RACE: RISC-V SoC for En/decryption Acceleration on the Edge for Homomorphic Computation
Zahra Azad, Guowei Yang, Rashmi Agrawal, Daniel Petrisko, Michael Bedford Taylor, Ajay M. Joshi · 2022
As more and more edge devices connect to the cloud to use its storage and compute capabilities, they bring in security and data privacy concerns. Homomorphic Encryption (HE) is a promising solution to maintain data privacy by enabling computations on the encrypted user data in the cloud. While there has been a lot of work on accelerating HE computation in the cloud, little attention has been paid to optimize the en/decryption on the edge. Therefore, in this paper, we present RACE, a custom-designed area- and energy-efficient SoC for en/decryption of data for HE. Owing to similar operations in en/decryption, RACE unifies the en/decryption datapath to save area. RACE efficiently exploits techniques like memory reuse and data reordering to utilize minimal amount of on-chip memory. We evaluate RACE using a complete RTL design containing a RISC-V processor and our unified accelerator. Our analysis shows that, for the end-to-end en/decryption, using RACE leads to, on average, 48 × to 39729 × (for a wide range of security parameters) more energy-efficient solution than purely using a processor.