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For the Inventor, By the Inventor

Madison, AL, United States of America

Stewart Glenn Carlton

This inventor holds 12 USPTO granted patents. Top assignee: Nvidia Corporation. Active years: 2012-2018.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Stewart Glenn Carlton. Retrieved from https://idiyas.com/inventor/stewart-glenn-carlton

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile

USPTO Granted Patents = 12

% Patents Active = 100.0

Average Co-Inventor Count = 7.2

ph-index = 6

Forward Citations = 136(Granted Patents)


Company Filing History:

goldMedal12 out of 6,208 
 
Nvidia Corporation
 patents

Years Active: 2012-2018

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12 patents (USPTO):Explore Patents
1. 10152329 - Pre-scheduled replays of divergent operations (2018-12-11),
2. 10007527 - Uniform load processing for parallel thread sub-sets (2018-06-26),
3. 9952977 - Cache operations and policies for a multi-threaded client (2018-04-24),
4. 9817668 - Batched replays of divergent operations (2017-11-14),
5. 9678897 - Approach for context switching of lock-bit protected memory (2017-06-13),
6. 9626191 - Shaped register file reads (2017-04-18),
7. 9286256 - Sharing data crossbar for reads and writes in a data cache (2016-03-15),
8. 9262174 - Dynamic bank mode addressing for memory access (2016-02-16),
9. 8595425 - Configurable cache for multiple clients (2013-11-26),
10. 8335892 - Cache arbitration between multiple clients (2012-12-18),
11. 8266383 - Cache miss processing using a defer/replay mechanism (2012-09-11),
12. 8266382 - Cache interface protocol including arbitration and hints (2012-09-11),

Title: Stewart Glenn Carlton: Innovator in Parallel Processing Technologies

Introduction

Stewart Glenn Carlton is a prominent inventor based in Madison, Alabama, known for his significant contributions to the field of parallel processing technologies. With a total of 12 patents to his name, Carlton has made remarkable advancements that enhance the efficiency of computing systems.

Latest Patents

Among his latest patents, Carlton has developed a method for pre-scheduled replays of divergent operations. This innovation optimizes the execution of pre-scheduled replay operations in a parallel processing subsystem. The technology involves a streaming multiprocessor that utilizes a multi-stage pipeline to manage pre-scheduled replay operations effectively. By detecting whether the current instruction accesses a common resource, the system can insert necessary replay operations, thereby reducing latency for divergent operations.

Another notable patent focuses on uniform load processing for parallel thread sub-sets. This technique allows for efficient processing of load instructions when multiple threads request the same memory address. By identifying uniform access patterns, the load/store unit can minimize the number of read requests, enhancing overall system performance.

Career Highlights

Stewart Glenn Carlton is currently employed at Nvidia Corporation, a leading company in graphics processing and computing technology. His work at Nvidia has positioned him at the forefront of innovation in parallel processing, contributing to the development of advanced computing solutions.

Collaborations

Throughout his career, Carlton has collaborated with talented individuals such as Rajeshwaran Selvanesan and Steven James Heinrich. These collaborations have fostered a creative environment that encourages the exchange of ideas and the development of groundbreaking technologies.

Conclusion

Stewart Glenn Carlton's contributions to parallel processing technologies have significantly impacted the field of computing. His innovative patents and collaborative efforts at Nvidia Corporation highlight his dedication to advancing technology. Carlton's work continues to pave the way for more efficient computing systems in the future.

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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