Scalable Power Management for On-Chip Systems with Malleable Applications

Muhammad Shafique, Anton Ivanov, Benjamin Vogel, Jorg Henkel

Research output: Contribution to journalArticlepeer-review

Abstract

We present a scalable Dynamic Power Management (DPM) schem e where malleable applications may change their degree of parallelism at run time depending upon the workload and performance constraints. We employ a per-application predictive power manager that autonomously controls the power states of the cores with the goal of energy efficiency. Furthermore, our DPM allows the applications to lend their idle cores for a short time period to expedite other critical applications. In this way, it allows for application-level scalability, while aiming at the overall system energy optimization. Compared to state-of-the-art centralized and distributed power management approaches, we achieve up to 58 percent (average ≈ 15-20 percent) ED2P reduction.

Original languageEnglish (US)
Article number7430334
Pages (from-to)3398-3412
Number of pages15
JournalIEEE Transactions on Computers
Volume65
Issue number11
DOIs
StatePublished - Nov 1 2016

Keywords

  • energy efficiency
  • low power
  • malleable applications
  • manycore
  • Power management
  • scalability
  • self-adaptation

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Hardware and Architecture
  • Computational Theory and Mathematics

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