An Analysis of the Feasibility of Energy Harvesting with Thermoelectric Generators on Petascale and Exascale Systems - Inria - Institut national de recherche en sciences et technologies du numérique
Conference Papers Year : 2016

An Analysis of the Feasibility of Energy Harvesting with Thermoelectric Generators on Petascale and Exascale Systems

Abstract

The heat induced by computing resources is generally a waste of energy in supercomputers. This is especially true in very large scale supercomputers, where the produced heat has to be compensated with expensive and energy consuming cooling systems. Energy is a critical point for future supercomputing trends that currently try to achieve exascale, without having its energy consumption reaching an important fraction of a nuclear power plant. Thus, new ways of generating or recovering energy have to be explored. Energy harvesting consists in recovering wasted energy. ThermoElectric Generators (TEGs) aim to recover energy by converting wasted dissipated energy into usable electricity. By combining computing units (CU) and TEGs at very large scale, we spotted a potential way to recover energy from wasted heat generated by computations on supercomputers. In this paper, we study the potential gains in combining TEGs with computational units at petascale and exascale. We present the technology behind TEGs, the study of a typical supercomputer environment, and finally our results concerning binding TEGs and computational units in a petascale and exascale system. With the available technology, we demonstrate that the use of TEGs in a supercomputer environment could be realistic and quickly profitable, and hence have a positive environmental impact.
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Dates and versions

hal-01348554 , version 1 (09-09-2019)

Identifiers

  • HAL Id : hal-01348554 , version 1

Cite

Issam Raïs, Laurent Lefèvre, Anne-Cécile Orgerie, Anne Benoit. An Analysis of the Feasibility of Energy Harvesting with Thermoelectric Generators on Petascale and Exascale Systems. Workshop Optimization of Energy Efficient HPC & Distributed Systems (OPTIM) in conjunction with HPCS, Jul 2016, Innsbruck, Austria. ⟨hal-01348554⟩
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