Hybrid Quantum-Classical Reinforcement Learning Enabled Thermal-Aware Electronic Design Automation Framework for Energy-Efficient Next-Generation VLSI Systems Applications
Modern Very Large-Scale Integration (VLSI) systems are becoming more complicated, which has increased need for sophisticated Electronic Design Automation (EDA) frameworks that can concurrently optimise thermal behaviour, power consumption, and performance.
Hybrid Quantum-Classical Computing; Reinforcement Learning; Electronic Design Automation (EDA); Thermal-Aware Optimization; VLSI Systems; Energy Efficiency; Chip Thermal Management; Quantum-Inspired Optimization; Semiconductor Design; Intelligent CAD Systems.