A Lightweight and Hardware-Efficient NTT FPGA Accelerator for FHE Applications

The Number Theoretic Transform (NTT) and its inverse (INTT) are pivotal operations in Fully Homomorphic Encryption (FHE) schemes to facilitate efficient polynomial multiplication over modular rings. We propose a compact and hardware-efficient NTT/INTT architecture for FHE systems with a novel twiddle factor generator (TFG) for Radix-2 multi-path delay commutator (MDC) designs, saving up to 97.2% of on-chip memory by storing the twiddle factors (TF) for the initial 11 stages (for log<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub>(<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">N</i>) = 15 to 17) and only the TF bases for on-the-fly generation in the remaining stages. DSP-efficient multipliers via non-standard tiling are designed to reduce DSP utilization as compared to standard tiling, without sacrificing performance. Benchmarking on comparable Xilinx FPGAs reveals that our design is the most compact, along with a significant efficiency advantage with up to 2.72× reduction in average area-time product (ATP) and up to 2.57× increase in throughput-per-equivalent-LUT (TPE) compared to state-of-the-art NTT designs. In various configurations, the architecture maintains lower BRAM and DSP utilization, and better overall efficiency, making it a scalable and efficient solution for real-world FHE deployments.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Circuits & Systems II Express Briefs
Published
2025-11-14
DOI
https://doi.org/10.1109/tcsii.2025.3633181
Primary Topic
Cryptography and Residue Arithmetic
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Lightweight and Hardware-Efficient NTT FPGA Accelerator for FHE Applications

Ayesha Khalid, Máire O׳Neill, Waqar Ahmad, Muhammad Rafiq Khan et al.
IEEE Transactions on Circuits & Systems II Express Briefs
Cryptography and Residue Arithmetic
article

A Lightweight and Hardware-Efficient NTT FPGA Accelerator for FHE Applications

Ayesha Khalid, Máire O׳Neill, Waqar Ahmad, Muhammad Rafiq Khan, M. Zaman
article en

Abstract

The Number Theoretic Transform (NTT) and its inverse (INTT) are pivotal operations in Fully Homomorphic Encryption (FHE) schemes to facilitate efficient polynomial multiplication over modular rings. We propose a compact and hardware-efficient NTT/INTT architecture for FHE systems with a novel twiddle factor generator (TFG) for Radix-2 multi-path delay commutator (MDC) designs, saving up to 97.2% of on-chip memory by storing the twiddle factors (TF) for the initial 11 stages (for log<sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub>(<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">N</i>) = 15 to 17) and only the TF bases for on-the-fly generation in the remaining stages. DSP-efficient multipliers via non-standard tiling are designed to reduce DSP utilization as compared to standard tiling, without sacrificing performance. Benchmarking on comparable Xilinx FPGAs reveals that our design is the most compact, along with a significant efficiency advantage with up to 2.72× reduction in average area-time product (ATP) and up to 2.57× increase in throughput-per-equivalent-LUT (TPE) compared to state-of-the-art NTT designs. In various configurations, the architecture maintains lower BRAM and DSP utilization, and better overall efficiency, making it a scalable and efficient solution for real-world FHE deployments.

IEEE Transactions on Circuits & Systems II Express BriefsVol. 73(1)
Queen's University Belfast (GB), Ghulam Ishaq Khan Institute of Engineering Sciences and Technology (PK), National University of Sciences and Technology (PK)
Queen's University Belfast, Queen's University, Engineering and Physical Sciences Research Council
Openalex Percentile: Top 52%
Cryptography and Residue Arithmetic
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.