摘 要
容器化技术作为一种轻量级虚拟化方案，近年来在高性能计算（HPC）集群中展现出巨大潜力。传统HPC资源调度面临任务复杂性高、资源利用率低以及异构环境适配困难等问题，而容器化技术以其高效隔离性和快速部署能力为这些问题提供了新的解决思路。本研究旨在通过引入容器化技术优化HPC集群的资源调度策略，提升系统整体性能与资源利用率。提出了一种基于容器编排的动态资源调度框架，该框架结合预测算法与负载均衡机制，能够根据任务特征和资源状态智能分配计算资源。框架支持多类型任务混合调度，并具备良好的可扩展性，适用于大规模异构集群场景。本研究的主要创新点在于将容器化技术与动态调度策略深度融合，突破了传统调度方法在灵活性与效率上的局限，为未来HPC集群管理提供了可行的技术路径。
关键词：容器化技术；高性能计算；动态资源调度；负载均衡；异构集群
Optimization of Resource Scheduling in High-Performance Computing Clusters Using Containerization Technology
英文人名
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Abstract
Containerization, as a lightweight virtualization solution, has shown great potential in high-performance computing (HPC) clusters in recent years. Traditional HPC resource scheduling is faced with problems such as high task complexity, low resource utilization and difficult adaptation to heterogeneous environments. Containerization technology provides a new solution for these problems with its high efficiency isolation and rapid deployment capability. This study aims to optimize the resource scheduling strategy of HPC cluster by introducing containerization technology to improve the overall system performance and resource utilization. A dynamic resource scheduling fr amework based on container orchestration is proposed, which combines prediction algorithm and load balancing mechanism to intelligently allocate computing resources according to task characteristics and resource state. The fr amework supports mixed scheduling of multiple types of tasks and has good scalability, which is suitable for large-scale heterogeneous cluster scenarios. The main innovation of this study is the deep integration of containerization technology and dynamic scheduling strategy, which breaks through the limitations of traditional scheduling methods in flexibility and efficiency, and provides a feasible technical path for future HPC cluster management.
Keywords: Containerization Technology；High Performance Computing；Dynamic Resource Scheduling；Load Balancing；Heterogeneous Cluster
目 录
引言 1
一、容器化技术基础与挑战 1
(一)容器化技术概述 1
(二)高性能计算集群特点 2
(三)资源调度的挑战分析 2
二、容器化资源调度的关键问题 3
(一)资源隔离与共享机制 3
(二)动态负载均衡策略 4
(三)调度延迟优化研究 4
三、容器化技术在高性能计算中的应用 5
(一)容器编排框架选型 5
(二)资源分配模型设计 5
(三)性能评估与实验验证 6
四、优化策略与未来方向 6
(一)智能调度算法设计 7
(二)异构资源管理方案 7
(三)下一步研究展望 8
结论 8
参考文献 10
致谢 10
