Dynamic knobs for responsive power-aware computing

HoffmannHenry,; SidiroglouStelios,; CarbinMichael,; MisailovicSasa,; AgarwalAnant,; RinardMartin,

doi:10.1145/1961296.1950390

Cited by 79 publications

(68 citation statements)

References 45 publications

(34 reference statements)

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“…Another example for online autotuning is PowerDial [49], which converts static configuration parameters that already exist in a program into dynamic knobs that can be tuned at runtime, with the goal of trading QoS guarantees for meeting performance and power usage goals. The system uses an online learning stage to construct a linear model of the choice configuration space which can be subsequently tuned using a linear control system.…”

Section: Autotuning Approaches Towards Energy Efficiencymentioning

confidence: 99%

Energy-efficient Algorithms for Ultrascale Systems

Carretero

Distefano

Petcu

et al. 2015

JSFI

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The chances to reach Exascale or Ultrascale Computing are strongly connected with the problem of the energy consumption for processing applications. For physical and economical reasons, the energy consumption has to be reduced significantly to make Ultrascale Computing possible. The research efforts towards energy-saving mechanisms of the hardware have already made energy-aware hardware systems available. However, to achieve a strong energy reduction, hardware mechanisms must be complemented with new energy-efficient software that can exploit them so that the foreseen energy savings actually result. In the software area, there also exist a multitude of research approaches towards energy saving, often concentrating either on the system software level or the application organization level, reflecting the expertise of the corresponding research group. The challenge of reducing the energy consumption dramatically to make Ultrascale Computing possible is so ambitious that a concerted action combining research efforts through all the software levels seems reasonable. In this article, we discuss the current research efforts and results related to energy efficiency in the diverse areas of software. We conclude with open problems and questions concerning energy-related techniques with an emphasis on the application or algorithmic side.

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Section: Autotuning Approaches Towards Energy Efficiencymentioning

confidence: 99%

Energy-efficient Algorithms for Ultrascale Systems

Carretero

Distefano

Petcu

et al. 2015

JSFI

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“…The algorithm computes the location in the array src of the pixel's neighboring four pixels (Lines 4-5), adjusts the locations at the image edges (Lines 7-14), and fetches the pixels (Lines [16][17][18][19]. To average the pixel values, the algorithm uses bilinear interpolation.…”

Section: Examplementioning

confidence: 99%

“…Then, to find the configuration of kernel reliability specifications that yield an acceptably accurate result, the profiler can systematically explore the search space, e.g. using strategies analogous to those that find configurations of accuracy-aware program transformations [16,24,26,40] from a finite set of possible configurations. The profiler then returns configurations that closely meet the accuracy target, ordered by the reliability of the most time-consuming kernels.…”

Section: Multiple Kernelsmentioning

confidence: 99%

See 1 more Smart Citation

Chisel

Misailovíc¹,

Carbin²,

Achour³

et al. 2014

Proceedings of the 2014 ACM International Conference on Object Oriented Programming Systems Languages &Amp; Applications

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The accuracy of an approximate computation is the distance between the result that the computation produces and the corresponding fully accurate result. The reliability of the computation is the probability that it will produce an acceptably accurate result. Emerging approximate hardware platforms provide approximate operations that, in return for reduced energy consumption and/or increased performance, exhibit reduced reliability and/or accuracy.We present Chisel, a system for reliability-and accuracyaware optimization of approximate computational kernels that run on approximate hardware platforms. Given a combined reliability and/or accuracy specification, Chisel automatically selects approximate kernel operations to synthesize an approximate computation that minimizes energy consumption while satisfying its reliability and accuracy specification.We evaluate Chisel on five applications from the image processing, scientific computing, and financial analysis domains. The experimental results show that our implemented optimization algorithm enables Chisel to optimize our set of benchmark kernels to obtain energy savings from 8.7% to 19.8% compared to the original (exact) kernel implementations while preserving important reliability guarantees.

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“…However, energy consumption is not proportional to its utilization. Hoffmann et al [6] presented a system that attempted to trade output accuracy for sustaining response time at peak loads. It dynamically tunes the configuration variables to exploit the accuracy-energy tradeoff.…”

Section: ) Server Clustersmentioning

confidence: 99%

On Accuracy-Performance Tradeoff Frameworks for Energy Saving: Models and Review

Yang

Jia

Chan

et al. 2012

2012 19th Asia-Pacific Software Engineering Conference

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A class of research, which explores energy saving via the accuracy-performance tradeoff ability of applications with soft outputs, is emerging. Many such applications implement various notions of precision improvement in their iterative computations and output approximated results. Computing more precisely often requires greater computational effort; hence there is a tradeoff space between precision and cost as long as the output accuracy remains within a targeted bound. This paper reviews the state-of-the-art accuracy tradeoff frameworks, and presents abstract model representations to facilitate our comparison of these frameworks in terms of robustness, performance, profiling, run-time feedback control, and specification of accuracy metrics.

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Dynamic knobs for responsive power-aware computing

Cited by 79 publications

References 45 publications

Energy-efficient Algorithms for Ultrascale Systems

Energy-efficient Algorithms for Ultrascale Systems

Chisel

On Accuracy-Performance Tradeoff Frameworks for Energy Saving: Models and Review

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