基于VTK的笔记本电脑高分辨率HPC仿真数据交互可视化与分析

J. Dubois, Guénolé Harel, Jacques-Bernard Lekien
{"title":"基于VTK的笔记本电脑高分辨率HPC仿真数据交互可视化与分析","authors":"J. Dubois, Guénolé Harel, Jacques-Bernard Lekien","doi":"10.1109/SciVis.2018.8823596","DOIUrl":null,"url":null,"abstract":"We present a highly efficient solution to interact with the Deep Water Impact Ensemble Data Set provided for the Scientific Visualization Contest 2018. Interactive visualization is made possible on one core of a laptop with the full resolution and the same accuracy as in the original data set, when originally 256 up to 2048 supercomputer nodes were required to generate the data. As far as we know this is the only way to achieve full-resolution exploration on a laptop. We first expose how our approach allows more efficient visualization by using the Tree-Based Adaptive Mesh Refinement grid data structure we introduced in VTK, vtkHyperTreeGrid [1], as compared to structured or unstructured approaches. Then we elaborate on the visualization capabilities offered by vtkHyperTreeGrid-optimized algorithms and the performance achieved on the limited resources available on a laptop. Next, we present how the hierarchical structure makes possible novel ways of exploring data interactively and helps achieve accelerated data exploration by hierarchically driving decimation of values. Finally, we show preliminary results of interactive volume rendering using splatting.","PeriodicalId":306021,"journal":{"name":"2018 IEEE Scientific Visualization Conference (SciVis)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Interactive Visualization and Analysis of High Resolution HPC Simulation Data on a Laptop With VTK\",\"authors\":\"J. Dubois, Guénolé Harel, Jacques-Bernard Lekien\",\"doi\":\"10.1109/SciVis.2018.8823596\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present a highly efficient solution to interact with the Deep Water Impact Ensemble Data Set provided for the Scientific Visualization Contest 2018. Interactive visualization is made possible on one core of a laptop with the full resolution and the same accuracy as in the original data set, when originally 256 up to 2048 supercomputer nodes were required to generate the data. As far as we know this is the only way to achieve full-resolution exploration on a laptop. We first expose how our approach allows more efficient visualization by using the Tree-Based Adaptive Mesh Refinement grid data structure we introduced in VTK, vtkHyperTreeGrid [1], as compared to structured or unstructured approaches. Then we elaborate on the visualization capabilities offered by vtkHyperTreeGrid-optimized algorithms and the performance achieved on the limited resources available on a laptop. Next, we present how the hierarchical structure makes possible novel ways of exploring data interactively and helps achieve accelerated data exploration by hierarchically driving decimation of values. Finally, we show preliminary results of interactive volume rendering using splatting.\",\"PeriodicalId\":306021,\"journal\":{\"name\":\"2018 IEEE Scientific Visualization Conference (SciVis)\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE Scientific Visualization Conference (SciVis)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SciVis.2018.8823596\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE Scientific Visualization Conference (SciVis)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SciVis.2018.8823596","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

我们提出了一种高效的解决方案,用于与为2018年科学可视化竞赛提供的深水撞击集成数据集进行交互。交互式可视化可以在笔记本电脑的一个核心上实现,具有与原始数据集相同的全分辨率和精度,而最初需要256到2048个超级计算机节点来生成数据。据我们所知,这是在笔记本电脑上实现全分辨率探索的唯一途径。与结构化或非结构化方法相比,我们首先暴露了我们的方法如何通过使用我们在VTK, vtkHyperTreeGrid[1]中引入的基于树的自适应网格细化网格数据结构来实现更有效的可视化。然后,我们详细介绍了vtkhypertreeggrid优化算法提供的可视化功能以及在笔记本电脑有限的可用资源上实现的性能。接下来,我们将介绍分层结构如何使交互式探索数据的新方法成为可能,并通过分层驱动值的抽取来帮助实现加速数据探索。最后,我们展示了使用飞溅的交互式体绘制的初步结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Interactive Visualization and Analysis of High Resolution HPC Simulation Data on a Laptop With VTK
We present a highly efficient solution to interact with the Deep Water Impact Ensemble Data Set provided for the Scientific Visualization Contest 2018. Interactive visualization is made possible on one core of a laptop with the full resolution and the same accuracy as in the original data set, when originally 256 up to 2048 supercomputer nodes were required to generate the data. As far as we know this is the only way to achieve full-resolution exploration on a laptop. We first expose how our approach allows more efficient visualization by using the Tree-Based Adaptive Mesh Refinement grid data structure we introduced in VTK, vtkHyperTreeGrid [1], as compared to structured or unstructured approaches. Then we elaborate on the visualization capabilities offered by vtkHyperTreeGrid-optimized algorithms and the performance achieved on the limited resources available on a laptop. Next, we present how the hierarchical structure makes possible novel ways of exploring data interactively and helps achieve accelerated data exploration by hierarchically driving decimation of values. Finally, we show preliminary results of interactive volume rendering using splatting.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信