基于快速启动OSv的HPC应用敏捷工作流微服务系统构建

Qiangxin Hu, Lixian Ma, En Shao, Guangming Tan
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引用次数: 0

摘要

容器的进步极大地促进了微服务架构的发展。这种体系结构将单片应用程序拆分为多个独立组件,容器编排器通过云环境中的容器管理这些组件。将高性能计算(HPC)应用程序部署为微服务的可行性已经得到了证明,但是现有的容器编排器会带来很大的性能开销,因为在同一物理主机上的不同容器之间存在干扰。在本文中,我们设计了一个基于快速启动OSv的敏捷工作流微服务系统。我们从单OSv启动时间优化和工作流编排优化两个方面考虑提高HPC工作流性能。对于单个OSv的启动时间优化,我们通过分析OSv启动过程,并通过修改OSv源代码找到优化点,设计了一个快速启动的OSv。通过这种方式,我们的启动时间提高了近50%。在工作流编排优化方面,结合OSv和工作流特性,提出节点融合、节点合并、镜像预加载、启动延迟四种优化技术,加快工作流的执行速度。此外,我们利用我们的快速启动OSv来设计一个编排系统,通过Kubevirt高效地构建一个敏捷的HPC工作流微服务。我们的实验结果优化微服务系统的执行时间比原来部署docker时减少了30%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Building Agile Workflow Microservice System for HPC Applications Based on Fast-start OSv
The advances of containers have significantly promoted the development of microservice architecture. This architecture splits a monolithic application into multiple independent components and the container orchestrator manages these components by the container in the cloud environment. The feasibility of deploying high performance computing(HPC) applications as microservices has been proven, but the existing container orchestrator incurs a large performance overhead as there is interference between different containers on the same physical host. In this paper, we design an agile workflow microservice system for HPC applications with fast-start OSv. We consider improving HPC workflow performance from two aspects: single OSv startup time optimization and workflow orchestration optimization. For single OSv startup time optimization, we design a fast-start OSv by analyzing the process of OSv startup and finding an optimization by modifying OSv source code. In this way, we get nearly 50% improvement of startup time. For workflow orchestration optimization, we propose four optimization techniques to speed up the execution of workflow by jointly considering OSv and workflow features, namely: node fusion, node merge, image preload, boot delay. Furthermore, we utilize our fast startup OSv to design an orchestration system for efficiently building an agile HPC workflow microservice by Kubevirt. Our experimental results optimization microservice system reduces the execution time by 30% compared with the original deployment with docker.
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