Munich, Germany

Tal Horowitz


 

Average Co-Inventor Count = 3.7

ph-index = 1


Company Filing History:


Years Active: 2019-2025

Loading Chart...
Loading Chart...
2 patents (USPTO):Explore Patents

Title: Tal Horowitz: Innovator in Multi-Thread Systolic Arrays and Big Data Applications

Introduction

Tal Horowitz is a prominent inventor based in Munich, Germany. He has made significant contributions to the fields of computer architecture and data processing. With a total of 2 patents, his work focuses on enhancing computational efficiency and data management.

Latest Patents

Horowitz's latest patents include innovative systems and methods for performing multiplication of one or more matrices using multi-thread systolic arrays. This technology involves a multi-thread systolic array that consists of multiple processing elements, each equipped with a processor. These processing elements are designed to receive inputs from various sources, schedule threads for operation cycles, and execute computation operations efficiently.

Another notable patent is for a multi-dimensional computer architecture tailored for big data applications. This data processing apparatus features a front-end interface that connects to a main processor. It is capable of determining the nature of the data—whether it is single-access or multiple-access—and routes it accordingly for optimal processing.

Career Highlights

Tal Horowitz is currently employed at Huawei Technologies Co., Limited, where he continues to push the boundaries of technology. His work is instrumental in developing advanced computing solutions that cater to the growing demands of data-intensive applications.

Collaborations

Throughout his career, Horowitz has collaborated with esteemed colleagues such as Uri Weiser and Zuguang Wu. These partnerships have fostered innovation and contributed to the success of his projects.

Conclusion

Tal Horowitz stands out as a key figure in the realm of computational technology and big data solutions. His patents reflect a commitment to advancing the efficiency of data processing and computational methods.

This text is generated by artificial intelligence and may not be accurate.
Please report any incorrect information to support@idiyas.com
Loading…