Understanding Layered Portability from HPC to Cloud in Containerized Environments
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arXiv
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| Hauptverfasser: | , , , |
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| Format: | Preprint |
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2024
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| _version_ | 1866913393655414784 |
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| author | Medeiros, Daniel Schieffer, Gabin Wahlgren, Jacob Peng, Ivy |
| author_facet | Medeiros, Daniel Schieffer, Gabin Wahlgren, Jacob Peng, Ivy |
| contents | Recent development in lightweight OS-level virtualization, containers, provides a potential solution for running HPC applications on the cloud platform. In this work, we focus on the impact of different layers in a containerized environment when migrating HPC containers from a dedicated HPC system to a cloud platform. On three ARM-based platforms, including the latest Nvidia Grace CPU, we use six representative HPC applications to characterize the impact of container virtualization, host OS and kernel, and rootless and privileged container execution. Our results indicate less than 4\% container overhead in DGEMM, miniMD, and XSBench, but 8\%-10\% overhead in FFT, HPCG, and Hypre. We also show that changing between the container execution modes results in negligible performance differences in the six applications. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_11760 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Understanding Layered Portability from HPC to Cloud in Containerized Environments Medeiros, Daniel Schieffer, Gabin Wahlgren, Jacob Peng, Ivy Distributed, Parallel, and Cluster Computing Recent development in lightweight OS-level virtualization, containers, provides a potential solution for running HPC applications on the cloud platform. In this work, we focus on the impact of different layers in a containerized environment when migrating HPC containers from a dedicated HPC system to a cloud platform. On three ARM-based platforms, including the latest Nvidia Grace CPU, we use six representative HPC applications to characterize the impact of container virtualization, host OS and kernel, and rootless and privileged container execution. Our results indicate less than 4\% container overhead in DGEMM, miniMD, and XSBench, but 8\%-10\% overhead in FFT, HPCG, and Hypre. We also show that changing between the container execution modes results in negligible performance differences in the six applications. |
| title | Understanding Layered Portability from HPC to Cloud in Containerized Environments |
| topic | Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2406.11760 |