Visualization Techniques for Large-Scale Monte Carlo Simulation

被引：0

作者：

Perry, Vincent ^{[1
]}

Gao, Wendy ^{[2
]}

Chen, Michael ^{[1
]}

Barton, J. Michael ^{[1
]}

Su, Simon ^{[1
]}

机构：

[1] US Army Res Lab, Aberdeen Proving Ground, MD 21005 USA

[2] Univ Maryland Baltimore Cty, Baltimore, MD 21228 USA

来源：

2019 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA) | 2019年

关键词：

Monte Carlo; simulation; high performance computing; in situ; virtual reality;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We present multiple modes of visualizing a large-scale Monte Carlo simulation. Due to disparity of the data, there is no one best visualization technique to understand the results of the simulation. By connecting the visualization methods directly to the simulation, we are able to visually analyze the simulation as it occurs in real time. This includes viewing the parameters of the model, the relationships among variables, and the 3D environment in which the simulation takes place. Furthermore, these environments may be coordinated for one seamless visual analytic experience.

引用

页码：3984 / 3991

页数：8

共 14 条

[1]

[Anonymous], 2019, React - A JavaScript library for building user interfaces

[2]

[Anonymous], 2019, PARAVIEWWEB JAVASCRI

[3]

[Anonymous], 2019, UNR ENG 4 DOC

[4]

Ayachit U., 2015, ISAV2015, P25, DOI [10.1145/2828612.2828624, DOI 10.1145/2828612.2828624, 10]

[5]

Childs H., 2012, HIGH PERFORMANCE VIS, P357

[6] In-Situ Feature Extraction of Large Scale Combustion Simulations Using Segmented Merge Trees [J].

Landge, Aaditya G. ;

Pascucci, Valerio ;

Gyulassy, Attila ;

Bennett, Janine C. ;

Kolla, Hemanth ;

Chen, Jacqueline ;

Bremer, Peer-Timo .

SC14: INTERNATIONAL CONFERENCE FOR HIGH PERFORMANCE COMPUTING, NETWORKING, STORAGE AND ANALYSIS, 2014, :1020-1031

[7]

North C., 2000, Proceedings of the the working conference on Advanced visual interfaces (AVI) 2000, P128, DOI [DOI 10.1145/345513.345282, 10.1145/345513.345282]

[8]

Richard J., 2018, HIP18030 HPCMP

[9]

Su S., 2018, ARLTR8504

[10]

Su S., 2018, SEARIS 2018 11 WORKS

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