Presentation
Accelerating IC Thermal Simulation Data Generation via Block Krylov and Operator Action
DescriptionRecent advances in data-driven approaches, such as Neural Operator (NO), have shown substantial efficacy in reducing the solution time for integrated circuit (IC) thermal simulations. However, a limitation of these approaches is requiring a large amount of high-fidelity training data, such as chip parameters and temperature distributions, thereby incurring significant computational costs. To address this challenge, we propose a novel algorithm for the generation of IC thermal simulation data, named block Krylov and operator action (BlocKOA), which simultaneously accelerates the data generation process and enhances the precision of generated data. BlocKOA is specifically designed for IC applications. Initially, we use the block Krylov algorithm based on the structure of the heat equation to quickly obtain a few basic solutions. Then we combine them to get numerous temperature distributions.
Finally, we apply heat operators on these functions to determine the heat source distributions, efficiently generating precise data points. Theoretical analysis shows that the time complexity of BlocKOA method is one order lower than direct solution methods. Experimental results further validate its efficiency, showing that BlocKOA accelerates the generation of datasets with 5000 instances by a factor of 420.
Finally, we apply heat operators on these functions to determine the heat source distributions, efficiently generating precise data points. Theoretical analysis shows that the time complexity of BlocKOA method is one order lower than direct solution methods. Experimental results further validate its efficiency, showing that BlocKOA accelerates the generation of datasets with 5000 instances by a factor of 420.
Event Type
Networking
Work-in-Progress Poster
TimeMonday, June 236:00pm - 7:00pm PDT
LocationLevel 2 Lobby