Affiliation:
1. Department of Electrical Engineering, National Quemoy University, Kinmen 89250, Taiwan
Abstract
A multi-modulus architecture based on the radix-8 Booth encoding of a modulo (2n − 1) multiplier, a modulo (2n) multiplier, and a modulo (2n + 1) multiplier is proposed in this paper. It uses the original single circuit and shares many common circuit characteristics with a small extra circuit to carry out multi-modulus operations. Compared with a previous radix-4 study, the radix-8 architecture can increase the modulation multiplication encoding selection from three codes to four codes. This reduces the use of partial products from ⌊n/2⌋ to ⌊n/3⌋ + 1, but it increases the operation complexity for multiplication by three circuits. A hard multiple generator (HMG) is used to address this problem. Two judgment signals in the multi-modulus circuit can be used to perform three operations of the modulo (2n − 1) multiplier, modulo (2n) multiplier, and modulo (2n + 1) multiplier at the same time. The weighted representation is used to reduce the number of partial products. Compared with previously reported methods in the literature, the proposed approach can achieve better performance by being more area-efficient, being faster, consuming low power, and having a lower area-delay product (ADP) and power-delay product (PDP). With the multi-modulus HMG, the proposed modified architecture can save 34.48–55.23% of hardware area. Compared with previous studies on the multi-modulus multiplier, the proposed architecture can save 22.78–35.46%, 4.12–11.15%, 12.59–24.73%, 27.88–38.88%, and 20.49–27.85% of hardware area, delay time, dissipation power, ADP, and PDP, respectively. Xilinx field programmable gate array (FPGA) Vivado 2019.2 tools and the Verilog hardware description language are used for synthesis and implementation. The Xilinx Artix-7 XC7A35T-CSG324-1 chipset is adopted to evaluate the performance.
Reference26 articles.
1. Ma, S., Hu, S., Yang, Z., Wang, X., Liu, M., and Hu, J. (2021). High Precision Multiplier for RNS {2n − 1, 2n, 2n + 1}. Electronics, 10.
2. Residue arithmetic systems in cryptography: A survey on modern security applications;Schoinianakis;J. Cryptogr. Eng.,2020
3. RNS-enabled Digital Signal Processor Design;Ramirez;Electron. Lett.,2002
4. Kalmykov, I.A., Pashintsev, V.P., Tyncherov, K.T., Olenev, A.A., and Chistousov, N.K. (2022). Error-Correction Coding Using Polynomial Residue Number System. Appl. Sci., 12.
5. Juang, T.-B., and Huang, J.-H. (2012, January 2–5). Multifunction RNS modulo (2n ± 1) Multipliers Based on Modified Booth Encoding. Proceedings of the 2012 IEEE Asia Pacific Conference on Circuits and Systems, Kaohsiung, Taiwan.