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Fine-grained processing towards HL-LHC computing in ATLAS

机译:在地图集的HL-LHC计算的细粒度处理

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During LHC's Run-2 ATLAS has been developing and evaluating new fine-grained approaches to workflows and dataflows able to better utilize computing resources in terms of storage, processing and networks. The compute-limited physics of ATLAS has driven the collaboration to aggressively harvest opportunistic cycles from what are often transiently available resources, including HPCs, clouds, volunteer computing, and grid resources in transitional states. Fine-grained processing (with typically a few minutes' granularity, corresponding to one event for the present ATLAS full simulation) enables agile workflows with a light footprint on the resource such that cycles can be more fully and efficiently utilized than with conventional workflows processing O(GB) files per job. The workflow component of this approach, the ATLAS Event Service, is currently in production on some grid sites and on several supercomputing sites. The Event Service architecture allows real-time delivery of fine-grained workloads to payload applications running on compute nodes. The outputs produced by the payload applications are immediately streamed out into a secure location, such that Event Service jobs can be terminated practically at any time with minimal data losses. On HPCs the architecture gives us the flexibility to dynamically vary the size of submitted jobs from several up to thousands of concurrent nodes and the duration of jobs from less than an hour (backfill jobs) to multiple hours, thus maximizing the utilization of the machine by ensuring every processing unit remains productively occupied. The architecture is an HPC-internal, MPI-based version of the highly scalable global workload management system of ATLAS which presently manages up to 1.2 million concurrent processors around the clock. This makes it a proven scalable candidate for exascale computing, which is expected to be an important element of LHC Run-3 computing from 2021 and HL-LHC from 2026. Today the R&D attention of the
机译:在LHC的Run-2 Atlas期间,已经开发和评估了能够在存储,处理和网络方面更好地利用计算资源的工作流程和数据流的新细粒度方法。 Atlas的计算有限的物理驱动了合作,从经常可用的资源,包括HPC,云,志愿者计算和转型状态的网格资源,积极收获机会循环。细粒度处理(通常为几分钟的粒度,对应于当前阿特拉斯的一个事件完整仿真)使得能够在资源上具有光占地面积,使得循环可以更充分和有效地利用与传统的工作流程处理o更完整有效地利用(GB)每个作业的文件。此方法的工作流组件是Atlas事件服务,目前在一些网格站点和几个超级计算站点上的生产中。事件服务架构允许实时将微粒工作负载传送到运行在计算节点上的有效载荷应用程序。由有效载荷应用程序产生的输出立即将其流输出到安全位置,使得事件服务作业可以实际上随时终止,数据丢失最小。在HPC上,该架构使我们能够灵活地将所提交的作业的大小从多达数千个并发节点和工作时间(回填作业)到多个小时的作业持续时间变化,从而最大限度地提高机器的利用率确保每个处理单元仍然高效占用。该架构是一个HPC-INTERINE,基于MPI的高度可扩展全球工作负载管理系统的MPI版本,目前在时钟周围管理高达120万的并发处理器。这使得它成为ExaScale计算的证明可扩展候选者,这预计将成为2021年和HL-LHC的LHC运行3计算的重要因素。今天的研发注意力

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