Hardware optimization and performance evaluation of high-performance computing clusters
高性能计算集群的硬件优化与性能评估

摘要

高性能计算集群的硬件优化是提升计算效率和资源利用率的关键手段。本文系统分析了集群硬件架构中的瓶颈因素，提出基于多层次缓存优化、网络拓扑调整和负载均衡策略的优化方案。通过实际性能评估，验证了优化措施在降低通信延迟、提升计算吞吐量和提高能效比方面的显著效果。研究结果表明，合理的硬件优化不仅提升了集群整体性能，还为大规模计算任务提供了有力支撑，推动了高性能计算系统的持续发展。本文的探索为相关领域的硬件设计和系统调优提供了理论依据和实践指导。

Abstract

Hardware optimization of high-performance computing clusters is a key means to improve computational efficiency and resource utilization. This paper systematically analyzes the bottleneck factors in cluster hardware architectures and proposes an optimization scheme based on multi-level cache optimization, network topology adjustment, and load balancing strategies. Through practical performance evaluation, the significant effects of the optimization measures in reducing communication latency, enhancing computational throughput, and improving energy efficiency ratio are verified. The research results show that reasonable hardware optimization not only enhances the overall performance of the cluster but also provides a strong support for large-scale computational tasks, promoting the continuous development of high-performance computing systems. The exploration in this paper provides a theoretical basis and practical guidance for hardware design and system tuning in related fields.