Tokyo, Japan

Tomokazu Higuchi

USPTO Granted Patents = 1 

Average Co-Inventor Count = 3.0

ph-index = 1


Company Filing History:


Years Active: 2025

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1 patent (USPTO):Explore Patents

Title: Tomokazu Higuchi: Innovator in Parallelization Techniques

Introduction

Tomokazu Higuchi is a prominent inventor based in Tokyo, Japan. He has made significant contributions to the field of computing, particularly in the area of parallelization techniques. His innovative approach has led to the development of a unique patent that addresses the complexities of data transfer in hierarchical memory systems.

Latest Patents

Higuchi holds a patent titled "Method for determining parallelization axes combination for split scheme, determining device, and computing system." This patent outlines a method for determining a split scheme by calculating data related to data transfer time for each combination of parallelization axes at various layers of a hierarchical memory computer. The method takes into account data transfer methods, problem sizes, and communication bandwidths between layers. By utilizing one or more processors, the method effectively determines the optimal combination of parallelization axes based on the calculated data.

Career Highlights

Tomokazu Higuchi is currently employed at Preferred Networks, Inc., where he continues to push the boundaries of innovation in computing. His work focuses on enhancing the efficiency of data processing through advanced parallelization techniques. With a patent portfolio that includes one significant patent, Higuchi has established himself as a key player in the field.

Collaborations

Higuchi collaborates with talented individuals such as Hiroto Imachi and Tomoya Adachi. Together, they work on various projects that aim to improve computational methods and technologies.

Conclusion

Tomokazu Higuchi's contributions to the field of computing through his innovative patent demonstrate his expertise and commitment to advancing technology. His work at Preferred Networks, Inc. continues to influence the development of efficient data processing methods.

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