CoolEmAll: Models and Tools for Planning and Operating Energy Efficient Data Centres

Berge, Micha vor dem; Buchholz, Jochen; Cupertino, Leandro Fontoura; Costa, Georges Da; Donoghue, Andrew; Gallizo, Georgina; Jarus, Mateusz; Lopez, Lara; Oleksiak, Ariel; Pages, Enric; Piątek, Wojciech; Pierson, Jean‐Marc; Piontek, Tomasz; Rathgeb, Daniel; Salom, Jaume; Siso, Laura; Volk, Eugen; Wössner, Uwe; Zilio, Thomas

doi:10.1007/978-1-4939-2092-1_6

Cited by 4 publications

(4 citation statements)

References 15 publications

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“…For instance, in [32] authors propose a coherent model which covers data centre operation from CPU to cooling tower and calculates the static operating states (power consumption, the temperature at inlet and outlet of servers, airflow through the servers and water flow from cooling units) of the data centre and its components under various operating conditions. In [33], the authors suggest a flexible simulation platform integrating models of power usage and thermodynamic properties of IT-equipment and data centre facilities on different levels of detail. SimWare [34] is a holistic simulator of warehouse-scale computers which unites detailed temperature, power, and performance models for servers and cooling units and considers the impact of heat recirculation and air supply timing.…”

Section: Related Workmentioning

confidence: 99%

“…SimWare [34] is a holistic simulator of warehouse-scale computers which unites detailed temperature, power, and performance models for servers and cooling units and considers the impact of heat recirculation and air supply timing. The models in [33] and [34] differ in approaches to modelling the thermal distribution in the data centre, the first one uses computational fluid dynamics (CFD), whereas, the second utilises a static distribution matrix.…”

Section: Related Workmentioning

confidence: 99%

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Modular Model of a Data Centre as a Tool for Improving Its Energy Efficiency

et al. 2020

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Modular Model of a Data Centre as a Tool for Improving Its Energy Efficiency

et al. 2020

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“…The PSU used to supply the needed 12 V DC for the RECS server is based on six single Power Units. To model the electrical characteristics, a set of measurements has been done by the manufacturer [30]. These measurements compare the PSU's input (P AC ) and output power (P DC ), determining the load dependent efficiency as the ratio P DC /P AC .…”

Section: Psu's Power Conversion Lossesmentioning

confidence: 99%

“…Fig.1. Geometry of the RECS high density computing system[30]. The RECS server (a) is composed of 18 independent modules (b) arranged in two rows.…”

mentioning

confidence: 99%

Mastering system and power measures for servers in datacenter

Costa

Pierson

Cupertino

2017

Sustainable Computing: Informatics and Systems

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Using power meters and performance counters to get insight on system's behavior in terms of power consumption is common nowadays. The values coming from these external or internal meters are usually used directly by the research community, for instance to derive higher-level power models with learning techniques or to use them in decision tools such as schedulers in HPC and Cloud Computing. While it is reasonable when one wants only to have a broad view on the power consumption, they can not be used directly in most cases: We prove in this article that the problems of distributed measure and hardware limits are way more complex and create bias, and we give the keys to understand and chose the proper methodology to handle these bias to obtain relevant values for enhanced usage. A generic methodology is analyzed and its main lessons extracted for a direct usage by the research community to master system and power measures for servers in datacenter.

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