Energy and thermal models for simulation of workload and resource management in computing systems

Proceedings of the 2015 ACM Sixth International Conference on Future Energy Systems

Berge

2015

Self Cite

In this paper we study the power usage and thermal management of micro servers to analyze their impact on the overall data center energy consumption. We propose thermal models of micro servers based on analytical approach tuned with parameters derived from empirical tests. We demonstrate how fan management configuration affects the energy consumption of servers and the whole data center. We also apply the proposed model to predict temperature changes in a short time ahead and take advantage of these predictions to improve fan management. We show why PUE is not sufficient or can be even misleading in minimizing data center energy consumption. To mitigate this issue, we propose metrics that can be used to reflect correctly fans management impact on the overall energy consumption.

Section: Methodsmentioning

confidence: 95%

“…In terms of thermal models we follow the ones presented in our recent studies [13]. Hence, the changes in temperature of the processor are characterized by:…”

Section: Thermalmentioning

confidence: 99%

Modeling Impact of Power- and Thermal-Aware Fans Management on Data Center Energy Consumption

Piątek

Proceedings of the 2015 ACM Sixth International Conference on Future Energy Systems

Berge

2015

Self Cite

“…On the Cloud federation side, DISSECT-CF [238] proposes a model for energy consumption considering different components of PMs, without however considering RAM and thermal management. Some other simulators such as DCWorms [239] also propose to take into account during the simulation the thermal effects. Current simulation frameworks have mainly two limitations:…”

Section: Simulationmentioning

confidence: 99%

“…Stochastic simulations [240,241] Coverage No simulator is able to cover all the needed elements for Ultrascale simulations. Some works are trying to add the missing elements such as power and energy [242], Dynamic voltage and frequency scaling (DVFS) [243] or thermal simulation [239]. These improvements are in different simulators leading to difficulties to obtain a precise and global simulation taking into account all phenomenon.…”

Section: Simulationmentioning

confidence: 99%

Energy aware ultrascale systems

Ultrascale Computing Systems

Lefèvre

Alonso

et al. 2019

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HAL is a multidisciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

“…This generic model is a starting point to provide individual estimations for particular components of M2DC box. For instance, to reflect the thermal behaviour of a processor we use the simplified version of the above model, benefiting from Newton's law of cooling, that is presented in [16].…”

Section: Thermal Managementmentioning

confidence: 99%

M2DC – Modular Microserver DataCentre with heterogeneous hardware

Microprocessors and Microsystems

Kierzynka

Piątek

et al. 2017

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The Modular Microserver DataCentre (M2DC) project investigates, develops and demonstrates a modular, highly-efficient, cost-optimized server architecture composed of heterogeneous microserver computing resources. The resulting server architecture will be able to be tailored to meet requirements from a wide range of application domains. M2DC is built on three main pillars: a flexible server architecture that can be easily customised, maintained and updated; advanced management strategies and system efficiency enhancements (SEE); well-defined interfaces to the surrounding software data centre ecosystem. In this paper, we focus in particular on the thermal management strategies and on the initial benchmarking of the Aarch64 ARM architecture.