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Discover, model and combine energy leverages for large scale energy efficient infrastructures

Issam Raïs 1, 2
Abstract : Energy consumption is a growing concern on the verge of Exascale computing, a machine reaching 10^18 operations per seconds, 10 times the actual best public supercomputers, it became a crucial focus. Data centers consumed about 7% of total demand of electricity and are responsible of 2% of global carbon emission. With the multiplication of connected devices per person around the world, reducing the energy consumption of large scale computing system is a mandatory step to address in order to build a sustainable digital society.Several techniques, that we call leverage, have been developed in order to lower the electricalconsumption of computing facilities. To face this growing concern many solutions have beendeveloped at multiple levels of computing facilities: infrastructure, hardware, middle-ware, andapplication.It is urgent to embrace energy efficiency as a major concern of our modern computing facilities. Using these leverages is mandatory to better energy efficiency. A lot of leverages are available on large scale computing center. In spite of their potential gains, users and administrators don't fully use them or don't use them at all to better energy efficiency. Although, using these techniques, alone and combined, could be complicated and counter productive if not wisely used.This thesis defines and investigates the discovery, understanding and smart usage of leverages available on a large scale data center or supercomputer. We focus on various single leverages and understand them. We then combine them to other leverages and propose a generic solution to the dynamic usage of combined leverages.
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Submitted on : Wednesday, October 10, 2018 - 3:40:57 PM
Last modification on : Monday, May 4, 2020 - 11:40:21 AM
Long-term archiving on: : Friday, January 11, 2019 - 4:21:19 PM


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  • HAL Id : tel-01892387, version 1


Issam Raïs. Discover, model and combine energy leverages for large scale energy efficient infrastructures. Distributed, Parallel, and Cluster Computing [cs.DC]. Université de Lyon, 2018. English. ⟨NNT : 2018LYSEN051⟩. ⟨tel-01892387⟩



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