UC Riverside

In this paper, we propose a new behavioral thermal modeling technique for high-performance microprocessors at package level. Firstly, the new approach applies the subspace identification method with the consideration of practical power maps with correlated power signals. We show that the input power signal needs to meet an independence requirement to ensure the model predictability and propose an iterative process to build the models with given error bounds. Secondly, we show that thermal systems fundamentally are nonlinear and then propose a piecewise linear (PWL) scheme to deal with nonlinear effects. The experimental results validated the proposed method on a realistic packaged integrated system modeled by the multi-domain/physics commercial tool, COMSOL. The new piecewise linear models can model thermal behaviors over wide temperature ranges or over different thermal boundary convective conditions due to different fan speeds. Further, the PWL modeling technique can lead to much smaller model order without accuracy loss, which translates to significant savings in both the simulation time and the time required to identify the reduced models compared to the simple modeling method by using the high order models. © 2013 Elsevier B.V. All rights reserved.