The 8th IEEE Symposium on Large Data Analysis and Visualization
in conjunction with IEEE VIS 2018, Berlin, Germany, October 21, 2018

Program – Symposium

October 21, 2018, Room: Conv 1, Sec D

9:00 – 9:10 am Opening Remarks
9:10 – 10:15 pm

Keynote Presentation

Large Data Analysis and Visualization – New Approaches for Dynamic Volumes and Particle Data Sets
Prof. Dr. Thomas Ertl, University of Stuttgart Details
10:15 – 10:40 am

Session: Uncertain Data

(Chair: Hanqi Guo)
  • Visual Analysis of Simulation Uncertainty Using Cost-Effective Sampling.
    Annie Preston, Yiran Li, Franz Sauer, Kwan-Liu Ma
10:40 – 11:00 amBreak
11:00 – 11:50 am

Session: Data Reduction

(Chair: Peer-Timo Bremer)
  • VOIDGA: A View-Approximation Oriented Image Database Generation Approach.
    Jonas Lukasczyk, Eric Kinner, James Ahrens, Heike Leitte, Christoph Garth
  • Lifted Wasserstein Matcher for Fast and Robust Topology Tracking.
    Maxime Soler, Mélanie Plainchault, Bruno Conche, Julien Tierny
11:50 – 12:40 pm

Panel

Progressive Visualization and Visual Analytics
Progressive visualization, also known as Online Aggregation, consists of splitting long and expensive computations into a series of approximate results improving with time; in this process, partial or approximate results are then rapidly returned to the user and can be interacted with in a fluent and iterative fashion. With the increasing growth in data, such progressive data analysis approaches will become one of the leading paradigms for data exploration systems, but it also will require major changes in the algorithms, data structures, and visualization tools used today. In early October 2018, a Dagstuhl Seminar explored progressive visualization; in this panel, speakers from that seminar will share outcomes from that conversation, and explore ways the LDAV community can adapt these approaches.
12:40 – 2:20 pm Lunch
2:20 – 4:00 pm

Session: Parallelism & Approximation

(Chair: Steffen Frey)
  • DPP-PMRF: Rethinking Optimization for a Probabilistic Graphical Model Using Data-Parallel Primitives.
    Brenton Lessley, Talita Perciano, Colleen Heinemann, David Camp, Hank Childs, E. Wes Bethel
  • Parallel Partial Reduction for Large-Scale Data Analysis and Visualization.
    Wenbin He, Hanqi Guo, Tom Peterka, Sheng Di, Franck Cappello, Han-Wei Shen
  • Comparing Binary-Swap Algorithms for Odd Factors of Processes.
    Kenneth Moreland
  • Foundations of Multivariate Functional Approximation for Scientific Data.
    Tom Peterka, Youssef S. G. Nashed, Iulian Grindeanu, Vijay S. Mahadevan, Raine Yeh, Xavier Tricoche
4:00 – 4:20 pm Break
4:20 – 5:35 pm

Session: Fidelity & Interactivity

(Chair: Tom Peterka)
  • Galaxy: Asynchronous Ray Tracing for Large High-Fidelity Visualization.
    Greg Abram, Paul Navrátil, Pascal Grossett, David Rogers, James Ahrens
  • SpRay: Speculative Ray Scheduling for Large Data Visualization.
    Hyungman Park, Donald Fussell, Paul Navrátil
  • Adaptive Encoder Settings for Interactive Remote Visualisation on High-Resolution Displays.
    Florian Frieß, Mathias Landwehr, Valentin Bruder, Steffen Frey, Thomas Ertl
5:35 – 5:45 pm Best Paper Award & Closing Remarks
7:00 - 9:00 pm

LDAV Poster Session (included in Vis Opening Reception)


Posters:
  • A Flow Visualization Using Parallel 3D Line Integral Convolution for Large Scale Unstructured Grid Data.
    Yangguang Liao, Hiroaki Matsui, Oliver Kreylos, Louise H. Kellogg
  • A Comprehensive Informative Metric for Summarizing HPC System.
    Yawei Hui, Byung Hoon Park, Christian Engelmann
  • Complexity Estimation of Feature Tracking Data.
    Dirk Norbert Helmrich, Andrea Schnorr, Torsten Wolfgang Kuhlen, Bernd Hentschel
  • Towards In-Situ Vortex Identification for Peta-Scale CFD using Contour Trees.
    Marius Koch, Paul H. J. Kelly, Peter E. Vincent
  • Method for Improving RadViz's Navigation Function Based on Focusing and Filtering.
    Hyunwoo Han, Taerin Yoon, Hyoji Ha, Juwon Hong, Kyungwon Lee
  • Exploring Visualization Techniques with HACC Simulation Data.
    D. Adamo, J. D. Emberson, Edouard Brooks, Silvio Rizzi, Joseph Insley, Michael E. Papka
  • In Situ Visualization and Analysis to Design Large Scale Experiments in Computational Fluid Dynamics.
    Bennett Bernardoni, Nicola Ferrier, Joseph Insley, Michael E. Papka, Saumil Patel, Silvio Rizzi
  • Comparison of Multiple Large Fluid-Structure Interaction Simulations in Virtual Reality.
    Daniel Orban, Seth A Johnson, Hakizumwami Birali Runesha, Lingyu Meng, Bethany Juhnke, Arthur Guy Erdman, Francesca Samsel, Daniel F. Keefe
  • Citation Network Visualization of Reference Papers based on Influence.
    Gyeongcheol Choi, Suhyun Lim, Taerin Yoon, Kyungwon Lee
  • A Large Data Visualization Framework for SPARC64 fx HPC Systems – Case Study: K Computer Operational Environment.
    Jorji Nonaka, Kenji Ono, Naohisa Sakamoto, Kengo Hayashi, Motohiko Matsuda, Fumiyoshi Shoji, Kentaro Oku, Masahiro Fujita, Kazuma Hatta

Keynote

Large Data Analysis and Visualization –
New Approaches for Dynamic Volumes and Particle Data Sets
Prof. Dr. Thomas Ertl – Visualization Research Center, University of Stuttgart, Germany

As data set sizes and complexity continue to grow, more elaborate techniques for their interactive analysis and visualization are being developed in our community. This talk presents some of the recent contributions of the VISUS group at the University of Stuttgart focusing on dynamic volumes and particle data sets. For volumes we exploit similarity between time steps to select the most important characteristic temporal features, while still allowing exploration, and we develop intermediate view dependent representations for hybrid in situ approaches. New adaptive volume rendering algorithms allow for maintaining interactive frame rates by balancing quality and sampling errors. For large particle data sets, we present multi-GPU techniques for static astrophysical datasets of more than trillions of particles; and for dynamic molecular trajectories we elaborate on the OSPRay integration into our Megamol framework. We conclude with our first attempts to learn interesting features in volumetric time series and performance characteristics of visual computing systems.

Speaker

Thomas Ertl received a MSc in computer science from the University of Colorado at Boulder and a PhD in theoretical astrophysics from the University of Tübingen. Since 1999 he is a full professor of computer science at the University of Stuttgart in the Visualization and Interactive Systems Institute (VIS) and the Visualization Research Center (VISUS). Currently, he serves as Vice President of Research of the University of Stuttgart. His research interests include visualization, computer graphics and human computer interaction in general with a focus on volume rendering, flow and particle visualization, parallel and hardware accelerated graphics, large datasets and interactive steering, visual analytics of text collections and social media, user interfaces and navigation systems for the blind. Thomas Ertl served on numerous program committees and as a papers co-chair for most conferences in the field. From 2007-2010 he was Editor-in-Chief of the IEEE Transactions on Visualization and Graphics (TVCG) and in 2011/2012 he served as Chairman of the Eurographics Association. He received the Outstanding Technical Contribution Award and the Distinguished Career Award of the Eurographics Association and the Technical Achievement Award of the IEEE Visualization and Graphics Technical Committee. In 2007 he was elected as a Member of the Heidelberg Academy of Sciences and Humanities. He received Honorary Doctorates from the Vienna University of Technology in 2011 and from the University of Magdeburg in 2014.