Details

Autor(en) / Beteiligte

• Azad, Zahra
• Yang, Guowei
• Agrawal, Rashmi
• Petrisko, Daniel
• Taylor, Michael
• Joshi, Ajay

Titel

RISE: RISC-V SoC for En/Decryption Acceleration on the Edge for Homomorphic Encryption

Ist Teil von

• IEEE transactions on very large scale integration (VLSI) systems, 2023-10, Vol.31 (10), p.1-14

Ort / Verlag

New York: IEEE

Erscheinungsjahr

2023

Link zum Volltext

• IEEE_Xplore

Quelle

IEEE Electronic Library (IEL)

Beschreibungen/Notizen

• Today, edge devices commonly connect to the cloud to use its storage and computing capabilities. This leads to security and privacy concerns about user data. Homomorphic encryption (HE) is a promising solution to address the data privacy problem as it allows arbitrarily complex computations on encrypted data without ever needing to decrypt it. While there has been a lot of work on accelerating HE computations in the cloud, small attention has been paid to the and conversion operations on the edge. In this work, we profile the edge-side conversion operations, and our analysis shows that during conversion error sampling, encryption and decryption operations are the bottlenecks. To overcome these bottlenecks, we present, an area and energy-efficient RISC-V system-on-chip (SoC). leverages an efficient and lightweight pseudorandom number generator (PRNG) core and combines it with fast sampling techniques to accelerate the error sampling operations. To accelerate the encryption and decryption operations, uses scalable data-level parallelism to implement the number theoretic transform (NTT) operation, the main bottleneck within the encryption and decryption operations. In addition, saves area by implementing a unified en/decryption datapath, and efficiently exploits techniques like memory reuse and data reordering to utilize a minimal amount of on-chip memory. We evaluate using a complete RTL design containing a RISC-V processor interfaced with our accelerator. Our analysis reveals that for and conversions, using leads up to <inline-formula> <tex-math notation="LaTeX">5986.99\times</tex-math> </inline-formula> and <inline-formula> <tex-math notation="LaTeX">1164.1\times</tex-math> </inline-formula> more energy-efficient solution, respectively, than when using just the RISC-V processor.