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Resource Management for Running HPC Applications in Container Clouds

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High Performance Computing (ISC High Performance 2016)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9697))

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Abstract

Innovations in operating-system-level virtualization technologies such as resource control groups, isolated namespaces, and layered file systems have driven a new breed of virtualization solutions called containers. Applications running in containers depend on the host operating system (OS) for resource allocation, throttling, and prioritization. However, the OS is designed to provide only best-effort/fair-share resource allocation. Lack of resource management, as in virtual machine managers, constrains the use of containers and container-based clusters to a subset of workloads other than traditional high-performance computing (HPC) workflows. In this paper, we describe problems with the fair-share resource management of CPUs, network bandwidth, and I/O bandwidth on HPC workloads and present mechanisms to allocate, throttle, and prioritize each of these three critical resources in containerized HPC environments. These mechanisms enable container-based HPC clusters to host applications with different resource requirements and enforce effective resource use so that a large collection of HPC applications can benefit from the flexibility, portability, and agile characteristics of containers.

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Acknowledgment

This work is supported by NSF grant #312259 and #312236. We also thank IBM for providing access to their Softlayer (http://www.softlayer.com) and Supervessel (https://ptopenlab.com) cloud platforms and for providing guidance on container technologies. Our code can be found on GitHub at [12, 15, 20, 22].

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Authors and Affiliations

  1. University of Delaware, Newark, USA

    Stephen Herbein, Ayush Dusia, Aaron Landwehr, Sean McDaniel, Jose Monsalve, Yang Yang & Michela Taufer

  2. IBM T. J. Watson Research Center, Yorktown Heights, USA

    Seetharami R. Seelam

Authors
  1. Stephen Herbein
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  2. Ayush Dusia
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  3. Aaron Landwehr
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  4. Sean McDaniel
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  5. Jose Monsalve
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  6. Yang Yang
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  7. Seetharami R. Seelam
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  8. Michela Taufer
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Corresponding author

Correspondence to Michela Taufer .

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Editors and Affiliations

  1. Deutsches Klimarechenzentrum, Hamburg, Germany

    Julian M. Kunkel

  2. Argonne National Laboratory, Lemont, Illinois, USA

    Pavan Balaji

  3. University of Tennessee, Knoxville, Tennessee, USA

    Jack Dongarra

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© 2016 Springer International Publishing Switzerland

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Herbein, S. et al. (2016). Resource Management for Running HPC Applications in Container Clouds. In: Kunkel, J., Balaji, P., Dongarra, J. (eds) High Performance Computing. ISC High Performance 2016. Lecture Notes in Computer Science(), vol 9697. Springer, Cham. https://doi.org/10.1007/978-3-319-41321-1_14

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  • DOI: https://doi.org/10.1007/978-3-319-41321-1_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-41320-4

  • Online ISBN: 978-3-319-41321-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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