Architecture-level thermal behavioral models for quad-core microprocessors

In this paper, we study a new architecture level thermal modeling problem from behavioral modeling perspective to address the emerging thermal related analysis and optimization problems for high-performance quad-core microprocessor designs. We propose a new approach to build the thermal behavioral models by using transfer function matrix from the measured thermal and power information at the architecture level. The new method builds behavioral thermal model using generalized pencil-of-function (GPOF) method, which was developed in the communication community to build the rational modeling from the measured data of real-time systems. To effectively model transient temperature changes, we propose two new schemes to improve the GPOF. First we apply logarithmic-scale sampling instead of traditional linear sampling to better capture the temperature changing characteristics. Second, we modify the extracted thermal impulse response such that the extracted poles from GPOF are guaranteed to be stable without accuracy loss. Experimental results on a practical quad-core microprocessor show that generated thermal behavioral models match the measured data very well.