Company Filing History:
Years Active: 2023-2025
Title: Minyi Guo: Innovator in Graph Computing
Introduction
Minyi Guo is a prominent inventor based in Shanghai, China. He has made significant contributions to the field of graph computing, particularly in memory management and data processing techniques. With a total of three patents to his name, Guo's work is paving the way for advancements in how large-scale graphs are managed and processed.
Latest Patents
Guo's latest patents include an "Adaptive Unified Memory Management Method and System for Large-Scale Graphs." This innovative method proposes a unified memory management policy that significantly enhances the performance of processing large graphs that exceed GPU memory capacity. By utilizing different graph algorithms based on the characteristics of graph data structures, this method improves GPU bandwidth utilization and reduces the overhead of processing page faults.
Another notable patent is the "Graph Sampling and Random Walk Acceleration Method and System on GPU." This system efficiently processes graph data by converting it into CSR format and utilizing the GPU for real-time sampling. The method enhances sampling throughput and reduces overall running time, showcasing Guo's commitment to optimizing graph data processing.
Career Highlights
Minyi Guo is affiliated with Shanghai Jiao Tong University, where he continues to contribute to research and innovation in graph computing. His work has garnered attention for its practical applications and potential to improve computational efficiency in various fields.
Collaborations
Guo collaborates with esteemed colleagues, including Chao Li and Pengyu Wang. Their combined expertise fosters a dynamic research environment that encourages innovation and the development of cutting-edge technologies.
Conclusion
Minyi Guo's contributions to graph computing through his patents and research at Shanghai Jiao Tong University highlight his role as a leading inventor in the field. His innovative methods are set to transform how large-scale graphs are managed and processed, paving the way for future advancements.