Company Filing History:
Years Active: 2025
Title: Innovations of Gopinath Vasanth Mahale
Introduction
Gopinath Vasanth Mahale is an accomplished inventor based in Karnataka, India. He has made significant contributions to the field of neural processing units and convolutional neural networks. With a total of 2 patents to his name, Mahale is recognized for his innovative approaches to enhancing computational efficiency.
Latest Patents
Mahale's latest patents include a "Power-efficient hybrid traversal apparatus and method for convolutional neural network accelerator architecture." This invention focuses on a hybrid traversal apparatus that efficiently processes input feature maps and kernel microbatches to generate output feature maps. The method emphasizes kernel reuse to optimize performance in both direct and Winograd convolutions.
Another notable patent is the "Z-first reference neural processing unit for mapping Winograd convolution and a method thereof." This invention describes a neural processing unit that utilizes a z-first data storage layout for input feature maps. It includes various components such as a reconfigurable IFM distributor and MAC units to perform efficient dot product operations, ultimately generating intermediate output feature maps.
Career Highlights
Gopinath Vasanth Mahale is currently employed at Samsung Electronics Co., Ltd. His work at this leading technology company has allowed him to explore and develop cutting-edge technologies in the field of artificial intelligence and machine learning.
Collaborations
Throughout his career, Mahale has collaborated with talented individuals such as Pramod Parameshwara Udupa and Sehwan Lee. These collaborations have contributed to the advancement of his research and the successful development of his patents.
Conclusion
Gopinath Vasanth Mahale's innovative contributions to neural processing units and convolutional neural networks highlight his expertise and commitment to advancing technology. His patents reflect a deep understanding of computational efficiency and the potential for future developments in this field.