Energy-efficient, thermal-aware modeling and simulation of data centers: The CoolEmAll approach and evaluation results

Cupertino, Leandro Fontoura; Costa, Georges Da; Oleksiak, Ariel; Piątek, Wojciech; Pierson, Jean‐Marc; Salom, Jaume; Siso, Laura; Stolf, Patricia; Sun, Hongyang; Zilio, Thomas

doi:10.1016/j.adhoc.2014.11.002

Cited by 49 publications

(31 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We start from the description of the testbed we used, together with applied methodology and conclude with the discussion of the results. Description of the power models accuracy can be found in [21,22].…”

Section: Evaluation Of the Modelsmentioning

confidence: 99%

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

Piątek

Oleksiak

Costa

2015

Simulation Modelling Practice and Theory

Self Cite

View full text Add to dashboard Cite

Section: Evaluation Of the Modelsmentioning

confidence: 99%

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

Piątek

Oleksiak

Costa

2015

Simulation Modelling Practice and Theory

Self Cite

View full text Add to dashboard Cite

“…Beitelmal et al further developed chiller and cooling tower model [8], while Demetriou et al included hydraulic modelling of the pipe network in the model of the cooling system [9]. Recently published model from Cupertino et al was focused on workload modelling [10].…”

Section: Introductionmentioning

confidence: 99%

Power Consumption Modeling of Data Center IT Room with Distributed Air Flow

Zhang¹,

Lindberg²,

Svensson³

et al. 2016

IJMO

View full text Add to dashboard Cite

 Abstract-Modern data centers are characterized by large sizes, high energy consumption and complexity involving IT, power supply, ventilation and cooling. Data center energy efficiency is a major concern for data center design and operation. To improve data center energy efficiency through efficient cooling and ventilation, advanced process control and optimization, process models to describe the process power consumption are required. In this work, data center power consumption models are investigated. A concept of distributed air flow control is presented. The objective is to develop a comprehensive data center power consumption model to describe IT room, computer room air handling (CRAH), data center ventilation and cooling characteristics as well as distributed air flow control. Data center operation scenarios with uneven IT load are simulated. Results show that the distributed air flow control can save the cooling energy significantly.

show abstract

“…The results showed that a significant reduction in cooling power is achieved by combining different cooling systems. In order to improve the energy efficiency in a data center, an enormous amount of attention has been focused on thermal modeling and workload scheduling [2,7,8]. Sun et al proposed a spatio-temporal analytical model to study the thermal-aware task scheduling for a set of high-performance computing applications in both heterogeneous and homogeneous data center [9,10].…”

Section: Relate Workmentioning

confidence: 99%

Comparative Study of Energy Performance between Chip and Inlet Temperature-Aware Workload Allocation in Air-Cooled Data Center

Yan

2018

Energies

View full text Add to dashboard Cite

Improving the energy efficiency of data center has become a research focus in recent years. Previous works commonly adopted the inlet temperature constraint to optimize the thermal environment in the data center. However, the inlet temperature-aware method cannot prevent the servers from over-cooling. To cope with this issue, we propose a thermal-aware workload allocation strategy with respect to the chip temperature constraint. In this paper, we conducted a comparative evaluation of the performance between the chip and inlet temperature-aware workload allocation strategies. The workload allocation strategies adopt a POD-based heat recirculation model to characterize the thermal environment in data center. The contribution of the temperature-dependent leakage power to server power consumption is also considered. We adopted a sample data center under constant-flow and variable-flow cooling air supply to evaluate the performance of these two different workload allocation strategies. The comparison results show that the chip temperature-aware workload allocation strategy prevents the servers from over-cooling and significantly improves the energy efficiency of data center, especially for the case of variable-flow cooling air supply.

show abstract

Energy-efficient, thermal-aware modeling and simulation of data centers: The CoolEmAll approach and evaluation results

Abstract: OATAO is an open access repository that collects the work of Toulouse researchers and makes it freely available over the web where possible.

Cited by 49 publications

References 33 publications

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

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

Power Consumption Modeling of Data Center IT Room with Distributed Air Flow

Comparative Study of Energy Performance between Chip and Inlet Temperature-Aware Workload Allocation in Air-Cooled Data Center

Contact Info

Product

Resources

About