Abstract
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.
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References
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
Czarnul, P., Rościszewski, P.: Optimization of execution time under power consumption constraints in a heterogeneous parallel system with GPUs and CPUs. In: Chatterjee, M., Cao, J., Kothapalli, K., Rajsbaum, S. (eds.) ICDCN 2014. LNCS, vol. 8314, pp. 66–80. Springer, Heidelberg (2014)
Beberg, A.L., Ensign, D.L., Jayachandran, G., Khaliq, S., Pande, V.S.: Folding@home: lessons from eight years of volunteer distributed computing. In: 8th IEEE International Workshop on High Performance Computational Biology (HiCOMB 2009) in Conjunction with the IEEE International Parallel and Distributed Processing Symposium (IPDpPS 2009) (2009)
Anderson, D.P.: Boinc: A system for public-resource computing and storage. In: Proceedings of 5th IEEE/ACM International Workshop on Grid Computing, Pittsburgh, USA (2004)
Anderson, D.P., Korpela, E., Walton, R.: High-performance task distribution for volunteer computing. In: Proceedings of the First International Conference on e-Science and Grid Computing, E-SCIENCE 2005, Washington, USA, pp. 196–203. IEEE Computer Society (2005)
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)
Balicki, J., Krawczyk, H., Nawarecki, E. (eds.): Grid and Volunteer Computing. Gdansk University of Technology, Faculty of Electronics, Telecommunication and Informatics Press, Gdansk ISBN: 978-83-60779-17-0 (2012)
Cushing, R., Putra, G., Koulouzis, S., Belloum, A., Bubak, M., de Laat, C.: Distributed computing on an ensemble of browsers. Internet Comput. IEEE 17, 54–61 (2013)
MacWilliam, T., Cecka, C.: Crowdcl: Web-based volunteer computing with webcl. In: High Performance Extreme Computing Conference (HPEC 2013), pp. 1–6. IEEE (2013)
Funai, C., Tapparello, C., Ba, H., Karaoglu, B., Heinzelman, W.: Extending volunteer computing through mobile ad hoc networking. In: IEEE GLOBECOM Global Communications Conference Exhibition & Industry Forum, Austin, TX, U.S.A (2014)
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)
Heien, E.M., Kondo, D., Anderson, D.P.: A correlated resource model of internet end hosts. IEEE Trans. Parallel Distrib. Syst. 23, 977–984 (2012)
Czarnul, P., Matuszek, M.: Performance modeling and prediction of real application workload in a volunteer-based system. In: Applications of Information Systems in Engineering and Bioscience, Proceedings of 13th International Conference on SOFTWARE ENGINEERING, PARALLEL and DISTRIBUTED SYSTEMS Conference (SEPADS), Gdansk, Poland, WSEAS, pp. 37–45 (2014). ISBN: 978-960-474-381-0. http://www.wseas.us/e-library/conferences/2014/Gdansk/SEBIO/SEBIO-03.pdf
Li, J., Deshpande, A., Srinivasan, J., Ma, X.: Energy and performance impact of aggressive volunteer computing with multi-core computers. In: IEEE International Symposium on Modeling, Analysis Simulation of Computer and Telecommunication Systems, MASCOTS, pp. 1–10 (2009)
McGough, A.S., Forshaw, M.: Reduction of wasted energy in a volunteer computing system through reinforcement learning. Sustainable Computing: Informatics and Systems, vol. 4, pp. 262–275. Special Issue on Energy Aware Resource Management and Scheduling (EARMS) (2014)
Hanappe, P.: Fine-grained cpu throttling to reduce the energy footprint of volunteer computing. Technical report, Sony Computer Science Laboratory Paris (2012)
Acknowledgments
The work was performed within grant “Modeling efficiency, reliability and power consumption of multilevel parallel HPC systems using CPUs and GPUs” sponsored by and covered by funds from the National Science Center in Poland based on decision no DEC-2012/07/B/ST6/01516.
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Czarnul, P., Matuszek, M. (2016). Considerations of Computational Efficiency in Volunteer and Cluster Computing. In: Wyrzykowski, R., Deelman, E., Dongarra, J., Karczewski, K., Kitowski, J., Wiatr, K. (eds) Parallel Processing and Applied Mathematics. Lecture Notes in Computer Science(), vol 9574. Springer, Cham. https://doi.org/10.1007/978-3-319-32152-3_7
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