Company Filing History:
Years Active: 2014-2024
Title: **Innovator Spotlight: Gurvinder Singh Chhabra**
Introduction
Gurvinder Singh Chhabra is a prominent inventor based in San Diego, California, known for his contributions to technology through his impressive portfolio of 19 patents. His innovative work primarily focuses on optimizing memory systems in processing technologies.
Latest Patents
One of Chhabra's latest patents is titled "Priority-based cache-line fitting in compressed memory systems of processor-based systems." This invention outlines a compressed memory system that utilizes a memory partitioning circuit to allocate a memory region into data areas with varying priority levels. The system features a cache line selection circuit designed to choose cache lines from both high and low priority data regions. Additionally, it incorporates a compression circuit to compact these cache lines, allowing for efficient packing of data. This invention is pivotal for enhancing the performance of processor-based systems by ensuring that high-priority data is managed effectively amid varying levels of data importance.
Career Highlights
Chhabra currently holds a significant position at Qualcomm Incorporated, a leading tech company widely recognized for its innovations in mobile technology and telecommunications. His extensive work in memory system optimization has positioned him as a key contributor to advancements in the field.
Collaborations
Throughout his career, Chhabra has worked alongside talented professionals, including Nieyan Geng and Richard Senior. Their collaborative efforts have spurred innovation that enhances the functionality of modern memory systems, showcasing the importance of teamwork in the realm of invention.
Conclusion
Gurvinder Singh Chhabra exemplifies the spirit of innovation that drives the tech industry forward. His developments and patents significantly contribute to the efficiency of processing systems, establishing him as an influential figure in modern technology. As industries continue to evolve, his work serves as a cornerstone for future advancements in memory system optimization.