Proceedings ArticleDOI
Energy minimization for periodic real-time tasks on heterogeneous processing units
Jian-Jia Chen,Andreas Schranzhofer,Lothar Thiele +2 more
- pp 1-12
TLDR
Experimental results show that the proposed polynomial-time algorithms for energy-aware task partitioning and processing unit allocation are effective for the minimization of the overall energy consumption.Abstract:
Adopting multiple processing units to enhance the computing capability or reduce the power consumption has been widely accepted for designing modern computing systems. Such configurations impose challenges on energy efficiency in hardware and software implementations. This work targets power-aware and energy-efficient task partitioning and processing unit allocation for periodic real-time tasks on a platform with a library of applicable processing unit types. Each processing unit type has its own power consumption characteristics for maintaining its activeness and executing jobs. This paper proposes polynomial-time algorithms for energy-aware task partitioning and processing unit allocation. The proposed algorithms first decide how to assign tasks onto processing unit types to minimize the energy consumption, and then allocate processing units to fit the demands. The proposed algorithms for systems without limitation on the allocated processing units are shown with an (m+1)-approximation factor, where mis the number of the available processing unit types. For systems with limitation on the number of the allocated processing units, the proposed algorithm is shown with bounded resource augmentation on the limited number of allocated units. Experimental results show that the proposed algorithms are effective for the minimization of the overall energy consumption.read more
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Real-Time Systems
TL;DR: The journal Real-Time Systems publishes papers, short papers and correspondence articles that concentrate on real-time computing principles and applications, including requirements engineering, specification and verification techniques, design methods and tools, programming languages, operating systems, scheduling algorithms, architecture, hardware and interfacing.
Journal ArticleDOI
Dynamic Power-Aware Mapping of Applications onto Heterogeneous MPSoC Platforms
TL;DR: This study shows that deriving approximative solutions with a constant worst-case approximation factor in polynomial time is not achievable unless P = NP, even if a feasible task mapping is provided as an input.
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A DVFS Based Energy-Efficient Tasks Scheduling in a Data Center
TL;DR: This paper proposes a new task model that describes the QoS requirements of tasks with the minimum frequency and proves that the minimization of ECR is NP-hard, which verifies the good performance of this strategy on energy saving.
Proceedings ArticleDOI
Energy-aware partitioning of tasks onto a heterogeneous multi-core platform
TL;DR: This research effort explores the energy efficient task-mapping on such a heterogeneous multicore platform to reduce overall energy consumption of the system.
Journal ArticleDOI
Energy-Efficient Real-Time Scheduling of DAG Tasks
TL;DR: This work adapts the decomposition-based framework for federated scheduling and proposes an energy-sub-optimal scheduler and derives an approximation algorithm to identify processors to be merged together for further improvements in energy-efficiency.
References
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