LAUSR

Number theoretic transform (NTT) method shows great advantages in speed and efficiency for applications such as homomorphic encryption. However, the twiddle factor data consumes a lot of memories. In this brief, we propose a novel data compression method, together with the corresponding data storage scheme and addressing algorithm. Furthermore, we design a 768k-bit multiplier with a full pipeline structure. Our proposed compression method has achieved a compression rate of 98.8% for the twiddle factor data. Compared with the state-of-the-art FPGA implementations, our design shows up to 44.2% improvement in terms of area-efficiency.