Company Filing History:
Years Active: 2020-2023
Title: Pradeep Janedula: Innovator in Machine Learning Acceleration
Introduction
Pradeep Janedula is a prominent inventor based in Bengaluru, India. He has made significant contributions to the field of machine learning through his innovative patents. With a total of 5 patents, Janedula is recognized for his advancements in hardware architecture that enhance the performance of machine learning accelerators.
Latest Patents
One of his latest patents is titled "Mechanism to perform non-linear functions in a machine learning accelerator." This invention discloses an apparatus that facilitates the execution of non-linear function operations. The apparatus includes accelerator circuitry with a compute grid comprising multiple processing elements. These elements execute neural network computations, store resulting values, and perform piecewise linear approximations of non-linear functions using the stored values as input data.
Another notable patent is "Efficient hardware architecture for accelerating grouped convolutions." This patent describes hardware accelerators designed for grouped convolution operations. The architecture includes a first buffer that receives a row of an input feature map from memory. A first group of tiles processes this row, while a second buffer handles additional rows, allowing for efficient computation of output feature maps based on the input data and kernels.
Career Highlights
Pradeep Janedula is currently employed at Intel Corporation, where he continues to push the boundaries of technology in machine learning. His work focuses on developing innovative solutions that improve the efficiency and effectiveness of machine learning applications.
Collaborations
Janedula collaborates with talented individuals such as Bharat Daga and Aravind Babu Srinivasan. Together, they contribute to the advancement of technology in their respective fields.
Conclusion
Pradeep Janedula is a key figure in the realm of machine learning innovation. His patents reflect a deep understanding of hardware architecture and its application in accelerating machine learning processes. His contributions are paving the way for future advancements in this critical area of technology.