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Architecture of the Slurm Workload Manager

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Job Scheduling Strategies for Parallel Processing (JSSPP 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14283))

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Abstract

Slurm is an open source, fault-tolerant, and highly scalable workload manager used on many of the world’s supercomputers and computer clusters. As a cluster workload manager, Slurm has three key functions. First, it allocates exclusive and/or non-exclusive access to resources for some duration of time. Second, it provides a framework for starting, executing, and monitoring work on the allocated resources. Finally, it arbitrates contention for resources by managing queues of pending work and enforcing administrative policies. This paper describes the current design and capabilities of Slurm.

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Notes

  1. 1.

    Slurm was originally an acronym for “Simple Linux Utility for Resource Management”, and stylized as “SLURM”. The acronym was dropped in 2012 and the preferred capitalization changed to “Slurm”.

  2. 2.

    The “partition” term was inherited from Quadrics RMS, which required a strict partitioning of compute nodes within the environment. The requirement that nodes be in disjoint partitions was discarded very early on, but the terminology has persisted.

  3. 3.

    This capability was successfully used at King Abdullah University of Science and Technology (KAUST) for a period when a power availability was limited. We are unaware of any other organization currently using of this capability.

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Author information

Authors and Affiliations

  1. SchedMD LLC, Lehi, UT, 84043, USA

    Morris A. Jette & Tim Wickberg

Authors
  1. Morris A. Jette
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  2. Tim Wickberg
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Correspondence to Morris A. Jette .

Editor information

Editors and Affiliations

  1. CESNET, Prague, Czech Republic

    Dalibor Klusáček

  2. Barcelona Supercomputing Center, Barcelona, Spain

    Julita Corbalán

  3. Apple, Cupertino, CA, USA

    Gonzalo P. Rodrigo

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Jette, M.A., Wickberg, T. (2023). Architecture of the Slurm Workload Manager. In: Klusáček, D., Corbalán, J., Rodrigo, G.P. (eds) Job Scheduling Strategies for Parallel Processing. JSSPP 2023. Lecture Notes in Computer Science, vol 14283. Springer, Cham. https://doi.org/10.1007/978-3-031-43943-8_1

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  • DOI: https://doi.org/10.1007/978-3-031-43943-8_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-43942-1

  • Online ISBN: 978-3-031-43943-8

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