Combining optimistic and pessimistic DVS scheduling: An adaptive scheme and analysis

Perathoner, Simon; Lampka, Kai; Stoimenov, Nikolay; Thiele, Lothar; J.-J., Chen

doi:10.1109/iccad.2010.5654109

Cited by 8 publications

(15 citation statements)

References 14 publications

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“…By adopting RTC models, Chen et al [2009] explored the schedulability for the online DVFS scheduling algorithms proposed in Yao et al [1995]. Combining optimistic and pessimistic DVFS scheduling, Perathoner et al [2010] presented an adaptive scheme for the scheduling of arbitrary event streams. When only considering dynamic power management (DPM), Huang et al [2009bHuang et al [ , 2011a presented an algorithm to find periodic time-driven patterns to turn on/off the processor for energy saving.…”

Section: Related Workmentioning

confidence: 99%

Applying Pay-Burst-Only-Once Principle for Periodic Power Management in Hard Real-Time Pipelined Multiprocessor Systems

Chen¹,

Huang

Buckl

et al. 2015

ACM Trans. Des. Autom. Electron. Syst.

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Pipelined computing is a promising paradigm for embedded system design. Designing a power management policy to reduce the power consumption of a pipelined system with nondeterministic workload is, however, nontrivial. In this article, we study the problem of energy minimization for coarse-grained pipelined systems under hard real-time constraints and propose new approaches based on an inverse use of the pay-burst-onlyonce principle. We formulate the problem by means of the resource demands of individual pipeline stages and propose two new approaches, a quadratic programming-based approach and fast heuristic, to solve the problem. In the quadratic programming approach, the problem is transformed into a standard quadratic programming with box constraint and then solved by a standard quadratic programming solver. Observing the problem is NP-hard, the fast heuristic is designed to solve the problem more efficiently. Our approach is scalable with respect to the numbers of pipeline stages. Simulation results using real-life applications are presented to demonstrate the effectiveness of our methods.

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Section: Related Workmentioning

confidence: 99%

Applying Pay-Burst-Only-Once Principle for Periodic Power Management in Hard Real-Time Pipelined Multiprocessor Systems

Chen¹,

Huang

Buckl

et al. 2015

ACM Trans. Des. Autom. Electron. Syst.

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“…By adopting RTC models, Chen et al [6] explored the schedulability for online DVFS scheduling algorithms. Combining optimistic and pessimistic DVFS Scheduling, Perathoner et al [19] presented an adaptive scheme for the scheduling of arbitrary event streams. When only consider dynamic power management (DPM), Huang et al [10] presented a algorithm to find periodic time-driven patterns to turn on/off processor for energy saving.…”

Section: Related Workmentioning

confidence: 99%

“…Proof: By using the approximated lower bound of (11), the lower bound of end-to-end service curve β Gl i (∆) for stream S i (i = 1, ..., m) can be derived as the form of the right hand side of (19) according to Lem. 1.…”

Section: Problem Formulationmentioning

confidence: 99%

Adaptive dynamic power management for hard real-time pipelined Multiprocessor Systems

Chen

Huang

Knoll

2014

2014 IEEE 20th International Conference on Embedded and Real-Time Computing Systems and Applications

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Abstract-Energy efficiency is a critical design concern for embedded systems. Dynamic power management (DPM) schemes in Multiprocessor System on Chips (MPSoCs) has been wildly used to explore the idleness of processors and dynamically reduce the energy consumption by putting idle processors to low-power states. In this paper, we explore how to effectively apply dynamic power management in adaptive manner to reduce leakage power consumption for coarse-grained pipelined systems under hard real-time requirements. At each adaptive point, a system transformation is proposed to model the pipeline system with unfinished events as multi-stream system. By using extended payburst-only-once principle, the service curves for corresponding stream can be computed as a constraint for a minimal resource demand and energy minimization problem can be formulated with respect to the resource demands at each adaptive point. One light-weight heuristic, called balance workload scheme (BWS), is proposed in this paper to solve the minimization problem. Simulation results using real-life applications are presented to demonstrate the effectiveness of our approach.

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“…By using the arrival curve model [7] to abstract task arrivals into time interval domain, techniques based on dynamic frequency scaling [8], [10] and dynamic power management [5], [4] have been recently proposed for uni-processor systems. Nevertheless, how to cope with multiple processors is not yet clear.…”

Section: Related Workmentioning

confidence: 99%

Energy Optimization with Worst-Case Deadline Guarantee for Pipelined Multiprocessor Systems

Chen¹,

Huang²,

Buckl

et al. 2013

Design, Automation &Amp; Test in Europe Conference &Amp; Exhibition (DATE), 2013

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Abstract-Pipelined computing is a promising paradigm for embedded system design. Designing the scheduling policy for a pipelined system is however more involved. In this paper, we study the problem of the energy minimization for coarse-grained pipelined systems under hard real-time constraints and propose a method based on an inverse use of the pay-burst-only-once principle. We formulate the problem by means of the resource demands of individual pipeline stages and solve it by quadratic programming. Our approach is scalable w.r.t the number of the pipeline stages. Simulation results using real-life applications as well as commercialized processors are presented to demonstrate the effectiveness of our method.

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Combining optimistic and pessimistic DVS scheduling: An adaptive scheme and analysis

Cited by 8 publications

References 14 publications

Applying Pay-Burst-Only-Once Principle for Periodic Power Management in Hard Real-Time Pipelined Multiprocessor Systems

Applying Pay-Burst-Only-Once Principle for Periodic Power Management in Hard Real-Time Pipelined Multiprocessor Systems

Adaptive dynamic power management for hard real-time pipelined Multiprocessor Systems

Energy Optimization with Worst-Case Deadline Guarantee for Pipelined Multiprocessor Systems

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