Oak Run, CA, United States of America

Gibson Dana Elliot

USPTO Granted Patents = 2 

Average Co-Inventor Count = 1.3

ph-index = 1


Company Filing History:


Years Active: 2010-2012

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2 patents (USPTO):Explore Patents

Title: Gibson Dana Elliot: Innovator in Processor Reconfiguration and Parallel Multiplication

Introduction

Gibson Dana Elliot is a notable inventor based in Oak Run, California. He has made significant contributions to the field of processor technology, holding two patents that showcase his innovative approach to dynamic reconfiguration and parallel multiplication.

Latest Patents

Elliot's latest patents include a "Method and apparatus for dynamic partial reconfiguration on an array of processors." This invention outlines a method that verifies if a processor is ready for dynamic partial reconfiguration, decides the degree of reconfiguration, and executes native machine code to modify the internal memory of a processing device. The apparatus described allows for the modification of multiple processors in an array, facilitating communication between different groups of processors without participating in their tasks.

Another significant patent is for a "Shift-add based parallel multiplication." This system performs parallel multiplication on multiple factors using a binary processor. It involves two memories that hold values for multiplication and determines the multiplier bit-count to perform operations efficiently.

Career Highlights

Gibson Dana Elliot is currently associated with VNS Portfolio LLC, where he continues to develop and refine his innovative ideas. His work focuses on enhancing the capabilities of processors, making them more efficient and versatile in handling complex tasks.

Collaborations

Elliot collaborates with Charles H Moore, a fellow innovator, to further explore advancements in processor technology and related fields.

Conclusion

Gibson Dana Elliot's contributions to the field of processor technology through his patents reflect his commitment to innovation. His work continues to influence the development of more efficient computing systems.

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