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Singularity: Simple, secure containers for compute-driven workloads

Published: 28 July 2019 Publication History

Abstract

Container technology makes it easy to create highly portable and reproducible research environments. The Singularity container platform has a unique security model allowing untrusted users to run untrusted containers safely on multi-tenant systems. Singularity has a special file format (called the Singularity Image Format or SIF) for packaging and distributing containers. This format allows for novel features like cryptographic signing and verification of containers, extreme portability, and guaranteed reproducibility. The Singularity runtime supports both integration as well as isolation, making it easy to read and write data to the host system, leverage hardware like GPUs and high-speed interconnects, and integrate with batch schedulers like Slurm, PBS, LSF, UGE, etc. This emphasis on integration is part of the overall development philosophy: Singularity is intended to be a simple, secure, feature-rich container solution. Sylabs Inc. has developed SingularityPRO, a professionally curated and supported version of the open source offering as well as the Singularity Container Services, an end-to-end cloud hosted solution for creating and distributing trusted containers. Most top HPC centers use Singularity in production, and enterprise users are rapidly adopting this solution as well.

References

[1]
G.M Kurtzer, V Sochat, and M.W. Bauer, (2017). Singularity: Scientific containers for mobility of compute. PLoS one, 12(5).
[2]
VV Sochat, CJ Prybol, and GM Kurtzer (2017). Enhancing reproducibility in scientific computing: Metrics and registry for Singularity containers. PloS one, 12(11).
[3]
A.J. Younge, K. Pedretti, R.E. Grant, and R Brightwell (2017). A Tale of Two Systems: Using Containers to Deploy HPC Applications on Supercomputers and Clouds. 2017 IEEE International Conference on Cloud Computing Technology and Science (CloudCom) (pp. 74--81). IEEE.
[4]
E. Le and D. Paz (2017). Performance Analysis of Applications using Singularity Container on SDSC Comet. Proceedings of the Practice and Experience in Advanced Research Computing 2017 on Sustainability, Success and Impact (p. 66). ACM.
[5]
C. Arango, R. Dernat, and J. Sanabria (2017). Performance evaluation of container-based virtualization for high performance computing environments. arXiv preprint arXiv:1709.10140.

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  • (2024)A qualitative and quantitative analysis of container enginesJournal of Systems and Software10.1016/j.jss.2024.111965210:COnline publication date: 25-Jun-2024
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  • (2023)Immersive OSPRay: Enabling VR Experiences with OSPRayPractice and Experience in Advanced Research Computing 2023: Computing for the Common Good10.1145/3569951.3597579(226-230)Online publication date: 23-Jul-2023
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Published In

cover image ACM Other conferences
PEARC '19: Practice and Experience in Advanced Research Computing 2019: Rise of the Machines (learning)
July 2019
775 pages
ISBN:9781450372275
DOI:10.1145/3332186
  • General Chair:
  • Tom Furlani
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 28 July 2019

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Author Tags

  1. Kubernetes
  2. Linux containers
  3. cloud native
  4. reproducible science

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  • Research-article
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  • Refereed limited

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PEARC '19

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Overall Acceptance Rate 133 of 202 submissions, 66%

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Cited By

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  • (2024)A qualitative and quantitative analysis of container enginesJournal of Systems and Software10.1016/j.jss.2024.111965210:COnline publication date: 25-Jun-2024
  • (2023)Multi-tenancy in Cloud-native Architecture: A Systematic Mapping StudyWSEAS TRANSACTIONS ON COMPUTERS10.37394/23205.2023.22.422(25-43)Online publication date: 7-Mar-2023
  • (2023)Immersive OSPRay: Enabling VR Experiences with OSPRayPractice and Experience in Advanced Research Computing 2023: Computing for the Common Good10.1145/3569951.3597579(226-230)Online publication date: 23-Jul-2023
  • (2023)MyKSC: Disaggregated Containerized Supercomputer PlatformWeb Services – ICWS 202310.1007/978-3-031-44836-2_6(83-91)Online publication date: 23-Sep-2023
  • (2022)Creating Secure File Systems in Open-Source Operating SystemsWSEAS TRANSACTIONS ON SYSTEMS10.37394/23202.2022.21.2421(221-232)Online publication date: 24-Nov-2022
  • (2022)TEES: topology-aware execution environment service for fast and agile application deployment in HPCTEES:一种面向高性能计算快速、灵活应用程序部署的拓扑感知的运行环境服务Frontiers of Information Technology & Electronic Engineering10.1631/FITEE.210028423:11(1631-1645)Online publication date: 1-Jun-2022
  • (2022)Self-deployed execution environment for high performance computing面向高性能计算的自部署运行环境Frontiers of Information Technology & Electronic Engineering10.1631/FITEE.210001623:6(845-857)Online publication date: 4-Mar-2022
  • (2022)Automating Multivariable Workflow Composition for Model-to-Model Integration2022 IEEE 18th International Conference on e-Science (e-Science)10.1109/eScience55777.2022.00030(159-170)Online publication date: Oct-2022
  • (2022)Container Technologies for ARM Architecture: A Comprehensive Survey of the State-of-the-ArtIEEE Access10.1109/ACCESS.2022.319715110(84853-84881)Online publication date: 2022
  • (2020)Optimizing Biomedical Ultrasound Workflow Scheduling Using Cluster SimulationsJob Scheduling Strategies for Parallel Processing10.1007/978-3-030-63171-0_4(68-84)Online publication date: 22-May-2020
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