Stochastic modeling of a thermally-managed multi-core system

Achieving high performance under a peak temperature limit is a first-order concern for VLSI designers. This paper presents a new abstract model of a thermally-managed system, where a stochastic process model is employed to capture the system performance and thermal behavior. We formulate the problem of dynamic thermal management (DTM) as the problem of minimizing the energy cost of the system for a given level of performance under a peak temperature constraint by using a controllable Markovian decision process (MDP) model. The key rationale for utilizing MDP for solving the DTM problem is to manage the stochastic behavior of the temperature states of the system under online re-configuration of its micro-architecture and/or dynamic voltage-frequency scaling. Experimental results demonstrate the effectiveness of the modeling framework and the proposed DTM technique.