Woodstock, NY, United States of America

Yurly M Pogudin


Average Co-Inventor Count = 3.0

ph-index = 1

Forward Citations = 3(Granted Patents)


Company Filing History:


Years Active: 2015

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1 patent (USPTO):Explore Patents

Title: Yurly M Pogudin: Innovator in Parallelization of Pipelined Computations

Introduction

Yurly M Pogudin is a notable inventor based in Woodstock, NY (US). He has made significant contributions to the field of computing, particularly in the area of parallel processing. His innovative approach has led to the development of a unique method that enhances the efficiency of pipelined computations.

Latest Patents

Yurly holds a patent for a "Method and system for parallelization of pipelined computations." This patent describes a method of parallelizing a pipeline that includes stages operable on a sequence of work items. The method involves allocating an amount of work for each work item, assigning at least one stage to each work item, partitioning the at least one stage into at least one team, and further partitioning the at least one team into at least one gang. Additionally, it assigns the teams and gangs to processors, ensuring that they are juxtaposed near one another to minimize communication losses.

Career Highlights

Yurly M Pogudin is currently employed at Qualcomm Incorporated, a leading technology company known for its advancements in telecommunications and computing. His work at Qualcomm has allowed him to apply his innovative ideas in a practical setting, contributing to the company's reputation for cutting-edge technology.

Collaborations

Yurly has collaborated with several talented individuals in his field, including Vladimir Kotlyar and Mayan Moudgill. These collaborations have fostered an environment of innovation and creativity, leading to advancements in their respective projects.

Conclusion

Yurly M Pogudin is a distinguished inventor whose work in parallelization of pipelined computations has made a significant impact in the field of computing. His contributions continue to influence the way computational processes are optimized for efficiency.

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