Dynamic power management of electronic systems
Proceedings of the 1998 IEEE/ACM international conference on Computer-aided design
Dynamic power management for non-stationary service requests
DATE '99 Proceedings of the conference on Design, automation and test in Europe
Design issues for dynamic voltage scaling
ISLPED '00 Proceedings of the 2000 international symposium on Low power electronics and design
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Power Evaluation of a Handheld Computer
IEEE Micro
Proceedings of the 40th annual Design Automation Conference
Dynamic voltage and frequency scaling based on workload decomposition
Proceedings of the 2004 international symposium on Low power electronics and design
DC-DC converter-aware power management for battery-operated embedded systems
Proceedings of the 42nd annual Design Automation Conference
Understanding voltage variations in chip multiprocessors using a distributed power-delivery network
Proceedings of the conference on Design, automation and test in Europe
Optimal selection of voltage regulator modules in a power delivery network
Proceedings of the 44th annual Design Automation Conference
Design of an efficient power delivery network in an soc to enable dynamic power management
ISLPED '07 Proceedings of the 2007 international symposium on Low power electronics and design
Battery-aware power management based on Markovian decision processes
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
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With the increasing demand for energy-efficient power delivery network (PDN) in today's electronic systems, configuring an optimal PDN that supports power management techniques, e.g., dynamic voltage scaling (DVS), has become a daunting, yet vital task. This paper describes how to model and configure such a PDN so as to minimize the total energy dissipation in DVS-enabled systems, while satisfying total PDN cost and/or power conversion efficiency constraints. The problem of configuring an energy-efficient PDN under various constraints is subsequently formulated by using a controllable Markovian decision process (MDP) model and solved optimally as a policy optimization problem. The key rationale for utilizing MDP for solving the PDN configuration problem is to manage stochastic behavior of the power mode transition times of DVS-enabled systems. Simulation results demonstrate that the proposed technique ensures energy savings, while satisfying design goals in terms of total PDN cost and its power efficiency.