Scheduling Multiprocessor Tasks to Minimize Schedule Length
IEEE Transactions on Computers
Measuring Parallelism in Computation-Intensive Scientific/Engineering Applications
IEEE Transactions on Computers
Speedup Versus Efficiency in Parallel Systems
IEEE Transactions on Computers
The Processor Working Set and its Use in Scheduling Multiprocessor Systems
IEEE Transactions on Software Engineering
Approximate algorithms scheduling parallelizable tasks
SPAA '92 Proceedings of the fourth annual ACM symposium on Parallel algorithms and architectures
Real-time scheduling of linear speedup parallel tasks
Information Processing Letters
Scheduling parallel tasks with individual deadlines
Theoretical Computer Science
Parallel Processing for Real-Time Simulation: A Case Study
IEEE Parallel & Distributed Technology: Systems & Technology
Energy-Aware Partitioning for Multiprocessor Real-Time Systems
IPDPS '03 Proceedings of the 17th International Symposium on Parallel and Distributed Processing
An Approximation Algorithm for Energy-Efficient Scheduling on A Chip Multiprocessor
Proceedings of the conference on Design, Automation and Test in Europe - Volume 1
Multiprocessor Energy-Efficient Scheduling for Real-Time Tasks with Different Power Characteristics
ICPP '05 Proceedings of the 2005 International Conference on Parallel Processing
Energy-Efficient Scheduling for Real-Time Systems on Dynamic Voltage Scaling (DVS) Platforms
RTCSA '07 Proceedings of the 13th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications
Integrating job parallelism in real-time scheduling theory
Information Processing Letters
A retargetable parallel-programming framework for MPSoC
ACM Transactions on Design Automation of Electronic Systems (TODAES)
Corollaries to Amdahl's Law for Energy
IEEE Computer Architecture Letters
Analysis of Parallel Algorithms for Energy Conservation in Scalable Multicore Architectures
ICPP '09 Proceedings of the 2009 International Conference on Parallel Processing
Gang EDF Scheduling of Parallel Task Systems
RTSS '09 Proceedings of the 2009 30th IEEE Real-Time Systems Symposium
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While much work has addressed energy-efficient scheduling 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 develop energy minimizing algorithms for parallel task systems with timing guarantees. For parallel tasks executed by a fixed number of processors, we first propose several heuristic algorithms based on level-packing for task scheduling, and then present a polynomial-time complexity energy minimizing algorithm which is optimal for any given level-packed task schedule. For parallel tasks that can run on a variable number of processors, we propose another polynomial-time complexity algorithm to determine the number of processors executing each task, task schedule and frequency assignment. To the best of our knowledge, this is the first work that addresses energy-efficient scheduling for parallel real-time tasks. Our simulation result shows that the proposed approach can significantly reduce the system energy consumption.