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A Heuristic Scheduling and Resource Management System for Solving Bioinformatical Problems via High Performance Computing on Heterogeneous Multi-platform Hardware

  • Andreas Hölzlwimmer
  • Hannes Brandstätter-Müller
  • Bahram Parsapour
  • Gerald Lirk
  • Peter Kulczycki
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6927)

Abstract

To process the data available in Bioinformatics, High Performance Computing is required. To efficiently calculate the necessary data, the computational tasks need to be scheduled and maintained. We propose a method of predicting runtimes in a heterogeneous high performance computing environment as well as scheduling methods for the execution of hgih performance tasks. The heuristic method used is the feedforward artificial neural network, which utilizes a collected history of real life data to predict and schedule upcoming jobs.

Keywords

Prediction Error High Performance Computing Schedule System Heuristic Schedule Node Hide Layer 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Condor Team: Condor Version 7.4.2 Manual. University of Wisconsin-Madison (May 2010)Google Scholar
  2. 2.
    SLURM Team: SLURM: A Highly Scalable Resource Manager. SLURM Website (June 2010) (last visit July 15, 2010)Google Scholar
  3. 3.
    Templeton, D.: A Beginner’s Guide to Sun Grid Engine 6.2. Whitepaper, Sun Microsystems (July 2009)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Andreas Hölzlwimmer
    • 1
  • Hannes Brandstätter-Müller
    • 1
  • Bahram Parsapour
    • 1
  • Gerald Lirk
    • 1
  • Peter Kulczycki
    • 1
  1. 1.Upper Austria University of Applied SciencesHagenbergAustria

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