Policy optimization for dynamic power management

• Published in: DAC 98: DAC: 35th Annual ACM/IEEE Design Automation Conference pp. 182 - 187
• Main Authors: Paleologo, G. A., Benini, L., Bogliolo, A., De Micheli, G.
• Format: Conference Proceeding
• Language: English
• Published: New York, NY, USA ACM 01.05.1998; IEEE
• Series: ACM Conferences
• Subjects: Applied computing > Physical sciences and engineering > Electronics; Applied computing > Physical sciences and engineering > Engineering; Computing methodologies > Modeling and simulation; Constraint optimization; Consumer electronics; Design automation; Energy consumption; Energy management; Home appliances; Mathematics of computing > Probability and statistics > Stochastic processes; Permission; Portable computers; Power system management; Power system modeling; functional simulation; reconstruction; visibility; emulation
• ISBN: 0897919645; 9780897919647
• DOI: 10.1145/277044.277094

Dynamic power management schemes (also called policies) can be used to control the power consumption levels of electronic systems, by setting their components in different states, each characterized by a performance level and a power consumption. In this paper, we describe power-managed systems using a finite-state, stochastic model. Furthermore, we show that the fundamental problem of finding an optimal policy which maximizes the average performance level of a system, subject to a constraint on the power consumption, can be formulated as a stochastic optimization problem called policy optimization. Policy optimization can be solved exactly in polynomial time (in the number of states of the model). We implemented a policy optimization tool and tested the quality of the optimal policies on a realistic case study.