Company Filing History:
Years Active: 2022-2023
Title: Aswathy Asok: Innovator in Graph Stream Processing
Introduction
Aswathy Asok is a prominent inventor based in Hyderabad, Telangana, India. She has made significant contributions to the field of graph stream processing, particularly in the management of registers for efficient data execution. With a total of 2 patents to her name, Aswathy is recognized for her innovative approaches in technology.
Latest Patents
Aswathy's latest patents include groundbreaking systems, apparatuses, and methods for efficient management of registers in a graph stream processing (GSP) system. One of her notable inventions is the "Single Instruction Multiple Data Execution with Variable Size Logical Registers." This patent describes a GSP system that features a thread scheduler module to initiate a SIMD thread, which includes a dispatch mask with an initial value. Additionally, it incorporates a thread arbiter module that selects instructions and provides them to compute resources, along with an instruction iterator module that determines the data type of the instruction and executes it iteratively based on the data type and dispatch mask. Another significant patent is the "Single Instruction Multiple Data (SIMD) Execution with Variable Width Registers," which shares similar functionalities and innovations aimed at enhancing the efficiency of GSP systems.
Career Highlights
Aswathy currently works at Blaize, Inc., where she continues to push the boundaries of technology in her field. Her work has garnered attention for its potential applications in various industries, making her a valuable asset to her company and the tech community.
Collaborations
Aswathy collaborates with talented individuals such as Kamaraj Thangam and Srinivasulu Nagisetty, contributing to a dynamic and innovative work environment.
Conclusion
Aswathy Asok stands out as a leading inventor in the realm of graph stream processing, with her patents reflecting her commitment to advancing technology. Her contributions are paving the way for more efficient data management systems in the future.