Experiences with Cross-Facility Real-Time Light Source Data Analysis Workflows

Anna Giannakou, Johannes P. Blaschke, Deborah Bard, L. Ramakrishnan
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引用次数: 9

Abstract

We are seeing a growth in scientific data from experimental and observational facilities that are resulting in significant new computational patterns and needs. For example, scientists running experiments at light sources, often analyses workflows require near real-time access to compute resources in order to obtain results used for re-configuring on-going experiments. These workflows often have requirements that are different from the traditional large-scale parallel applications that have traditionally run at HPC centers. In this paper, we present our experiences supporting two light source data analysis workflows that run on HPC resources at National Energy Research Scientific Computing Center. We discuss the characteristics of workflows, runtime requirements and associated execution challenges when running on HPC environments. We present a discussion and a summary of best practices that address execution challenges and current and future solutions for leveraging HPC resources for near real-time data analysis.
具有跨设施实时光源数据分析工作流程的经验
我们看到来自实验和观测设施的科学数据正在增长,这导致了重要的新计算模式和需求。例如,科学家在光源下进行实验,通常分析工作流程需要接近实时访问计算资源,以便获得用于重新配置正在进行的实验的结果。这些工作流通常具有不同于传统的在HPC中心运行的大规模并行应用程序的需求。在本文中,我们介绍了我们在国家能源研究科学计算中心的高性能计算资源上支持两个光源数据分析工作流的经验。我们将讨论在HPC环境中运行时工作流的特征、运行时需求和相关的执行挑战。我们讨论并总结了解决执行挑战的最佳实践,以及利用HPC资源进行近实时数据分析的当前和未来解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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