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Issue No. 01 - Jan.-March (2016 vol. 4)
ISSN: 2168-7161
pp: 20-33
Jin Chen , Edward S. Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON, Canada
Gokul Soundararajan , , NetApp, Inc., Paloalto, CA
Saeed Ghanbari , , NetApp, Inc., Paloalto, CA
Francesco Iorio , , Autodesk Research and Department of Computer Science
Ali B. Hashemi , Edward S. Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON, Canada
Cristiana Amza , Edward S. Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON, Canada
ABSTRACT
We introduce Ensemble, a runtime framework and associated tools for building application performance models on-the-fly. These dynamic performance models can be used to support complex, highly dimensional resource allocation, and/or what-if performance inquiry in modern heterogeneous environments, such as data centers and Clouds. Ensemble combines simple, partially specified, and lower-dimensionality models to provide good initial approximations for higher dimensionality application performance models. We evaluated Ensemble on industry-standard and scientific applications. The results show that Ensemble provides accurate, fast, and flexible performance models even in the presence of significant environment variability.
INDEX TERMS
Analytical models, Mathematical model, Computational modeling, Cloud computing, Data models, Buffer storage, Context
CITATION

J. Chen, G. Soundararajan, S. Ghanbari, F. Iorio, A. B. Hashemi and C. Amza, "Ensemble: A Tool for Performance Modeling of Applications in Cloud Data Centers," in IEEE Transactions on Cloud Computing, vol. 4, no. 1, pp. 20-33, 2016.
doi:10.1109/TCC.2015.2469656
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