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A roofline model of energy
"... Abstract—We describe an energy-based analogue of the timebased roofline model. We create this model from the perspective of algorithm designers and performance tuners, with the intent not of making exact predictions, but rather, developing highlevel analytic insights into the possible relationships ..."
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Abstract—We describe an energy-based analogue of the timebased roofline model. We create this model from the perspective of algorithm designers and performance tuners, with the intent not of making exact predictions, but rather, developing highlevel analytic insights into the possible relationships among the time, energy, and power costs of an algorithm. The model expresses algorithms in terms of operations, concurrency, and memory traffic; and characterizes the machine based on a small number of simple cost parameters, namely, the time and energy costs per operation or per word of communication. We confirm the basic form of the model experimentally. From this model, we suggest under what conditions we ought to expect an algorithmic time-energy trade-off, and show how algorithm properties may help inform power management. Keywords-performance analysis; power and energy modeling; computational intensity; machine balance; roofline model I.
SPARTS: Simulator for Power Aware and Real-Time Systems
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An energyaware algorithm exploiting limited preemptive scheduling under fixed priorities
, 2013
"... Abstract—This paper presents a new energy-aware algorithm ..."
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Abstract—This paper presents a new energy-aware algorithm
Energy-aware partitioning of tasks onto a heterogeneous multi-core platform
- in Real-Time and Embedded Technology and Applications Symposium (RTAS), 2013 IEEE 19th
"... Modern multicore processors for the embedded market are often heterogeneous in nature. One feature often available are multiple sleep states with varying transition cost for entering and leaving said sleep states. This research effort explores the energy efficient task-mapping on such a heterogeneou ..."
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Modern multicore processors for the embedded market are often heterogeneous in nature. One feature often available are multiple sleep states with varying transition cost for entering and leaving said sleep states. This research effort explores the energy efficient task-mapping on such a heterogeneous multicore platform to reduce overall energy consumption of the system. This is performed in the context of a partitioned scheduling approach and a realistic power model, which improves over some of the simplifying assumptions often made in the state-of-the-art. The developed heuristic consists of two phases, in the first phase, tasks are allocated to minimise their active energy consumption, while the second phase trades off a higher active energy consumption for an increased ability to exploit savings through more efficient sleep states. Extensive simulations demonstrate the effectiveness of the approach.
Energy Saving Exploiting the Limited Preemption Task Model
"... Abstract-Limited preemptive scheduling has been shown to dominate both non-preemptive and fully preemptive scheduling under fixed priority systems, as far as schedulability is concerned. This paper suggests the use of DVFS and DPM techniques under limited preemptive scheduling to further reduce ene ..."
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Abstract-Limited preemptive scheduling has been shown to dominate both non-preemptive and fully preemptive scheduling under fixed priority systems, as far as schedulability is concerned. This paper suggests the use of DVFS and DPM techniques under limited preemptive scheduling to further reduce energy consumption with respect to a fully preemptive or non-preemptive approach.
On the Impact of Runtime Overhead on Energy-Aware Scheduling
"... Abstract—The real-time research community is often con-cerned with finding suitable assumptions to simplify the schedu-lability analysis of current real-time systems. This includes sim-plified power models, negligible scheduling overhead, negligible preemption cost, bounded cache misses and bus cont ..."
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Abstract—The real-time research community is often con-cerned with finding suitable assumptions to simplify the schedu-lability analysis of current real-time systems. This includes sim-plified power models, negligible scheduling overhead, negligible preemption cost, bounded cache misses and bus contention, etc. However, the actual behavior of a real application might be significantly different than that expected from a simplified system under the adopted set of assumptions. This paper investigates the impact that preemption cost might have on the energy consumption under a given energy-aware scheduling algorithm. A set of simulation experiments illustrate the influence of context switch and scheduling overhead on the actual energy consumed in a given system. Results show that, in certain conditions, the penalty due to the runtime overhead might be as large as the amount of energy saved using aggressive DPM and DVFS scheduling techniques. In this context, limited preemptive scheduling is proposed as a possible solution for limiting the main sources of overhead to fully exploit the benefits of power saving features of current computer architectures. I.
Online Intra-Task Device Scheduling for Hard Real-Time Systems
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