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Cluster Performance Forecasting Using Predictive Modeling for Virtual Beowulf Clusters

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Distributed Computing and Networking (ICDCN 2009)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5408))

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Abstract

In this paper we discuss our implementation of a virtual Beowulf cluster, and the results of experiments using which we have built a predictive model. Estimating a cluster’s performance is difficult, and investing in a real cluster without any idea of the performance that will be delivered is not recommended. We aim to suggest a way to address this problem by using a virtual Beowulf cluster. A virtual Beowulf cluster is a virtualized setup to simulate and understand the working of a real Beowulf cluster, but without extensive investments in hardware. This virtual setup is used to build a predictive model.

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Author information

Authors and Affiliations

  1. International Institute of Information Technology, Bangalore, India

    Abhijit Rao, Rajat Upadhyay, Nirav Shah, Sagar Arlekar, Jayanth Raghothamma & Shrisha Rao

Authors
  1. Abhijit Rao
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  2. Rajat Upadhyay
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  3. Nirav Shah
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  4. Sagar Arlekar
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  5. Jayanth Raghothamma
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  6. Shrisha Rao
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Editor information

Editors and Affiliations

  1. IBM India Research Laboratory, 110070, New Delhi, India

    Vijay Garg

  2. ETH Zurich, 8092, Zurich, Switzerland

    Roger Wattenhofer

  3. International Institute of Information Technology, 500032, Hyderabad, India

    Kishore Kothapalli

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© 2008 Springer-Verlag Berlin Heidelberg

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Rao, A., Upadhyay, R., Shah, N., Arlekar, S., Raghothamma, J., Rao, S. (2008). Cluster Performance Forecasting Using Predictive Modeling for Virtual Beowulf Clusters. In: Garg, V., Wattenhofer, R., Kothapalli, K. (eds) Distributed Computing and Networking. ICDCN 2009. Lecture Notes in Computer Science, vol 5408. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-92295-7_55

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  • DOI: https://doi.org/10.1007/978-3-540-92295-7_55

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-92294-0

  • Online ISBN: 978-3-540-92295-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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