Computation with Energy-Time Trade-Offs: Models, Algorithms and Lower-Bounds

Bingham, Brad; Greenstreet, Mark R.

doi:10.1109/ispa.2008.127

Cited by 17 publications

(10 citation statements)

References 27 publications

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“…Vincent et al describe a technique that minimises Et 1 using CPU throttling [15]. Bingham and Greenstreet use Et n metrics to analyse runtime constraints imposed by a fixed energy budget for various algorithms [6]. Laros et al use Et n metrics to assess a number of production applications and state that Et 3 strikes the right balance between runtime and energy for HPC [26].…”

Section: Energy-aware Metricsmentioning

confidence: 99%

The Power-optimised Software Envelope

Roberts

Wright

Fahmy

et al. 2019

ACM Trans. Archit. Code Optim.

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Advances in processor design have delivered performance improvements for decades. As physical limits are reached, refinements to the same basic technologies are beginning to yield diminishing returns. Unsustainable increases in energy consumption are forcing hardware manufacturers to prioritise energy efficiency in their designs. Research suggests that software modifications may be needed to exploit the resulting improvements in current and future hardware. New tools are required to capitalise on this new class of optimisation. In this article, we present the Power Optimised Software Envelope (POSE) model, which allows developers to assess the potential benefits of power optimisation for their applications. The POSE model is metric agnostic and in this article, we provide derivations using the established Energy-Delay Product metric and the novel Energy-Delay Sum and Energy-Delay Distance metrics that we believe are more appropriate for energy-aware optimisation efforts. We demonstrate POSE on three platforms by studying the optimisation characteristics of applications from the Mantevo benchmark suite. Our results show that the Pathfinder application has very little scope for power optimisation while TeaLeaf has the most, with all other applications in the benchmark suite falling between the two. Finally, we extend our POSE model with a formulation known as System Summary POSE-a meta-heuristic that allows developers to assess the scope a system has for energy-aware software optimisation independent of the code being run. CCS Concepts: • Computing methodologies → Modeling and simulation; Model development and analysis; Modeling methodologies; • Hardware → Power and energy; Power estimation and optimization;

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Section: Energy-aware Metricsmentioning

confidence: 99%

The Power-optimised Software Envelope

Roberts

Wright

Fahmy

et al. 2019

ACM Trans. Archit. Code Optim.

View full text Add to dashboard Cite

show abstract

“…Vincent et al describe a technique which minimises Et 1 using CPU throttling [8]. Bingham and Greenstreet use Et n metrics to analyse runtime constraints imposed by a fixed energy budget for various algorithms [4]. Laros et al use Et n metrics to assess a number of production applications and state that Et 3 strikes the right balance between runtime and energy for high performance computing [16].…”

Section: Related Workmentioning

confidence: 99%

Metrics for Energy-Aware Software Optimisation

Roberts

Wright

Fahmy

et al. 2017

Lecture Notes in Computer Science

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A note on versions:The version presented here may differ from the published version or, version of record, if you wish to cite this item you are advised to consult the publisher's version. Please see the 'permanent WRAP url' above for details on accessing the published version and note that access may require a subscription.For more information, please contact the WRAP Team at: wrap@warwick.ac.uk Metrics for Energy-Aware Software OptimisationStephen I. Roberts, Steven A. Wright, Suhaib A. Fahmy, and Stephen A. Jarvis University of Warwick, U.K. S.I.Roberts@warwick.ac.uk Abstract. Energy consumption is rapidly becoming a limiting factor in scientific computing. As a result, hardware manufacturers increasingly prioritise energy efficiency in their processor designs. Performance engineers are also beginning to explore software optimisation and hardware/software co-design as a means to reduce energy consumption. Energy efficiency metrics developed by the hardware community are often re-purposed to guide these software optimisation efforts. In this paper we argue that established metrics, and in particular those in the Energy Delay Product (Et n ) family, are unsuitable for energy-aware software optimisation. A good metric should provide meaningful values for a single experiment, allow fair comparison between experiments, and drive optimisation in a sensible direction. We show that Et n metrics are unable to fulfil these basic requirements and present suitable alternatives for guiding energy-aware software optimisation. We finish with a practical demonstration of the utility of our proposed metrics.

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“…No task structuring of the parallel algorithms is considered. Approaches for an energy complexity metric are discussed in [41]. [42] proposes a system-level iso-energy-efficiency model to analyze, evaluate, and predict energy-performance of data intensive parallel applications.…”

Section: Related Workmentioning

confidence: 99%

Modeling and analyzing the energy consumption of fork‐join‐based task parallel programs

Rauber

Rünger

2014

Concurrency and Computation

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SUMMARYBecause of environmental and monetary concerns, it is increasingly important to reduce the energy consumption in all areas, including parallel and high performance computing. In this article, we propose an approach to reduce the energy consumption needed for the execution of a set of tasks computed in parallel in a fork-join fashion. The approach consists of an analytical model for the energy consumption of a parallel computation in fork-join form on dynamic voltage frequency scaling processors, a theoretical specification of an energy-optimal frequency-scaled state, and the energy minimization by computing optimal scaling factors. For larger numbers of tasks, the approach is extended by scheduling algorithms, which exploit the analytical result and aim at a reduction of the energy. Energy measurements of a complex numerical method and the SPEC CPU2006 benchmarks as well as simulations for a large number of randomly generated tasks illustrate and validate the energy modeling, the minimization, and the scheduling results.

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Computation with Energy-Time Trade-Offs: Models, Algorithms and Lower-Bounds

Cited by 17 publications

References 27 publications

The Power-optimised Software Envelope

The Power-optimised Software Envelope

Metrics for Energy-Aware Software Optimisation

Modeling and analyzing the energy consumption of fork‐join‐based task parallel programs

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