Stochastic Dynamic Thermal Management: A Markovian Decision-based Approach

This paper proposes a stochastic dynamic thermal management (DTM) technique in high-performance VLSI system with especial attention to the uncertainty in temperature observation. More specifically, we propose a stochastic thermal management framework to improve the accuracy of decision making in DTM, which performs dynamic voltage and frequency scaling to minimize total power dissipation and on-chip temperature. A key characteristic of the framework is that thermal states are controlled by stochastic processes, i.e., partially observable semi-Markov decision processes. Collaborative optimization is considered with mathematical programming formulations to reduce operating temperature by using multi-objective design optimization methods. Experimental results with 32-bit embedded RISC processor demonstrate the effectiveness of the technique and show that the proposed algorithm ensures thermal safety under performance constraints.