Energy-Efficient Parallel Real-Time Scheduling on Clustered Multi-Core

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

6 Scopus Citations
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Author(s)

  • Ashikahmed Bhuiyan
  • Di Liu
  • Aamir Khan
  • Abusayeed Saifullah
  • Zhishan Guo

Detail(s)

Original languageEnglish
Article number9066868
Pages (from-to)2097-2111
Journal / PublicationIEEE Transactions on Parallel and Distributed Systems
Volume31
Issue number9
Online published14 Apr 2020
Publication statusPublished - Sep 2020
Externally publishedYes

Abstract

Energy-efficiency is a critical requirement for computation-intensive real-time applications on multi-core embedded systems. Multi-core processors enable intra-task parallelism, and in this work, we study energy-efficient real-time scheduling of constrained deadline sporadic parallel tasks, where each task is represented as a directed acyclic graph (DAG). We consider a clustered multi-core platform where processors within the same cluster run at the same speed at any given time. A new concept named speed-profile is proposed to model per-task and per-cluster energy-consumption variations during run-time to minimize the expected long-term energy consumption. To our knowledge, no existing work considers energy-aware real-time scheduling of DAG tasks with constrained deadlines, nor on a clustered multi-core platform. The proposed energy-aware real-time scheduler is implemented upon an ODROID XU-3 board to evaluate and demonstrate its feasibility and practicality. To complement our system experiments in large-scale, we have also conducted simulations that demonstrate a CPU energy saving of up to 67 percent through our proposed approach compared to existing methods.

Research Area(s)

  • cluster-based platform, energy minimization, heterogeneous platform, Parallel task, real-time scheduling

Citation Format(s)

Energy-Efficient Parallel Real-Time Scheduling on Clustered Multi-Core. / Bhuiyan, Ashikahmed; Liu, Di; Khan, Aamir; Saifullah, Abusayeed; Guan, Nan; Guo, Zhishan.

In: IEEE Transactions on Parallel and Distributed Systems, Vol. 31, No. 9, 9066868, 09.2020, p. 2097-2111.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review