Company Filing History:
Years Active: 2011-2025
Title: Showi-Min Shen: Innovator in Data Path Technologies
Introduction
Showi-Min Shen is a notable inventor based in San Jose, CA, with a focus on advancements in data path technologies. He holds 2 patents that contribute to the field of signal processing and data synchronization.
Latest Patents
One of his latest patents is titled "Low latency phase alignment for parallel data paths." This invention involves receiver circuitry designed to mitigate the effects of phase differences between a capture clock signal and the receipt of a data signal. The circuitry includes first and second data path components, along with phase alignment circuitry that adjusts the phase of launch clock signals based on clock slip signals. This innovation enhances the reliability of data transmission in parallel processing environments.
Another significant patent is "Scalable channel bundling with adaptable channel synchronization." This patent outlines structures and methods for facilitating channel bundling. It includes signal distribution circuitry that connects registers to data channels in a bundle, allowing for efficient signal distribution and synchronization. The invention also features self-switch circuits that enable channels to switch between bundle-wide and locally generated signals, optimizing performance in data processing applications.
Career Highlights
Showi-Min Shen has worked with prominent companies in the technology sector, including Altera Corporation and Xilinx, Inc. His experience in these organizations has allowed him to develop and refine his innovative ideas in data path technologies.
Collaborations
Throughout his career, Showi-Min has collaborated with talented individuals such as Keith Duwel and Michael Menghui Zheng. These partnerships have contributed to the successful development of his patents and innovations.
Conclusion
Showi-Min Shen's contributions to data path technologies through his patents demonstrate his commitment to innovation in the field. His work continues to influence advancements in signal processing and data synchronization.