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L2M – Reinforcement-Learning-Driven Electronic Design Automation (EDA) for Optimal Layout Placement
Reinforcement Learning (RL) driven Electronic Design Automation (EDA) is revolutionizing layout placement optimization for integrated circuits, enabling a faster design process. By incorporating the RL techniques, we enhance the historically precise yet labor-intensive process for smart integrated circuit (IC) fabrication. This innovative approach streamlines IC design, accounting for factors such as foggy and proximity effects, promoting both efficiency and accuracy in the layout placement design.
Faculty Supervisor:
Lihong Zhang;Octavia Dobre
Student:
Partner:
Springboard Atlantic Inc.
Discipline:
Engineering
Sector:
Artificial Intelligence; Technology
University:
Memorial University of Newfoundland
Program:
Business Strategy Internship
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