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Post-processing and visualization of large-scale DEM simulation data with the open-source VELaSSCo platform

机译:具有开源Velassco平台的大规模DEM模拟数据的后处理和可视化

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Regardless of its origin, in the near future the challenge will not be how to generate data, but rather how to manage big and highly distributed data to make it more easily handled and more accessible by users on their personal devices. VELaSSCo (Visualization for Extremely Large-Scale Scientific Computing) is a platform developed to provide new visual analysis methods for large-scale simulations serving the petabyte era. The platform adopts Big Data tools/architectures to enable in-situ processing for analytics of engineering and scientific data and hardware-accelerated interactive visualization. In large-scale simulations, the domain is partitioned across several thousand nodes, and the data (mesh and results) are stored on those nodes in a distributed manner. The VELaSSCo platform accesses this distributed information, processes the raw data, and returns the results to the users for local visualization by their specific visualization clients and tools. The global goal of VELaSSCo is to provide Big Data tools for the engineering and scientific community, in order to better manipulate simulations with billions of distributed records. The ability to easily handle large amounts of data will also enable larger, higher resolution simulations, which will allow the scientific and engineering communities to garner new knowledge from simulations previously considered too large to handle. This paper shows, by means of selected Discrete Element Method (DEM) simulation use cases, that the VELaSSCo platform facilitates distributed post-processing and visualization of large engineering datasets.
机译:无论其起源如何,在不久的将来,挑战不会是如何生成数据的,而是如何管理大型和高度分布式数据,使其个人设备上的用户更容易处理和更容易访问。 Velassco(非常大规模的科学计算的可视化)是一个平台,为提供了为Petabyte Era提供的大型模拟提供了新的视觉分析方法。该平台采用大数据工具/架构,为工程和科学数据的分析和硬件加速的交互式可视化启用原位处理。在大规模模拟中,域在几千个节点上划分,数据(网格和结果)以分布式方式存储在这些节点上。 Velassco平台访问此分布式信息,处理原始数据,并将结果返回到用户的本地可视化客户端和工具。 Velassco的全球目标是为工程和科学界提供大数据工具,以便以数十亿个分布式记录更好地操纵模拟。轻松处理大量数据的能力还将实现更大,更高的分辨率模拟,这将允许科学和工程社区从以前考虑过大的模拟来获得新知识。本文通过选定的离散元素方法(DEM)仿真用例,该纸张显示了Velassco平台的促进了分布式后处理和大型工程数据集的可视化。

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