A Lightweight and Hardware-Efficient NTT FPGA Accelerator for FHE Applications
Bibliographic record
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".