A Proposal of Fast Thermal Simulation Method For 2.5-D Advanced Packaging to Enable Efficient Thermal-Aware Placement Optimization

In this work, an efficient thermal-aware placement optimization framework is developed by combining a fast thermal simulation method with intelligent optimization algorithm. The fast thermal simulation method for 2.5-D advanced packaging is proposed by improving global stiffness matrix and load vector reconstruction process of traditional finite element method. Its performance is verified by comparing it with the traditional finite element method, the fast steady-state solver of the open-source HotSpot, and commercial software in terms of computational accuracy and efficiency. Then, an improved genetic algorithm, the elite immigrant primal-dual genetic algorithm is developed for effective placement optimization. By combining the fast thermal simulation method with the elite immigrant primal-dual genetic algorithm, the efficient thermal-aware placement framework for 2.5-D advanced packaging is established. The performance of the proposed optimization framework is then evaluated through several cases studies, including comparisons with optimization frameworks with other intelligent algorithms in terms of effective layout area, maximum temperature, temperature uniformity, and total wirelength. Additionally, its time efficiency is compared with frameworks based on other thermal simulation methods.