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Model. Perform. Eval. Comput. Syst."],"published-print":{"date-parts":[[2020,9,30]]},"abstract":"<jats:p>Power consumption of servers and applications are of utmost importance as computers are becoming ubiquitous, from smart phones to IoT and full-fledged computers. To optimize their power consumption, knowledge is necessary during execution at different levels: for the Operating System to take decisions of scheduling, for users to choose between different applications.<\/jats:p>\n          <jats:p>Several models exist to evaluate the power consumption of computers without relying on actual wattmeters: Indeed, these hardware are costly but also usually have limits on their pooling frequency (usually a one-second frequency is observed) except for dedicated professional hardware. The models link applications behavior with their power consumption, but up to now there is a 5% wall: Most models cannot reduce their error under this threshold and are usually linked to a particular hardware configuration.<\/jats:p>\n          <jats:p>This article demonstrates how to break the 5% wall of power models. It shows that by using neural networks it is possible to create models with 1% to 2% error. It also quantifies the reachable precision obtainable with other classical methods such as analytical models.<\/jats:p>","DOI":"10.1145\/3388322","type":"journal-article","created":{"date-parts":[[2020,6,1]],"date-time":"2020-06-01T04:34:30Z","timestamp":1590986070000},"page":"1-36","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Effectiveness of Neural Networks for Power Modeling for Cloud and HPC"],"prefix":"10.1145","volume":"5","author":[{"given":"Georges DA","family":"Costa","sequence":"first","affiliation":[{"name":"IRIT, University of Toulouse"}]},{"given":"Jean-Marc","family":"Pierson","sequence":"additional","affiliation":[{"name":"IRIT, University of Toulouse"}]},{"given":"Leandro","family":"Fontoura-Cupertino","sequence":"additional","affiliation":[{"name":"IRIT, University of Toulouse"}]}],"member":"320","published-online":{"date-parts":[[2020,5,31]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"BIOS and Kernel Developer\u2019s Guide (BKDG) for AMD Family 15h Models 00h-0Fh Processors","author":"Advanced Micro Devices Inc. 2013.","unstructured":"Advanced Micro Devices Inc. 2013. 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