Stochastic modeling of a power-managed system - Construction and optimization

Qinru Qiu, Qing Wu, Massoud Pedram

Research output: Contribution to journalArticle

79 Scopus citations

Abstract

The goal of a dynamic power management policy is to reduce the power consumption of an electronic system by putting system components into different States, each representing a certain performance and power consumption level. The policy determines the type and timing of these transitions based on the system history, workload, and performance constraints. In this paper, we propose a new abstract model of a power-managed electronic system. We formulate the problem of system-level power management as a controlled optimization problem based on the theories of continuous-time Markov decision processes and stochastic networks. This problem is solved exactly using linear programming or heuristically using "policy iteration." Our method is compared with existing heuristic methods for different workload statistics. Experimental results show that the power management method based on a Markov decision process outperforms heuristic methods by as much as 44% in terms of power dissipation savings for a given level of system performance.

Original languageEnglish (US)
Pages (from-to)1200-1217
Number of pages18
JournalIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Volume20
Issue number10
DOIs
StatePublished - Oct 1 2001
Externally publishedYes

Keywords

  • Low-power design
  • Markov decision process
  • Policy optimization
  • Power management
  • Stochastic modeling

ASJC Scopus subject areas

  • Software
  • Computer Graphics and Computer-Aided Design
  • Electrical and Electronic Engineering

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