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ieee symposium on visualization for Cyber Security (VizSec)

作者： Subramanian, Siva Sandeep Pushparaj, Parab Liu, Zerong Lu, Aidong Univ N Carolina Dept Comp Sci Charlotte NC 28223 USA

ISBN: (纸本)9781728138763

Online social networks are prone to be targeted by various frauds and attacks, which are difficult to detect due to their complexity and variations. The challenge is to make sense of all information with suitable exploration tools for different groups of users. This project focuses on an explainable visualization approach to study collaborative behaviors of vandal users on Wikipedia. Our approach creates visualization with commonly used techniques from cartography and statistical graphics that are familiar to the general public for effectiveness and explainability. We have built a large-scale visualization system which supports an illustrative interface with multiple data query, filtering, analysis, and interactive exploration functions. Examples and case studies are provided to demonstrate that our approach can be used effectively for a set of Wikipedia behavior analysis tasks.

关键词： Human-centered computing-visualization-visualization techniques Human-centered computing-visualization-visualization design and evaluation methods

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Homogeneity Guided Probabilistic data Summaries for Analysis and visualization of large-Scale data Sets 10

Homogeneity Guided Probabilistic Data Summaries for Analysis...

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ieee Pacific visualization symposium (ieee PacificVis)

作者： Dutta, Soumya Woodring, Jonathan Shen, Han-Wei Chen, Jen-Ping Ahrens, James Ohio State Univ Columbus OH 43210 USA Los Alamos Natl Lab Los Alamos NM USA

ISBN: (纸本)9781509057382

High-resolution simulation data sets provide plethora of information, which needs to be explored by application scientists to gain enhanced understanding about various phenomena. Visual-analytics techniques using raw data sets are often expensive due to the data sets' extreme sizes. But, interactive analysis and visualization is crucial for big data analytics, because scientists can then focus on the important data and make critical decisions quickly. To assist efficient exploration and visualization, we propose a new region-based statistical data summarization scheme. Our method is superior in quality, as compared to the existing statistical summarization techniques, with a more compact representation, reducing the overall storage cost. The quantitative and visual efficacy of our proposed method is demonstrated using several data sets along with an in situ application study for an extreme-scale flow simulation.

关键词： I.3 [COMPUTER graphics]: Picture/Image Generation-Display algorithms G.3 [PROBABILITY AND STATISTICS]: Distribution functions-Statistical computing

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Eurographics symposium on parallel graphics and visualization, EGPGV 2007

Eurographics Symposium on Parallel Graphics and Visualizatio...

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7th Eurographics symposium on parallel graphics and visualization, EGPGV 2007

ISBN: (纸本)9783905673500

The proceedings contain 13 papers. The topics discussed include: multiresolution visualization of massive models on a large spatial 3D display;distributed collaborative data analysis with heterogeneous visualization systems;direct send compositing for parallel sort-last rendering;interactive particle visualization with advanced shading models using lazy evaluation;scalable sort-first parallel direct volume rendering with dynamic load balancing;dynamic regions of interest for interactive flow exploration;work stealing for time-constrained octree exploration: application to real-time 3D modeling;exploiting parallelism in physically-based simulations on multi-core processor architectures;parallel reflective symmetry transformation for volume data;and asynchronous BVH construction for ray tracing dynamic scenes on parallel multi-core architectures.

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Eurographics Workshop on parallel graphics and visualization

Eurographics Workshop on Parallel Graphics and Visualization

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2016 Eurographics symposium on parallel graphics and visualization, EGPGV 2016

ISBN: (纸本)9783038680062

The proceedings contain 10 papers. The topics discussed include: adaptive collision culling for large-scale simulations by a parallel sweep and prune algorithm;external face-list calculation with data-parallel primitives;parallel spatial splits in bounding volume hierarchies;interacting with large distributed datasets using sketch;high-performance mesh partitioning and ghost cell generation for visualization software;web-enabled server-based and distributed real-time ray-tracing;a scalable streamline generation algorithm via flux-based isocontour extraction;dynamically scheduled region-based image compositing;dynamic work packages in parallel rendering;and data mining tornado-genesis precursors.

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A hardware-assisted scalable solution for interactive volume rendering of time-varying data

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ieee TRANSACTIONS ON visualization AND COMPUTER graphics 2002年第3期8卷 286-301页

作者： Lum, EB Ma, KL Clyne, J Univ Calif Davis CIPIC Davis CA 95616 USA Univ Calif Davis Dept Comp Sci Davis CA 95616 USA Natl Ctr Atmospher Res Boulder CO 80303 USA

We present a scalable volume rendering technique that exploits lossy compression and low-cost commodity hardware to permit highly interactive exploration of time-varying scalar volume data. A palette-based decoding technique and an adaptive bit allocation scheme are developed to fully utilize the texturing capability of a commodity 3D graphics card. Using a single PC equipped with a modest amount of memory, a texture capable graphics card, and an inexpensive disk array, we are able to render hundreds of time steps of regularly gridded volume data (up to 42 million voxels each time step) at interactive rates. By clustering multiple PCs together, we demonstrate the data-size scalability of our method. The frame rates achieved make possible the interactive exploration of data in the temporal, spatial, and transfer function domains. A comprehensive evaluation of our method based on experimental studies using data sets (up to 134 million voxels per time step) from turbulence flow simulations is also presented.

关键词： compression disk I/O high performance computing out-of-core processing parallel rendering PC scalable algorithms scientific visualization texture hardware time-varying data transform encoding volume rendering

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Cubic Gradient-Based Material Interfaces

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ieee TRANSACTIONS ON visualization AND COMPUTER graphics 2013年第10期19卷 1687-1699页

作者： Prilepov, Iuri Obermaier, Harald Deines, Eduard Garth, Christoph Joy, Kenneth I. Univ Calif Davis Dept Comp Sci Inst Data Anal & Visualizat Davis CA 95616 USA CD Adapco Austin TX 78750 USA Tech Univ Kaiserslautern D-67653 Kaiserslautern Germany

Multifluid simulations often create volume fraction data, representing fluid volumes per region or cell of a fluid data set. Accurate and visually realistic extraction of fluid boundaries is a challenging and essential task for efficient analysis of multifluid data. In this work, we present a new material interface reconstruction method for such volume fraction data. Within each cell of the data set, our method utilizes a gradient field approximation based on trilinearly blended Coons-patches to generate a volume fraction function, representing the change in volume fractions over the cells. A continuously varying isovalue field is applied to this function to produce a smooth interface that preserves the given volume fractions well. Further, the method allows user-controlled balance between volume accuracy and physical plausibility of the interface. The method works on two-and three-dimensional Cartesian grids, and handles multiple materials. Calculations are performed locally and utilize only the one-ring of cells surrounding a given cell, allowing visualizations of the material interfaces to be easily generated on a GPU or in a large-scale distributed parallel environment. Our results demonstrate the robustness, accuracy, and flexibility of the developed algorithms.

关键词： visualization boundary representations computational geometry and object modeling

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A study of I/O methods for parallel visualization of large-scale data

A study of I/O methods for parallel visualization of large-s...

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symposium on parallel graphics and visualization

作者： Yu, HF Ma, KL Univ Calif Davis Dept Comp Sci Davis CA 95616 USA

This paper presents two parallel I/O methods for the visualization of time-varying volume data in a high-performance computing environment. We discuss the interplay between the parallel renderer, I/O strategy, and file system, and show the results of our study on the performance of the I/O strategies with and without MPI parallel I/O support. The targeted application is earthquake modeling using a large 3D unstructured mesh consisting of one hundred millions cells. Our test results on the HP/Cornpaq AlphaServer operated at the Pittsburgh Supercomputing Center demonstrate that the I/O methods effectively remove the I/O bottlenecks commonly present in time-varying data visualization, and therefore help significantly lower interfrarne delay. This high-performance visualization solution allows scientists to explore their data in the temporal, spatial, and visualization domains at high resolution. Such new explorability, likely not presently available to most computational science groups, will help lead to many new insights into the modeled physical and chemical processes. (c) 2005 Elsevier B.V. All rights reserved.

关键词： high-performance computing massively parallel supercomputing MPI scientific visualization parallel I/O parallel rendering time-varying data volume rendering

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Redirecting research in large-format displays for visualization

Redirecting research in large-format displays for visualizat...

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2nd symposium on large-Scale data Analysis and visualization, LDAV 2012

作者： Moreland, Kenneth

ISBN: (纸本)9781467347334

large-format displays, in particular tiled displays, remain actively used and researched today after almost two decades since their conception. Many government, academic, and commercial entities have invested considerably in the construction and use of large-format displays. During this time we have developed new applications but have also discovered faulty assumptions. This position paper evaluates the most important lessons learned from early and recent research in large-format displays. Each lesson suggests a direction for future research, which generally takes the form of a more user- and application-centric focus. © 2012 ieee.

关键词： large format DISPLAYING visualization redirection

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Robust Tracing and visualization of Heterogeneous Microvascular Networks

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ieee TRANSACTIONS ON visualization AND COMPUTER graphics 2019年第4期25卷 1760-1773页

作者： Govyadinov, Pavel A. Womack, Tasha Eriksen, Jason L. Chen, Guoning Mayerich, David Univ Houston Dept Comp Sci Houston TX 77031 USA Univ Houston Dept Pharmacol & Pharmaceut Sci Houston TX 77031 USA Univ Houston Dept Elect & Comp Engn Houston TX 77031 USA

Advances in high-throughput imaging allow researchers to collect three-dimensional images of whole organ microvascular networks. These extremely large images contain networks that are highly complex, time consuming to segment, and difficult to visualize. In this paper, we present a framework for segmenting and visualizing vascular networks from terabyte-sized three-dimensional images collected using high-throughput microscopy. While these images require terabytes of storage, the volume devoted to the fiber network is approximate to 4 percent of the total volume size. While the networks themselves are sparse, they are tremendously complex, interconnected, and vary widely in diameter. We describe a parallel GPU-based predictor-corrector method for tracing filaments that is robust to noise and sampling errors common in these data sets. We also propose a number of visualization techniques designed to convey the complex statistical descriptions of fibers across large tissue sections-including commonly studied microvascular characteristics, such as orientation and volume.

关键词： Microvessel network tracking glyph visualization predictor-corrector segmantation spherical harmonics superquadrics KESM

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Task-based Augmented Merge Trees with Fibonacci Heaps 7

Task-based Augmented Merge Trees with Fibonacci Heaps

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ieee 7th symposium on large data Analysis and visualization (LDAV)

作者： Gueunet, Charles Fortin, Pierre Jomier, Julien Tierny, Julien UPMC Univ Paris 06 Sorbonne Univ CNRS Kitware SASLIP6UMR 7606 Paris France UPMC Univ Paris 06 Sorbonne Univ CNRS LIP6UMR 7606 Paris France Kitware SAS Villeurbanne France

ISBN: (纸本)9781538606179

This paper presents a new algorithm for the fast, shared memory multi-core computation of augmented merge trees on triangulations. In contrast to most existing parallel algorithms, our technique computes augmented trees. This augmentation is required to enable the full extent of merge tree based applications, including data segmentation. Our approach completely revisits the traditional, sequential merge tree algorithm to re-formulate the computation as a set of independent local tasks based on Fibonacci heaps. This results in superior time performance in practice, in sequential as well as in parallel thanks to the OpenMP task runtime. In the context of augmented contour tree computation, we show that a direct usage of our merge tree procedure also results in superior time performance overall, both in sequential and parallel. We report performance numbers that compare our approach to reference sequential and multi-threaded implementations for the computation of augmented merge and contour trees. These experiments demonstrate the runtime efficiency of our approach as well as its scalability on common workstations. We demonstrate the utility of our approach in data segmentation applications. We also provide a lightweight VTK-based C++ implementation of our approach for reproduction purposes.

关键词： Algorithm design and analysis data analysis data visualization Feature extraction Electronic mail Runtime

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