Composable thermal modeling and characterization for fast temperature estimation

TL;DR: In this article, a new thermal compact modeling technique for fast thermal analysis in the context of multi-core microprocessors design is proposed, which builds the models from detailed thermal structures for each core using finite difference method and reduces the model complexity by sampling-based model order reduction and circuit realization techniques.

Abstract: Efficient temperature estimation is critical for designing thermal efficient, low power and robust integrated circuits in nanometer regime. Thermal simulation starts from the detailed thermal structures by solving thermal diffusion equations no longer meets demanding tasks for efficient design space exploration. Compact and composable model-based simulation provides a viable solution to this difficult problem. However, building such thermal models from detailed thermal structures was not well addressed in the past. In this paper, we propose a new thermal compact modeling techniques for fast thermal analysis in the context of multi-core microprocessors design. The new approach builds the models from detailed structures for each core using finite difference method and reduces the model complexity by sampling-based model order reduction and circuit realization techniques. To improve the reduction efficiency, number of ports of thermal models are first reduced by port merging, which actually leads to coarse grids at the boundaries. The resulting thermal circuits can be simulated by general circuit simulator SPICE. Experimental results on a quad-core microprocessor architecture show that the new approach can easily build accurate thermal systems from the composite compact models. The new thermal systems lead to order of magnitude speedup over standard finite difference models in transient thermal simulation.