrapping as compared to CPU implementations. We also discuss the overhead of CE-RAM for FHE on energy and area consumption, showing comparable or improved performance as compared to other work or hypothetical near-memory accelerators.