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Adapting MCP and HLFET Algorithms to Multiple Simultaneous Scheduling

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Abstract

We deal with the following scheduling problem: an infinite number of tasks must be scheduled for processing on a finite number of heterogeneous machines, such as all tasks are sent to execution with a minimum delay. The tasks have causal dependencies and are generated in the context of biomedical applications, and produce results relevant for the medical domain, such as diagnosis support or drug dose adjust measures. The proposed scheduling model had a starting point in two known bounded number of processors algorithms: Modified Critical Path and Highest Level First With Estimated Times. Several steps were added to the original implementation along with a merge stage in order to combine the results obtained for each of the previously scheduled tasks. Regarding the implementation, a simulator was used to analyze and design the scheduling algorithms.

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Notes

  1. As the preprocessing stage produced only one hash in the case of these simulations, the algorithm has been modified by suppressing the step in which the hashes containing partial results were merged, without loss of generality with respect to the purposes of the simulation.

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Acknowledgements

This article is based upon work from COST Action IC1406 High-Performance Modelling and Simulation for Big Data Applications (cHiPSet), supported by COST (European Cooperation in Science and Technology). Work has been partially supported by project DataWay - Real-time Data Processing Platform for Smart Cities: Making sense of Big Data (Platform de Procesare n Timp Real pentru Big Data n Orae Intelligent), with a grant of the Romanian National Authority for Scientific Research and Innovation, CNCS UEFISCDI, Project Number PN-II-RU-TE-2014-4-2731.

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Authors and Affiliations

  1. Computer Science Department, University Politehnica of Bucharest, Splaiul Independentei 313, 060042, Bucharest, Romania

    Emilia Popa & Florin Pop

  2. Dipartimento di Matematica e Fisica, Università degli Studi della Campania “Luigi Vanvitelli”, viale Lincoln 5, 81100, Caserta, Italy

    Mauro Iacono

  3. National Institute for Research and Development in Informatics (ICI), 8-10, Maresal Averescu, 011455, Bucharest, Romania

    Florin Pop

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  1. Emilia Popa
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Correspondence to Mauro Iacono.

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Popa, E., Iacono, M. & Pop, F. Adapting MCP and HLFET Algorithms to Multiple Simultaneous Scheduling. Int J Parallel Prog 46, 607–629 (2018). https://doi.org/10.1007/s10766-017-0516-z

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