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Performance and Energy Efficiency of Parallel Processing in Data Center Environments

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Energy Efficient Data Centers (E2DC 2014)

Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 8945))

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Abstract

A novel approach is presented for the analysis of parallel processing of stochastic workload by multi-processor/multi-core processing resources in data center environments. The method is based on job workload descriptions by task graphs with generally-distributed task execution times and task scheduling under consideration of prescribed precedence and synchronization constraints. For the analytic performance evaluation, task graphs are restricted to the analysis of directed acyclic graphs which are reduced by stepwise aggregations of tasks. The reduction allows to aggregate the whole task graph under a given number n of processing elements to a single virtual job processing time with average value hv and coefficient of variation cv. By this way, the whole multi-processor system can be modeled by a queuing system of type GI/G/1 from which the response time TR and the speedup factor S(n) is derived. Finally, the influence of the stochastic properties of the workload on the performance and on energy efficiency of parallel computing will be studied and compared with serial computing on a multi-processor system modeled by a queuing system of the type M/G/n.

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Author information

Authors and Affiliations

  1. Institute of Communication Networks and Computer Engineering, University of Stuttgart, Stuttgart, Germany

    Paul J. Kuehn

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  1. Paul J. Kuehn
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Correspondence to Paul J. Kuehn .

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Editors and Affiliations

  1. University of Mannheim, Mannheim, Germany

    Sonja Klingert

  2. ICT-Division Italian National Agency for New Technologies Energy, Rome, Italy

    Marta Chinnici

  3. Gas Natural Fenosa, Technological Projects, Barcelona, Spain

    Milagros Rey Porto

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Kuehn, P.J. (2015). Performance and Energy Efficiency of Parallel Processing in Data Center Environments. In: Klingert, S., Chinnici, M., Rey Porto, M. (eds) Energy Efficient Data Centers. E2DC 2014. Lecture Notes in Computer Science(), vol 8945. Springer, Cham. https://doi.org/10.1007/978-3-319-15786-3_2

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  • DOI: https://doi.org/10.1007/978-3-319-15786-3_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-15785-6

  • Online ISBN: 978-3-319-15786-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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