HEP 基准套件:提高全球大型强子对撞机计算基础设施的效率和可持续性

Natalia Szczepanek, David Britton, Alessandro Di Girolamo, Ewoud Ketele, Ivan Glushkov, Domenico Giordano, Ladislav Ondris, Emanuele Simili, Gonzalo Menendez Borge
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摘要

随着科学界不断挑战计算能力的极限,解决相关能源消耗和碳足迹问题的责任也日益重大。这一责任延伸到了全球大型强子对撞机计算网格(WLCG),它包括 40 个国家的 170 多个站点,为大型强子对撞机实验提供重要的计算、磁盘、磁带存储和网络支持。除了性能指标之外,确保这些不同站点的高效运行也至关重要。本文介绍了 "HEP 基准 "套件,这是一个增强型套件,旨在使用 "HEPScore23 "作为性能单位,统一测量所有 WLCG 场址的计算资源性能。该套件不仅仅通过 HEPScore23 评估执行速度。事实上,该套件还包括机器负载、内存使用、内存交换等指标,尤其是功耗。该工具的适应性和用户友好界面使其在进行基准测试的同时,还能全面获取系统相关数据。在整个 2023 年,该工具在多个 WLCG 站点进行了严格测试。重点是研究计算作业插槽性能,并将其与结构指标相关联。初步分析揭示了该工具在建立计算资源利用标准化模型方面的功效,同时还指出了通常由站点错误配置引起的异常情况。本文旨在阐明该工具的功能,并介绍通过广泛测试获得的结果。通过传播这些信息,目的是提高社区对这一探测模型的认识,促进更广泛的采用,鼓励负责任的计算实践,优先考虑性能和环境影响的缓解。
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HEP Benchmark Suite: Enhancing Efficiency and Sustainability in Worldwide LHC Computing Infrastructures
As the scientific community continues to push the boundaries of computing capabilities, there is a growing responsibility to address the associated energy consumption and carbon footprint. This responsibility extends to the Worldwide LHC Computing Grid (WLCG), encompassing over 170 sites in 40 countries, supporting vital computing, disk, tape storage and network for LHC experiments. Ensuring efficient operational practices across these diverse sites is crucial beyond mere performance metrics. This paper introduces the HEP Benchmark suite, an enhanced suite designed to measure computing resource performance uniformly across all WLCG sites, using HEPScore23 as performance unit. The suite expands beyond assessing only the execution speed via HEPScore23. In fact the suite incorporates metrics such as machine load, memory usage, memory swap, and notably, power consumption. Its adaptability and user-friendly interface enable comprehensive acquisition of system-related data alongside benchmarking. Throughout 2023, this tool underwent rigorous testing across numerous WLCG sites. The focus was on studying compute job slot performance and correlating these with fabric metrics. Initial analysis unveiled the tool's efficacy in establishing a standardized model for compute resource utilization while pinpointing anomalies, often stemming from site misconfigurations. This paper aims to elucidate the tool's functionality and present the results obtained from extensive testing. By disseminating this information, the objective is to raise awareness within the community about this probing model, fostering broader adoption and encouraging responsible computing practices that prioritize both performance and environmental impact mitigation.
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