Shuguo Li
Tsinghua University
28 Papers
60 Citations
Shuguo Li is an academic researcher from Tsinghua University. The author has contributed to research in topics: Computer science & Modular arithmetic. The author has an hindex of 8, co-authored 26 publications.
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Papers
High-Speed ECC Processor Over NIST Prime Fields Applied With Toom–Cook Multiplication
Jinnan Ding,Shuguo Li,Zhen Gu +2 more
TL;DR: A high-speed elliptic curve cryptography (ECC) processor specialized for primes recommended by the National Institute of Standards and Technology (NIST) was constructed and introduced non-least-positive (NLP) form into the design, so that the carry chain in the large array accumulation was broken down, which greatly shortened the critical path and made parallel processing possible.
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An Efficient Implementation of the NewHope Key Exchange on FPGAs
Yufei Xing,Shuguo Li +1 more
TL;DR: This work proposes an efficient implementation of NewHope on Xilinx Artix-7 7020 FPGA platform that consumes 3158 slices, 10285 LUTs, 6623 registers in the server side, and 3042 slices, 10345 LUTing in the client side, achieving a 45% reduction in LUT, 30% reductionIn FF while the total time utilization also decreases by 16% compared with the up to date and directly related work.
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A Division-Free Toom–Cook Multiplication-Based Montgomery Modular Multiplication
TL;DR: This brief proposes a method of division-free Toom–Cook multiplication based Montgomery modular multiplication, which makes it possible for Toom-Cook multiplication to be applied in practical and efficient hardware implementations.
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RLWE-Oriented High-Speed Polynomial Multiplier Utilizing Multi-Lane Stockham NTT Algorithm
Xiang Feng,Shuguo Li,Sufen Xu +2 more
TL;DR: This brief presents a novel polynomial multiplier based on Stockham fast Fourier transform (FFT) algorithm, which can achieve a speed up factor of no less than 2.7 times compared with the state of art designs.
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A Low-Latency and Low-Cost Montgomery Modular Multiplier Based on NLP Multiplication
Jinnan Ding,Shuguo Li +1 more
TL;DR: A non-least positive form (NLP) based modular multiplication method that combines Karatsuba and schoolbook multiplication is applied in Montgomery modular multiplication, which saves 2 base multiplications compared toKaratsuba-only designs and allows pipeline structure to make most use of the parallelism in large modular multiplications.
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