Presentation
Enhancing Design Automation with AI and Quantum Algorithms for Chip Design
DescriptionThe demand for rapid, complex, and optimized chip designs for various applications requires enhancement in design automation. Although AI/ML can automate and optimize chip design processes, Quantum Algorithms have shown a significant gain in reducing area, power consumption and nodes. Quantum or quantum-inspired algorithms (QIA) can be run either on standard processors or quantum computers, showing significant gains in optimizing chip's power consumption as compared to pure AI/ML-based design approaches, even for optimizations in large solution spaces (>10500). Research on these techniques is based on the concept of making semiconductor matrix design nodes equivalent to Quantum Hamiltonians with high complexity, which are then solved using QIA to search for the lowest possible energy-level states. We use microprocessors designed on a 7nm technology node to benchmark AI/ML tools as compared to those aided by QIA. The research also demonstrates that GPU designs using QIA can experience an exponential advantage over AI/ML, as the number of nodes increases.
Event Type
Research Special Session
TimeMonday, June 235:00pm - 5:30pm PDT
Location3010, Level 3
Design