异构HPC环境中的性能与可移植性：为何需要预执行基准测试
Performance vs Portability in Heterogeneous HPC Environments: Why Pre-execution Benchmarking is Required
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中文总结 AI 辅助
本研究对比了容器化与系统直接执行量子化学软件的性能，发现编译、启动开销和配置影响性能，强调需针对工作负载进行预执行基准测试和用户级监控。
中文摘要 AI 辅助
云计算和高性能计算（HPC）通常遵循不同的范式：云服务常通过Kubernetes进行编排，而HPC工作负载则通过Slurm等批处理调度器管理。对共享计算资源日益增长的需求增加了这些环境之间互操作性的必要性。本研究使用Podman作为用户可访问的工具，对以预编译可执行文件形式分发的量子化学软件进行基准测试。在CPU优化构建和多个计算节点上，比较了容器化执行和系统直接执行，且未进行额外的网络优化。结果表明，性能取决于软件编译、启动开销和执行配置。容器准备可能主导短任务工作流，而长时间运行的计算则需要监控计算进度。这些发现强调了在HPC系统上以容器方式部署科学应用时，进行工作负载特定基准测试和用户级监控的重要性。
英文摘要
Cloud computing and high-performance computing (HPC) typically follow different paradigms: cloud services are often orchestrated using Kubernetes, whereas HPC workloads are managed through batch schedulers such as Slurm. Growing demand for shared computational resources increases the need for interoperability between these environments. This study uses Podman as a user-accessible tool to benchmark quantum chemistry software distributed as precompiled executables. Containerized and on-system execution are compared across CPU-optimized builds and multiple compute nodes, without additional network optimizations. The results demonstrate that performance depends on software compilation, startup overhead, and execution configuration. Container preparation can dominate short-task workflows, while long-running calculations require monitoring of computational progress. These findings highlight the importance of workload-specific benchmarking and user-level monitoring when deploying scientific applications in containers on HPC systems.
发表机构
- Institute of Chemical Physics, Faculty of Physics, Vilnius University（维尔纽斯大学物理学院化学物理研究所）
机构由 AI 辅助整理，请以论文原文为准。
