Considerations of Computational Efficiency in Volunteer and Cluster Computing

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• 关键词：Performance ; Power consumption ; Volunteer computing ; Cluster computing
• 刊名：Lecture Notes in Computer Science
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：9574
• 期：1
• 页码：66-74
• 全文大小：149 KB
• 参考文献：1.Dongarra, J.: Overview of high performance computing, SC 2013, UTK Booth talk, Denver, U.S.A (2013). http://​www.​netlib.​org/​utk/​people/​JackDongarra/​SLIDES/​sc13-UTK.​pdf
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  6.Czarnul, P., Kuchta, J., Matuszek, M.: Parallel computations in the volunteer – based comcute system. In: Wyrzykowski, R., Dongarra, J., Karczewski, K., Waśniewski, J. (eds.) PPAM 2013, Part I. LNCS, vol. 8384, pp. 261–271. Springer, Heidelberg (2014)CrossRef
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  11.Estrada, T., Taufer, M., Reed, K.: Modeling job lifespan delays in volunteer computing projects. In: 9th IEEE/ACM International Symposium on Cluster Computing and the Grid, CCGRID 2009, pp. 331–338 (2009)
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• 作者单位：Paweł Czarnul (19)
  Mariusz Matuszek (19)
  
  19. Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, Gdansk, Poland
  
• 丛书名：Parallel Processing and Applied Mathematics
• ISBN：978-3-319-32152-3
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349

文摘

In the paper we focus on analysis of performance and power consumption statistics for two modern environments used for computing – volunteer and cluster based systems. The former integrate computational power donated by volunteers from their own locations, often towards social oriented or targeted initiatives, be it of medical, mathematical or space nature. The latter is meant for high performance computing and is typically installed in a dedicated computing centre. While volunteer systems allow to obtain high computing power, they are not meant for dense computations and do not feature state-of-the-art hardware. Clusters offer best of the best at the cost of high purchase and maintenance cost. In the paper we give computational efficiency statistics for Atlas@Home, Asteroids@Home and BOINC cross-project and compare these to clusters such as Cray XC30, SuperMUC and TRYTON.