Lessons Learned from Building In Situ Coupling Frameworks
Lessons Learned from Building In Situ Coupling Frameworks
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从构建原位耦合框架中吸取的经验教训
DOI：
10.1145/2828612.2828622
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发表时间：
2015
期刊：
影响因子：
--
通讯作者：
B. Raffin
中科院分区：
文献类型：
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作者：
Matthieu Dorier;Matthieu Dreher;T. Peterka;J. Wozniak;Gabriel Antoniu;B. Raffin
在过去的几年里，大规模模拟产生的越来越多的数据促使人们从传统的离线数据分析转向现场分析和可视化。现场处理开始时是并行模拟与分析或可视化库的结合，主要是为了避免访问存储的高成本。除了这种简单的成对紧耦合之外，今天的复杂分析工作流是具有一个或多个数据源和几个相互连接的分析组件的图形。在本文中，我们回顾了我们为解决将模拟与可视化包或分析工作流相结合而开发的四个工具：Damaris、Decaf、FlowVR和SWIFT。这一自我批判性的调查旨在不仅揭示它们的潜力，而且最重要的是揭示这些框架和其他现场分析和可视化框架将面临的即将到来的软件挑战，以迈向艾级。
Over the past few years, the increasing amounts of data produced by large-scale simulations have motivated a shift from traditional offline data analysis to in situ analysis and visualization. In situ processing began as the coupling of a parallel simulation with an analysis or visualization library, motivated primarily by avoiding the high cost of accessing storage. Going beyond this simple pairwise tight coupling, complex analysis workflows today are graphs with one or more data sources and several interconnected analysis components. In this paper, we review four tools that we have developed to address the challenges of coupling simulations with visualization packages or analysis workflows: Damaris, Decaf, FlowVR and Swift. This self-critical inquiry aims to shed light not only on their potential, but most importantly on the forthcoming software challenges that these and other in situ analysis and visualization frameworks will face in order to move toward exascale.