HMNTT: A Highly Efficient MDC-NTT Architecture for Privacy-preserving Applications
Published in The 34th edition of Great Lakes Symposium on VLSI (GLSVLSI), 2024
Recommended citation: Liu, Changxu, Danqing Tang, Jie Song, Hao Zhou, Shoumeng Yan, and Fan Yang. "HMNTT: A Highly Efficient MDC-NTT Architecture for Privacy-preserving Applications." In Proceedings of the Great Lakes Symposium on VLSI 2024, pp. 7-12. 2024. https://dl.acm.org/doi/abs/10.1145/3649476.3658734
Abstract: In privacy-preserving applications like Post-Quantum Cryptography (PQC) and Fully Homomorphic Encryption (FHE), polynomial multiplication is common, and the Number Theoretic Transform (NTT) is a key algorithm for reducing its complexity. In this paper, we present HMNTT, a highly efficient MDC-NTT architecture. Utilizing the four-step NTT algorithm and a pipelined transpose module, HMNTT offers a highly efficient and scalable architecture for handling NTT with large degrees. We optimize the processing element (PE) to alleviate backpressure and data conflicts in data flow. Leveraging FPGA characteristics, we construct a modular multiplication module to reduce resource usage and improve operating frequency. Evaluation results indicate that HMNTT achieves an average of 2.34× and 1.26× reduction in Area-Time Product compared to the latest pipelined NTT architectures.