Charliecloud: Unprivileged containers for user-defined software stacks in HPC

Priedhorsky, Reid; Randles, Timothy

doi:10.2172/1296650

Cited by 35 publications

(47 citation statements)

References 5 publications

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“…We provide an overview of our comparison of the leading container technologies in (Table 1), which has been extended and adopted from [30]. As it is the case that technologies change quickly, the authors would like to note that this table, and the following discussion, is relevant to the time of writing of this paper.…”

Section: The Problems That Singularity Solvesmentioning

confidence: 99%

Singularity: Scientific containers for mobility of compute

2017

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Here we present Singularity, software developed to bring containers and reproducibility to scientific computing. Using Singularity containers, developers can work in reproducible environments of their choosing and design, and these complete environments can easily be copied and executed on other platforms. Singularity is an open source initiative that harnesses the expertise of system and software engineers and researchers alike, and integrates seamlessly into common workflows for both of these groups. As its primary use case, Singularity brings mobility of computing to both users and HPC centers, providing a secure means to capture and distribute software and compute environments. This ability to create and deploy reproducible environments across these centers, a previously unmet need, makes Singularity a game changing development for computational science.

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Section: The Problems That Singularity Solvesmentioning

confidence: 99%

Singularity: Scientific containers for mobility of compute

2017

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“…Charliecloud and Docker. Priedhorsky and Randles from the Los Alamos National Laboratory introduced in 2017 in [16] a lightweight open source implementations of a container framework: Charliecloud. The authors followed their basic assumptions that the need for user-defined software stacks (UDSS) increases.…”

Section: Related Workmentioning

confidence: 99%

Enabling EASEY Deployment of Containerized Applications for Future HPC Systems

Höb

Kranzlmüller

2020

Lecture Notes in Computer Science

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The upcoming exascale era will push the changes in computing architecture from classical CPU-based systems towards hybrid GPU-heavy systems with much higher levels of complexity. While such clusters are expected to improve the performance of certain optimized HPC applications, it will also increase the difficulties for those users who have yet to adapt their codes or are starting from scratch with new programming paradigms. Since there are still no comprehensive automatic assistance mechanisms to enhance application performance on such systems, we propose a support framework for future HPC architectures, called EASEY (Enable exASclae for EverYone). Our solution builds on a layered software architecture, which offers different mechanisms on each layer for different tasks of tuning, including a workflow management system. This enables users to adjust the parameters on each of the layers, thereby enhancing specific characteristics of their codes. We introduce the framework with a Charliecloud-based solution, showcasing the LULESH benchmark on the upper layers of our framework. Our approach can automatically deploy optimized container computations with negligible overhead and at the same time reduce the time a scientist needs to spent on manual job submission configurations.

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“…Indeed, some works already described COS technologies in a scientific use case [31], [7], [33], [10]. Despite the advantages offered by container technologies, the implications for scientific computing, including HPC, are still unclear, although there are already some initiatives like Singularity, Shifter [19] (See also benchmarks on Cray systems for Shifter [6]), Charliecloud [35], cHPC [41] or Docker Universe Applications in HTCondor 10 .…”

Section: Iii-g Source Codementioning

confidence: 99%

Performance evaluation of container-based virtualization for high performance computing environments

Arango¹,

Dernat

Sanabria³

2019

revuin

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Virtualization technologies have evolved along with the development of computational environments since virtualization offered needed features at that time such as isolation, accountability, resource allocation, resource fair sharing and so on. Novel processor technologies bring to commodity computers the possibility to emulate diverse environments where a wide range of computational scenarios can be run. Along with processors evolution, system developers have created different virtualization mechanisms where each new development enhanced the performance of previous virtualized environments. Recently, operating system-based virtualization technologies captured the attention of communities abroad (from industry to academy and research) because their important improvements on performance area.In this paper, the features of three container-based operating systems virtualization tools (LXC, Docker and Singularity) are presented. LXC, Docker, Singularity and bare metal are put under test through a customized single node HPL-Benchmark and a MPI-based application for the multi node testbed. Also the disk I/O performance, Memory (RAM) performance, Network bandwidth and GPU performance are tested for the COS technologies vs bare metal. Preliminary results and conclusions around them are presented and discussed.

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Charliecloud: Unprivileged containers for user-defined software stacks in HPC

Cited by 35 publications

References 5 publications

Singularity: Scientific containers for mobility of compute

Singularity: Scientific containers for mobility of compute

Enabling EASEY Deployment of Containerized Applications for Future HPC Systems

Performance evaluation of container-based virtualization for high performance computing environments

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