Minimizing energy consumption for linear speedup parallel real-time tasks

Yu Han Lin, Fan Xin Kong, Hui Ting Xu, Xi Jin, Qing Xu Deng

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Energy-efficiency is one of the most important design goals for embedded real-time systems. While much work has addressed the problem for sequential tasks where each task can run on only one processor at a time, little work has been done for parallel tasks where an individual task can be executed by multiple processors simultaneously. In this paper, we study the energy minimization problem for parallel task systems with discrete operation modes and under timing constraints. We focus on a system with DVS (Dynamic Voltage Scaling) enabled processors and workload satisfying linear speedup ratio model. We first prove a lemma, a sufficient condition for minimizing the system energy, which indicates that the overall system energy is minimized when each task runs on all of the processors simultaneously. Then, adopting the earliest deadline first (EDF) scheduling policy and the lemma proved, we employ a 0-1 Integer Linear Program (0-1 ILP) to derive the optimized frequency assignment with minimized energy consumption. Furthermore, two polynomial-time complexity heuristics with opposite frequency assignment searching directions are also proposed. The simulation experiment results show that the proposed heuristics can significantly reduce the system energy consumption and consume nearly the same energy as does 0-1 ILPs.

Original languageEnglish (US)
Pages (from-to)384-392
Number of pages9
JournalJisuanji Xuebao/Chinese Journal of Computers
Volume36
Issue number2
DOIs
StatePublished - Feb 1 2013
Externally publishedYes

Keywords

  • Dynamic voltage scaling
  • Energy minimization
  • Multi-cores
  • Parallel tasks
  • Real-time systems

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Networks and Communications
  • Computer Graphics and Computer-Aided Design

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