Using Container Migration for HPC Workloads Resilience

2019 IEEE High Performance Extreme Computing Conference (HPEC) Pub Date : 2019-09-01 DOI:10.1109/HPEC.2019.8916436

Mohamad Sindi, John R. Williams

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引用次数: 7

Abstract

We share experiences in implementing a containerbased HPC environment that could help sustain running HPC workloads on clusters. By running workloads inside containers, we are able to migrate them from cluster nodes anticipating hardware problems, to healthy nodes while the workloads are running. Migration is done using the CRIU tool with no application modification. No major interruption or overhead is introduced to the workload. Various real HPC applications are tested. Tests are done with different hardware node specs, network interconnects, and MPI implementations. We also benchmark the applications on containers and compare performance to native. Results demonstrate successful migration of HPC workloads inside containers with minimal interruption, while maintaining the integrity of the results produced. We provide several YouTube videos demonstrating the migration tests. Benchmarks also show that application performance on containers is close to native. We discuss some of the challenges faced during implementation and solutions adopted. To the best of our knowledge, we believe this work is the first to demonstrate successful migration of real MPI-based HPC workloads using CRIU and containers.

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使用容器迁移实现HPC工作负载弹性

我们将分享实现基于容器的HPC环境的经验，该环境有助于在集群上持续运行HPC工作负载。通过在容器内运行工作负载，我们能够在工作负载运行时将它们从预测硬件问题的集群节点迁移到健康节点。迁移是使用CRIU工具完成的，不需要修改应用程序。没有给工作负载引入主要的中断或开销。测试了各种实际HPC应用程序。测试使用了不同的硬件节点规格、网络互连和MPI实现。我们还在容器上对应用程序进行基准测试，并将性能与本机进行比较。结果表明，HPC工作负载在容器内的成功迁移具有最小的中断，同时保持所产生结果的完整性。我们提供了几个演示迁移测试的YouTube视频。基准测试还显示，容器上的应用程序性能接近本机。我们将讨论在实施过程中面临的一些挑战和采用的解决方案。据我们所知，我们认为这项工作是第一次展示使用CRIU和容器成功迁移真正基于mpi的HPC工作负载。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2019 IEEE High Performance Extreme Computing Conference (HPEC)

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