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.
Original language | English |
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Article number | 9066868 |
Pages (from-to) | 2097-2111 |
Number of pages | 15 |
Journal | IEEE Transactions on Parallel and Distributed Systems |
Volume | 31 |
Issue number | 9 |
DOIs | |
Publication status | Published - 1 Sep 2020 |
Keywords
- cluster-based platform
- energy minimization
- heterogeneous platform
- Parallel task
- real-time scheduling
ASJC Scopus subject areas
- Signal Processing
- Hardware and Architecture
- Computational Theory and Mathematics