Fast Thermal

Fast thermal analysis is crucial for designing energy-efficient and high-performance electronic systems, particularly in complex architectures like 3D-integrated circuits and chiplet-based systems. Current research focuses on developing machine learning models, such as neural networks and reinforcement learning algorithms, to significantly accelerate thermal simulations, often achieving speedups of several orders of magnitude compared to traditional methods like finite element analysis. These advancements enable faster design exploration and optimization, addressing critical thermal constraints in high-density electronics and improving the efficiency of design processes. The resulting improvements in accuracy and speed are impacting various fields, from optimizing chip design to aiding in medical imaging analysis of brain tumors.