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Walltime Prediction and Its Impact on Job Scheduling Performance and Predictability

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F63839172%3A_____%2F20%3A10133332" target="_blank" >RIV/63839172:_____/20:10133332 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1007/978-3-030-63171-0_7" target="_blank" >http://dx.doi.org/10.1007/978-3-030-63171-0_7</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-030-63171-0_7" target="_blank" >10.1007/978-3-030-63171-0_7</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Walltime Prediction and Its Impact on Job Scheduling Performance and Predictability

  • Original language description

    For more than two decades researchers have been analyzing the impact of inaccurate job walltime (runtime) estimates on the performance of job scheduling algorithms, especially the backfilling. In this paper, we extend these existing works by focusing on the overall impact that improved walltime estimates have both on job scheduling performance and predictability. For this purpose, we evaluate such impact in several steps. First, we present a simple walltime predictor and analyze its accuracy with respect to original user walltime estimates captured in real-life workload traces. Next, we use these traces and a simulator to see what is the impact of improved estimates on general performance (backfilling ratio and wait time) as well as predictability. We show that even a simple predictor can significantly decrease user-based errors in runtime estimates, while also slightly improving job wait times and backfilling ratio. Concerning predictions, we show that walltime predictor significantly decreases errors in job wait time forecasting while having little effect on the ability of the scheduler to provide solid advance predictions about which nodes will be used by a given waiting job.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2020

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Job Scheduling Strategies for Parallel Processing

  • ISBN

    978-3-030-63170-3

  • ISSN

    0302-9743

  • e-ISSN

  • Number of pages

    18

  • Pages from-to

    127-144

  • Publisher name

    Springer

  • Place of publication

    Switzerland

  • Event location

    New Orleans

  • Event date

    May 22, 2020

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article