San Diego, CA, United States of America

Coleman C Cheung


Average Co-Inventor Count = 2.0

ph-index = 1

Forward Citations = 6(Granted Patents)


Company Filing History:


Years Active: 2014

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1 patent (USPTO):Explore Patents

Title: The Innovative Mind of Coleman C. Cheung

Introduction

Coleman C. Cheung is a notable inventor based in San Diego, CA. He has made significant contributions to the field of dataflow techniques, particularly in the area of matrix decomposition. His innovative approach has led to the development of efficient and scalable circuitry that enhances computational processes.

Latest Patents

Coleman holds a patent for "Matrix decomposition using dataflow techniques." This invention focuses on efficient and scalable circuitry for performing Cholesky decomposition. The design is based on a dataflow style architecture that utilizes self-timed circuitry, eliminating the need for complicated state machines. The calculations are ordered to create partial sums of products in parallel, adhering to data dependency requirements. This allows a single accumulator to perform the summation effectively. A Vector FIFO receives partial sums from a vector processing engine, while a Feedback FIFO stores and feeds partial results back to the data path based on signals from a dataflow controller. The flexibility of this circuitry accommodates different matrix sizes, speed grades, and target frequencies without the need for recompilation. Coleman has 1 patent to his name.

Career Highlights

Coleman is currently employed at Altera Corporation, where he continues to push the boundaries of innovation in circuitry design. His work has been instrumental in advancing the capabilities of data processing technologies.

Collaborations

Coleman collaborates with Steven Perry, leveraging their combined expertise to drive forward innovative projects within their field.

Conclusion

Coleman C. Cheung exemplifies the spirit of innovation through his groundbreaking work in matrix decomposition and dataflow techniques. His contributions are paving the way for more efficient computational methods in technology.

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