A. P. Yzquierdo, M. Mascheroni, Edita Kizinevič, F. Khan, Hyunwoo Kim, M. A. Flechas, Nikos Tsipinakis, Saqib Haleem
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引用次数: 0
摘要
大型强子对撞机实验的计算资源需求预计将在运行3阶段和HL-LHC时代继续大幅增长。随着高性能计算(HPC)和云计算资源在总计算能力中所占比例越来越大,可用资源的格局也将发生变化。未来几年,无论是在可扩展性还是在日益增加的复杂性方面,实验的资源供应模式都将面临挑战。CMS 提交基础设施(SI)为 CMS 工作流提供计算资源。该基础设施建立在一组联合 HTCondor 池的基础上,目前共有 40 万个 CPU 内核,分布在全球各地,支持同时执行 20 多万个计算任务。将高性能计算资源纳入 CMS 计算首先是一项整合挑战,因为与网格站点相比,高性能计算中心更加多样化。其次,在保持全局灵活性和效率的前提下,将目前的 SI(利用当前 CMS 计算能力的尺寸)发展到 HLLHC 阶段所需的资源规模,将是 SI 面临的另一项挑战。为了预防性地解决未来潜在的可扩展性限制,SI 团队定期进行测试,以探索我们基础设施的最大范围。本说明概述了将高性能计算资源整合到 CMS 离线计算中的情况,描述了因运行规模扩大而可能引起的 SI 问题,并报告了 CMS SI 可扩展性测试的最新结果。
HPC resources for CMS offline computing: An integration and scalability challenge for the Submission Infrastructure
The computing resource needs of LHC experiments are expected to continue growing significantly during the Run 3 and into the HL-LHC era. The landscape of available resources will also evolve, as High Performance Computing (HPC) and Cloud resources will provide a comparable, or even dominant, fraction of the total compute capacity. The future years present a challenge for the experiments’ resource provisioning models, both in terms of scalability and increasing complexity. The CMS Submission Infrastructure (SI) provisions computing resources for CMS workflows. This infrastructure is built on a set of federated HTCondor pools, currently aggregating 400k CPU cores distributed worldwide and supporting the simultaneous execution of over 200k computing tasks. Incorporating HPC resources into CMS computing represents firstly an integration challenge, as HPC centers are much more diverse compared to Grid sites. Secondly, evolving the present SI, dimensioned to harness the current CMS computing capacity, to reach the resource scales required for the HLLHC phase, while maintaining global flexibility and efficiency, will represent an additional challenge for the SI. To preventively address future potential scalability limits, the SI team regularly runs tests to explore the maximum reach of our infrastructure. In this note, the integration of HPC resources into CMS offline computing is summarized, the potential concerns for the SI derived from the increased scale of operations are described, and the most recent results of scalability test on the CMS SI are reported.