In Situ Methods, Infrastructures, and Applications on High Performance Computing Platforms
In Situ Methods, Infrastructures, and Applications on High Performance Computing Platforms
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DOI：
10.1111/cgf.12930
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发表时间：
2016-06-01
影响因子：
2.5
通讯作者：
Bethel, E. W.
中科院分区：
文献类型：
--
作者：
Bauer, A. C.;Abbasi, H.;Bethel, E. W.
高性能计算（HPC）社区对分析和可视化数据而无需首先写入磁盘的相当大的兴趣，即。例如，原位处理是由于几个因素。首先是I/O成本节省，其中数据在生成时被分析/可视化，而无需首先存储到文件系统。其次是提高准确性的潜力，其中瞬态分析的精细时间采样可能暴露在粗略时间采样中遗漏的一些复杂行为。第三是在分析产品的计算中使用所有可用资源（CPU和加速器）的能力。这篇星星论文汇集了在极端规模HPC中使用原位方法的研究人员，开发人员和从业人员，旨在介绍现有的方法，基础设施以及使用原位分析和可视化的一系列计算科学和工程应用。
The considerable interest in the high performance computing (HPC) community regarding analyzing and visualization data without first writing to disk, i. e., in situ processing, is due to several factors. First is an I/O cost savings, where data is analyzed/visualized while being generated, without first storing to a filesystem. Second is the potential for increased accuracy, where fine temporal sampling of transient analysis might expose some complex behavior missed in coarse temporal sampling. Third is the ability to use all available resources, CPU's and accelerators, in the computation of analysis products. This STAR paper brings together researchers, developers and practitioners using in situ methods in extreme-scale HPC with the goal to present existing methods, infrastructures, and a range of computational science and engineering applications using in situ analysis and visualization.