HRCIM-NTT: An Efficient Compute-in-Memory NTT Accelerator With Hybrid-Redundant Numbers

Recently, four NIST-approved Post-Quantum Cryptography (PQC) algorithms are selected to be standardized. Three of them are lattice-based cryptographic schemes and feature the number-theoretic transform (NTT) as the computing bottleneck compelling fast and low-power hardware implementations. In this work, a high-speed and power-efficient NTT accelerator is presented leveraging the compute-in-memory (CIM) technique with bottom-up optimizations. Firstly, a carry-free modular multiplication (CFMM) algorithm is proposed, which utilizes on-the-fly reduction and hybrid-redundant representation to optimize the butterfly unit operation, the cornerstone of NTT. Based on the optimized algorithm, an efficient butterfly unit in memory (BUIM) is developed by co-designing with SRAM circuit, which saves the memory access energy, decreases operation cycles, and obtains ultra-short critical path. Additionally, the data pattern of CIM array is also improved to avoid redundant memory read/write operations, which further reduces memory access overhead. Finally, a combination of pipelined operation flow and constant interstage data mapping strategy is employed to bestow the proposed hybrid-redundant CIM NTT (HRCIM-NTT) architecture with minimized computing cycles and reduced routing overhead. The implementation under 45nm CMOS technology demonstrates that HRCIM-NTT achieves the highest throughput and lowest latency among the existing CIM-based NTT accelerators.

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Publication Details

Journal
IEEE Transactions on Circuits and Systems I Regular Papers
Published
2024-09-30
DOI
https://doi.org/10.1109/tcsi.2024.3463184
Citations
4
Primary Topic
Embedded Systems Design Techniques
Type
article
Field-Weighted Citation Impact
1.96

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article

HRCIM-NTT: An Efficient Compute-in-Memory NTT Accelerator With Hybrid-Redundant Numbers

Jing Tian, Minghao Li, Zhongfeng Wang, Y Wei et al.
4 citations
IEEE Transactions on Circuits and Systems I Regular Papers
Embedded Systems Design Techniques
1.96
article

HRCIM-NTT: An Efficient Compute-in-Memory NTT Accelerator With Hybrid-Redundant Numbers

Jing Tian, Minghao Li, Zhongfeng Wang, Y Wei, Xu Zhang
article en
4 citations

Abstract

Recently, four NIST-approved Post-Quantum Cryptography (PQC) algorithms are selected to be standardized. Three of them are lattice-based cryptographic schemes and feature the number-theoretic transform (NTT) as the computing bottleneck compelling fast and low-power hardware implementations. In this work, a high-speed and power-efficient NTT accelerator is presented leveraging the compute-in-memory (CIM) technique with bottom-up optimizations. Firstly, a carry-free modular multiplication (CFMM) algorithm is proposed, which utilizes on-the-fly reduction and hybrid-redundant representation to optimize the butterfly unit operation, the cornerstone of NTT. Based on the optimized algorithm, an efficient butterfly unit in memory (BUIM) is developed by co-designing with SRAM circuit, which saves the memory access energy, decreases operation cycles, and obtains ultra-short critical path. Additionally, the data pattern of CIM array is also improved to avoid redundant memory read/write operations, which further reduces memory access overhead. Finally, a combination of pipelined operation flow and constant interstage data mapping strategy is employed to bestow the proposed hybrid-redundant CIM NTT (HRCIM-NTT) architecture with minimized computing cycles and reduced routing overhead. The implementation under 45nm CMOS technology demonstrates that HRCIM-NTT achieves the highest throughput and lowest latency among the existing CIM-based NTT accelerators.

IEEE Transactions on Circuits and Systems I Regular PapersVol. 72(1)
Nanjing University (CN)
Ant Group
Affordable and clean energy
Openalex Percentile: Top 12%
Embedded Systems Design Techniques
1.96
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HRCIM-NTT: An Efficient Compute-in-Memory NTT Accelerator With Hybrid-Redundant Numbers — Jing Tian, Minghao Li, et al. · IEEE Transactions on Circuits and Systems I Regular Papers (2024) | TGRS Research Map | TGRS