BP-NTT: Fast and Compact in-SRAM Number Theoretic Transform with Bit-Parallel Modular Multiplication
Jingyao Zhang, Mohsen Imani, Elaheh Sadredini
Abstract
Number Theoretic Transform (NTT) is an essential mathematical tool for computing polynomial multiplication in promising lattice-based cryptography. However, costly division operations and complex data dependencies make efficient and flexible hardware design to be challenging, especially on resource-constrained edge devices. Existing approaches either focus on only limited parameter settings or impose substantial hardware overhead. In this paper, we introduce a hardware-algorithm methodology to efficiently accelerate NTT in various settings using in-cache computing. By leveraging an optimized bit-parallel modular multiplication and introducing costless shift operations, our proposed solution provides up to 29× higher throughput-per-area and 10-138× better throughput-per-power compared to the state-of-the-art.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext 92b9573d-8266-4bd4-b28d-e558c9907294Cited by top-tier papers3
- : On-Device Real-Time Deep Reinforcement Learning for Autonomous RoboticsZexin Li, Aritra Samanta, Yufei Li, Andrea Soltoggio et al.RTSS 2023 · 9 citations
- ModSRAM: Algorithm-Hardware Co-Design for Large Number Modular Multiplication in SRAMJonathan Hao-Cheng Ku, Junyao Zhang, Haoxuan Shan, Saichand Samudrala et al.DAC 2024 · 1 citation
- Enabling Low-Cost Secure Computing on Untrusted In-Memory ArchitecturesSahar Ghoflsaz Ghinani, Jingyao Zhang, Elaheh SadrediniUSENIX Security 2025
Builds on2
- CryptoPIM: In-memory Acceleration for Lattice-based Cryptographic HardwareHamid Nejatollahi, Saransh Gupta, Mohsen Imani, Tajana Simunic Rosing et al.DAC 2020 · 63 citations
- Infinity Stream: Portable and Programmer-Friendly In-/Near-Memory FusionZhengrong Wang, Christopher Liu, Aman Arora, Lizy Kurian John et al.ASPLOS 2023 · 20 citations
Related papers
- An NTT/INTT Accelerator with Ultra-High Throughput and Area Efficiency for FHEZhaojun Lu, Weizong Yu, Peng Xu, Wei Wang et al.DAC 2024 · 3 citations
- Exploring the Advantages and Challenges of Fermat NTT in FHE AccelerationAndrey Kim, Ahmet Can Mert, Anisha Mukherjee, Aikata et al.CRYPTO 2024 · 5 citations
- A scalable SIMD RISC-V based processor with customized vector extensions for CRYSTALS-kyberHuimin Li, Nele Mentens, Stjepan PicekDAC 2022 · 13 citations
- Efficient access scheme for multi-bank based NTT architecture through conflict graphXiangren Chen, Bohan Yang, Yong Lu, Shouyi Yin et al.DAC 2022 · 12 citations
- An Efficient and Scalable Hardware Architecture for Number Theoretic Transform on FPGA with Design AutomationYilan Zhu, Geng Yang, Xingyu Tian, Dilshan Kumarathunga et al.HPCA 2026 · 1 citation
