C-Oracle: Predictive Thermal Management for Data Centers

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C-Oracle: Predictive Thermal Management for Data Centers (2008)

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by Luiz Ramos , Ricardo Bianchini

Venue:	In Symposium on High-Performance Computer Architecture
Citations:	44 - 5 self

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@INPROCEEDINGS{Ramos08c-oracle:predictive,
    author = {Luiz Ramos and Ricardo Bianchini},
    title = {C-Oracle: Predictive Thermal Management for Data Centers},
    booktitle = {In Symposium on High-Performance Computer Architecture},
    year = {2008},
    pages = {111--122}
}

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Abstract

Thermal management has become a critical requirement for today’s power-dense server clusters, due to the negative impact of high temperatures on the reliability of computer hardware. Recognizing this fact, researchers have started to design software-based thermal management policies that leverage high-level information to control system-wide temperatures effectively. Unfortunately, designing these policies is currently a challenge, since it is difficult to predict the exact temperature and performance that would result from trying to react to a thermal emergency. Reactions that are excessively severe may cause unnecessary performance degradation and/or generate emergencies in other parts of the system, whereas reactions that are excessively mild may take relatively long to become effective (if at all), compromising the reliability of the system. To address this challenge, in this paper we propose C-Oracle, a software infrastructure for Internet services that dynamically predicts the temperature and performance impact of different thermal management reactions into the future, allowing the thermal management policy to select the best reaction at each point in time. C-Oracle makes predictions based on simple models of temperature, component utilization, and policy behavior that can be solved efficiently. We experimentally evaluate C-Oracle for thermal management policies based on load redistribution and dynamic voltage/frequency scaling in both single-tier and multi-tier services. Our results show that, regardless of management policy or service organization, C-Oracle enables non-trivial decisions that effectively manage thermal emergencies, while avoiding unnecessary performance degradation. 1

Keyphrases

data center predictive thermal management thermal emergency thermal management policy unnecessary performance degradation software infrastructure non-trivial decision management policy performance impact power-dense server cluster high temperature internet service exact temperature whereas reaction simple model thermal management critical requirement dynamic voltage frequency scaling different thermal management reaction component utilization negative impact system-wide temperature software-based thermal management policy multi-tier service high-level information service organization computer hardware policy behavior load redistribution

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