IEEE Transactions on Very Large Scale Integration (VLSI) Systems
A predictive system shutdown method for energy saving of event-driven computation
ICCAD '97 Proceedings of the 1997 IEEE/ACM international conference on Computer-aided design
Dynamic Power Management for Nonstationary Service Requests
IEEE Transactions on Computers
Proceedings of the 40th annual Design Automation Conference
Online strategies for dynamic power management in systems with multiple power-saving states
ACM Transactions on Embedded Computing Systems (TECS)
Hierarchical Adaptive Dynamic Power Management
Proceedings of the conference on Design, automation and test in Europe - Volume 1
Joint Power Management of Memory and Disk
Proceedings of the conference on Design, Automation and Test in Europe - Volume 1
Policy optimization for dynamic power management
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Stochastic modeling of a power-managed system-construction and optimization
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Stochastic modeling and optimization for robust power management in a partially observable system
Proceedings of the conference on Design, automation and test in Europe
Analysis of multi-domain scenarios for optimized dynamic power management strategies
DATE '12 Proceedings of the Conference on Design, Automation and Test in Europe
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This paper presents a timeout-driven DPM technique which relies on the theory of Markovian processes. The objective is to determine the energy-optimal timeout values for a system with multiple power saving states while satisfying a set of user defined performance constraints. More precisely, a controllable Markovian process is exploited to model the power management behavior of a system under the control of a timeout policy. Starting with this model, a perturbation analysis technique is applied to develop an offline gradient-based approach to determine the optimal timeout values. Online implementation of this technique for a system with dynamically-varying system parameters is also described. Experimental results demonstrate the effectiveness of the proposed approach. Introduction