A data-driven approach to modeling power consumption for a hybrid supercomputer
Author:
Affiliation:
1. Department of Computer Science; University of Pisa; Pisa Italy
2. Science Division; New York University Abu Dhabi; Abu Dhabi United Arab Emirates
3. Department of Computer Science and Engineering; University of Bologna; Bologna Italy
Funder
European project SoBigData Research Infrastructure-Big Data and Social Mining Ecosystem, H2020-INFRAIA program
Publisher
Wiley
Subject
Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software
Reference30 articles.
1. Cavazzoni C Eurora: a European architecture toward exascale 2012 Venezia, Italy
2. Support vector regression machines;Smola;Adv Neural Inf Process Syst,1997
3. CINECA: The Italian Interuniversitary Consortium For High Performance Computing www.cineca.it
4. Bartolini A Cacciari M Cavazzoni C Tecchiolli G Benini L Unveiling eurora-thermal and power characterization of the most energy-efficient supercomputer in the world 2014 Dresden, Germany
5. Sîrbu A Babaoglu O Predicting system-level power for a hybrid supercomputer 2016 Innsbruck, Austria
Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Workload Prediction and VM Clustering Based Server Energy Optimization in Enterprise Cloud Data Center;Algorithms and Architectures for Parallel Processing;2022
2. Energy Consumption of MD Calculations on Hybrid and CPU-Only Supercomputers with Air and Immersion Cooling;Parallel Computing: Technology Trends;2020-03-20
3. Predicting Job Power Consumption Based on RJMS Submission Data in HPC Systems;Lecture Notes in Computer Science;2020
4. HPC & Co strike back: Where are distributed paradigms heading toward?;Concurrency and Computation: Practice and Experience;2018-02-12
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3