摘 要
随着信息技术的迅猛发展，高性能计算在科学计算、工程仿真等领域发挥着不可替代的作用。本研究旨在构建高性能计算集群并对其性能进行优化，以满足日益增长的大规模数据处理需求。研究基于当前主流硬件架构和网络技术，选用特定类型的服务器节点，通过高速互联网络连接，构建了具备高可扩展性的计算集群。采用MPI并行编程模型实现任务调度与资源管理，并引入容器化技术提高应用部署效率。针对集群性能瓶颈问题，从硬件配置优化、软件算法改进以及系统参数调优三方面入手，提出了一套完整的性能优化方案。实验结果表明，在多种典型应用场景下，经过优化后的集群性能较原始状态有显著提升，部分场景下的加速比接近理想值。本研究创新性地将容器化技术应用于高性能计算集群环境，有效解决了传统部署方式中存在的兼容性和移植性难题，同时为后续研究提供了新的思路与方法，对推动高性能计算技术的发展具有重要意义。
关键词：高性能计算集群；性能优化；容器化技术；MPI并行编程；硬件配置优化
Abstract
With the rapid advancement of information technology, high-performance computing (HPC) plays an indispensable role in scientific computing and engineering simulation. This study aims to construct and optimize an HPC cluster to meet the growing demand for large-scale data processing. Based on current mainstream hardware architectures and network technologies, specific types of server nodes were selected and interconnected via a high-speed network to build a highly scalable computing cluster. The Message Passing Interface (MPI) parallel programming model was employed for task scheduling and resource management, while containerization technology was introduced to enhance application deployment efficiency. To address performance bottlenecks in the cluster, a comprehensive optimization strategy was proposed from three perspectives: hardware configuration optimization, software algorithm improvement, and system parameter tuning. Experimental results demonstrate that, under various typical application scenarios, the optimized cluster exhibits significant performance improvements compared to its original state, with speedup ratios approaching ideal values in some cases. Innovatively, this research applies containerization technology to the HPC cluster environment, effectively resolving compatibility and portability issues inherent in traditional deployment methods. Furthermore, it provides new insights and methodologies for future research, contributing significantly to the development of HPC technology.
Keywords：High-Performance Computing Cluster；Performance Optimization；Containerization Technology；Mpi Parallel Programming；Hardware Configuration Optimization
目 录
摘 要 I
Abstract II
引 言 1
第一章 高性能计算集群的构建基础 2
1.1 构建需求分析 2
1.2 硬件选型原则 2
1.3 软件环境搭建 3
第二章 集群网络架构设计 5
2.1 网络拓扑选择 5
2.2 通信协议优化 5
2.3 带宽与延迟平衡 6
第三章 性能评估与瓶颈分析 8
3.1 性能指标体系 8
3.2 关键瓶颈识别 8
3.3 评测工具应用 9
第四章 综合性能优化策略 11
4.1 并行计算优化 11
4.2 资源调度改进 11
4.3 故障容错机制 12
结 论 14
参考文献 15
致 谢 16
