Zhejiang, China

Jie Lv


Average Co-Inventor Count = 1.0

ph-index = 1


Company Filing History:


Years Active: 2025

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1 patent (USPTO):Explore Patents

Title: Innovations of Jie Lv in Parallel Multiplication for the Saber Algorithm

Introduction

Jie Lv is an accomplished inventor based in Zhejiang, China. He has made significant contributions to the field of computing, particularly in the development of efficient algorithms. His innovative work focuses on enhancing the performance of the Saber algorithm through advanced hardware solutions.

Latest Patents

Jie Lv holds a patent for a "Parallel multiplier for Saber algorithm." This invention comprises a coefficient memory, two parallel pre-adding circuits, three parallel multiplication circuits, and a post-adding circuit. The design employs a divide-and-conquer strategy, allowing for parallel computation that significantly reduces the computation time of modulo multiplication. By limiting the bit width, the invention avoids the constraint that the modulus must be a prime number. Additionally, the use of the Karatsuba algorithm minimizes extra circuit area expenditure. Overall, this parallel multiplier is characterized by low computation complexity and efficient hardware implementation.

Career Highlights

Jie Lv is affiliated with Wenzhou University, where he continues to advance his research and development efforts. His work has garnered attention for its practical applications in modern computing technologies. With a focus on algorithm optimization, Jie has positioned himself as a key figure in the field.

Collaborations

Jie has collaborated with notable colleagues, including Pengjun Wang and Bo Chen. Their combined expertise has contributed to the successful development of innovative solutions in their respective areas of research.

Conclusion

Jie Lv's contributions to the field of computing, particularly through his patent on the parallel multiplier for the Saber algorithm, showcase his innovative spirit and dedication to advancing technology. His work not only enhances computational efficiency but also opens new avenues for future research and development.

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