Policy optimization for dynamic power management

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 usin...

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Bibliographic Details
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
Online Access:Get full text
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Summary: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.
Bibliography:SourceType-Conference Papers & Proceedings-1
ObjectType-Conference Paper-1
content type line 25
ISBN:0897919645
9780897919647
DOI:10.1145/277044.277094