Beer Sheva, Israel

Daniel Khankin

USPTO Granted Patents = 3 

Average Co-Inventor Count = 1.0

ph-index = 1


Company Filing History:


Years Active: 2024-2025

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3 patents (USPTO):Explore Patents

Title: Innovations by Daniel Khankin

Introduction

Daniel Khankin is an accomplished inventor based in Beer Sheva, Israel. He has made significant contributions to the field of algorithm generation and computation through his innovative patents. With a total of two patents to his name, Khankin's work focuses on enhancing processing architectures and approximating elementary functions.

Latest Patents

Khankin's latest patents include "Automatic generation of processing architecture-specific algorithms" and "Automatic generation of computation kernels for approximating elementary functions." The first patent describes a method for automatically generating architecture-specific algorithms by receiving an architecture-independent algorithm and parameters that define the target processing architecture. This method involves determining the functionality of the algorithm, selecting architecture-specific computing blocks, and generating an architecture-specific code segment based on execution code. The second patent outlines an apparatus for computing functions using polynomial-based approximation. It details a process where one or more processing circuitries compute a polynomial-based approximant by executing iterations that minimize approximation errors while adhering to specific constraints.

Career Highlights

Daniel Khankin is currently associated with Next Silicon Ltd., where he applies his expertise in algorithm generation and computation. His work at the company emphasizes the development of advanced processing architectures and efficient computation methods. Khankin's innovative approach has positioned him as a key figure in the field of computational technology.

Collaborations

Due to space constraints, the collaborations section will be omitted.

Conclusion

Daniel Khankin's contributions to the field of algorithm generation and computation are noteworthy. His innovative patents reflect a commitment to advancing technology and improving processing efficiency. His work continues to influence the landscape of computational methods and architectures.

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