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parallel clustering for visualizing large scientific line data

Parallel clustering for visualizing large scientific line da...

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ieee symposium on large data Analysis and visualization (LDAV)

作者： Jishang Wei Hongfeng Yu Jacqueline H. Chen Kwan-Liu Ma University of California Davis USA Sandia National Laboratories USA

Scientists often need to extract, visualize and analyze lines from vast amounts of data to understand dynamic structures and interactions. The effectiveness of such a visual validation and analysis process mainly relies on a good strategy to categorize and visualize the lines. However, the sheer size of line data produced by state-of-the-art scientific simulations poses great challenges to preparing the data for visualization. In this paper, we present a parallelization design of regression model-based clustering to categorize large line data derived from detailed scientific simulations by leveraging the power of heterogeneous computers. This parallel clustering method employs the Expectation Maximization algorithm to iteratively approximate the optimal data partitioning. First, we use a sorted-balance algorithm to partition and distribute the lines with various lengths among multiple compute nodes. During the following iterative clustering process, regression model parameters are recovered based on the local lines on each individual node, with only a few inter-node message exchanges involved. Meanwhile, the workload of regression model computing is well balanced across the nodes. The experimental results demonstrate that our approach can effectively categorize large line data in a scalable manner to concisely convey dynamic structures and interactions, leading to a visualization that captures salient features and suppresses visual clutter to facilitate scientific exploration of large line data.

关键词： Mathematical model Vectors Clustering algorithms data visualization data models graphics processing unit Computational modeling

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STREAMIT: Dynamic visualization and interactive exploration of text streams

STREAMIT: Dynamic visualization and interactive exploration ...

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Pacific (formerly Asia-Pacific APVIS) visualization symposium

作者： Jamal Alsakran Yang Chen Ye Zhao Jing Yang Dongning Luo Kent University USA North Carolina State University Charlotte USA

Text streams demand an effective, interactive, and on-the-fly method to explore the dynamic and massive data sets, and meanwhile extract valuable information for visual analysis. In this paper, we propose such an interactive visualization system that enables users to explore streaming-in text documents without prior knowledge of the data. The system can constantly incorporate incoming documents from a continuous source into existing visualization context, which is “physically” achieved by minimizing a potential energy defined from similarities between documents. Unlike most existing methods, our system uses dynamic keyword vectors to incorporate newly-introduced keywords from data streams. Furthermore, we propose a special keyword importance that makes it possible for users to adjust the similarity on-the-fly, and hence achieve their preferred visual effects in accordance to varying interests, which also helps to identify hot spots and outliers. We optimize the system performance through a similarity grid and with parallel implementation on graphics hardware (GPU), which achieves instantaneous animated visualization even for a very large data collection. Moreover, our system implements a powerful user interface enabling various user interactions for in-depth data analysis. Experiments and case studies are presented to illustrate our dynamic system for text stream exploration.

关键词： visualization Dynamics Animation data visualization Computational modeling Layout graphics processing unit

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Volume graphics 2010 - 8th ieee/EG International symposium on Volume graphics

Volume Graphics 2010 - 8th IEEE/EG International Symposium o...

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8th ieee/EG International symposium on Volume graphics, Volume graphics 2010, Co-located with the Annual Conference of the European Association for Computer graphics, Eurographics 2010

ISBN: (纸本)9783905674217

The proceedings contain 16 papers. The topics discussed include: a new sampling scheme for slice based volume rendering;multi-layer volume ray casting on GPU;wavelet-based multi resolution isosurface rendering;split-voxel: a simple discontinuity-preserving voxel representation for volume rendering;real-time surface analysis and tagged material cleansing for virtual colonoscopy;slimming brick cache strategies for seismic horizon propagation algorithms;volumetric evaluation of meshless data from smoothed particle hydrodynamics simulations;concurrent volume visualization of real-time fMRI;fast volumetric data exploration with importance-based accumulated transparency modulation;multi-dimensional reduction and transfer function design using parallel coordinates;a survey of transfer functions suitable for volume rendering;feature-driven ambient occlusion for direct volume rendering;and GPU-supported lossless compression scheme for rendering time-varying volume data.

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large Program Trace Analysis and Compression with ZDDs

Large Program Trace Analysis and Compression with ZDDs

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8th International symposium on Code Generation and Optimization

作者： Price, Graham Vachharajani, Manish Univ Colorado Dept Elect & Comp Engn Boulder CO 80309 USA

ISBN: (纸本)9781605586359

Prior work has shown that reduced, ordered, binary decision diagrams (BDDs) can be a powerful tool for program trace analysis and visualization. Unfortunately, it can take hours or days to encode large traces as BDDs. Further, techniques used to improve BDD performance are inapplicable to large dynamic program traces. This paper explores the use of ZDDs for compressing dynamic trace data. Prior work has show that ZDDs can represent sparse data sets with less memory compared to BDDs. This paper demonstrates that (1) ZDDs do indeed provide greater compression for sets of dynamic traces (25% smaller than BDDs on average), (2) with proper tuning, ZDDs encode sets of dynamic trace data over 9 x faster than BDDs, and (3) ZDDs can be used for

关键词： parallel programming trace compression

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VAST 09 - ieee symposium on Visual Analytics Science and Technology, proceedings

VAST 09 - IEEE Symposium on Visual Analytics Science and Tec...

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VAST 09 - ieee symposium on Visual Analytics Science and Technology

ISBN: (纸本)9781424452835

The proceedings contain 56 papers. The topics discussed include: interactive visual clustering of large collections of trajectories;proximity-based visualization of movement trace data;guided analysis of hurricane trends using statistical processes integrated with interactive parallel coordinates;finding comparable temporal categorical records: a similarity measure with an interactive visualization;a visual analytics system for radio frequency fingerprinting-based localization;combining automated analysis and visualization techniques for effective exploration of high-dimensional data;two-stage framework for visualization of clustered high dimensional data;model space visualization for multivariate linear trend discovery;parallel tag clouds to explore and analyze faceted text corpora;describing story evolution from dynamic information streams;VAST contest dataset use in education;evaluating visual analytics systems for investigative analysis: deriving design principles from a case study;and visual analysis of graphs with multiple connected components.

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parallel tag clouds to explore and analyze faceted text corpora

Parallel tag clouds to explore and analyze faceted text corp...

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VAST 09 - ieee symposium on Visual Analytics Science and Technology

作者： Collins, Christopher Viégas, Fernanda B. Wattenberg, Martin University of Toronto Canada IBM Research

ISBN: (纸本)9781424452835

Do court cases differ from place to place? What kind of picture do we get by looking at a country's collection of law cases? We introduce parallel Tag Clouds: a new way to visualize differences amongst facets of very large metadata-rich text corpora. We have pointed parallel Tag Clouds at a collection of over 600,000 US Circuit Court decisions spanning a period of 50 years and have discovered regional as well as linguistic differences between courts. The visualization technique combines graphical elements from parallel coordinates and traditional tag clouds to provide rich overviews of a document collection while acting as an entry point for exploration of individual texts. We augment basic parallel tag clouds with a details-in-context display and an option to visualize changes over a second facet of the data, such as time. We also address text mining challenges such as selecting the best words to visualize, and how to do so in reasonable time periods to maintain interactivity. ©2009 ieee.

关键词： visualization

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Model space visualization for multivariate linear trend discovery

Model space visualization for multivariate linear trend disc...

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VAST 09 - ieee symposium on Visual Analytics Science and Technology

作者： Guo, Zhenyu Ward, Matthew O. Rundensteiner, Elke A. Computer Science Department Worcester Polytechnic Institute United States

ISBN: (纸本)9781424452835

Discovering and extracting linear trends and correlations in datasets is very important for analysts to understand multivariate phenomena. However, current widely used multivariate visualization techniques, such as parallel coordinates and scatterplot matrices, fail to reveal and illustrate such linear relationships intuitively, especially when more than 3 variables are involved or multiple trends coexist in the dataset. We present a novel multivariate model parameter space visualization system that helps analysts discover single and multiple linear patterns and extract subsets of data that fit a model well. Using this system, analysts are able to explore and navigate in model parameter space, interactively select and tune patterns, and refine the model for accuracy using computational techniques. We build connections between model space and data space visually, allowing analysts to employ their domain knowledge during exploration to better interpret the patterns they discover and their validity. Case studies with real datasets are used to investigate the effectiveness of the visualizations. ©2009 ieee.

关键词： visualization

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A scalable architecture for visual data exploration

A scalable architecture for visual data exploration

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VAST 09 - ieee symposium on Visual Analytics Science and Technology

作者： Decker, Jonathan Godwin, Alex Livingston, Mark A. Royle, Denise Naval Research Laboratory United States Charles River Analytics United States

ISBN: (纸本)9781424452835

Intelligence analysts in the areas of defense and homeland security are now faced with the difficult problem of discerning the relevant details amidst massive data stores. We propose a component-based visualization architecture that is built specifically to encourage the flexible exploration of geospatial event databases. The proposed system is designed to deploy on a variety of display layouts, from a single laptop screen to a multi-monitor tiled-display. By utilizing a combination of parallel coordinates, principal components plots, and other data views, analysts may reduce the dimensionality of a data set to its most salient features. Of particular value to our target applications are understanding correlations between data layers, both within a single view and across multiple views. Our proposed system aims to address the limited scalability associated with coordinated multiple views (CMVs) through the implementation of an efficient core application which is extensible by the end-user. ©2009 ieee.

关键词： visualization

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GPU accelerated plant growth modeling and visualization

GPU accelerated plant growth modeling and visualization

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3rd International symposium on Plant Growth Modeling, Simulation, visualization and Applications, PMA09

作者： Zhao, Xing Hu, Jingjing Kang, Mengzhen School of Mathematical Sciences Capital Normal University Beijing 100048 China School of Software Beijing Institute of Technology Beijing 100081 China Institute of Automation Chinese Academy of Sciences Beijing 100080 China

ISBN: (纸本)9780769539881

We present a GPU-accelerated algorithm for plant growth modeling and visualization. In this algorithm, plant topological structures and geometrical structures are represented separately. Plant topological structures are generated by dual-scale automaton, and geometrical structures are dynamically constructed in parallel by the geometry shader of graphics Processing Unit (GPU). This scheme greatly reduces the amount of transferred data between main memory and GPU memory, and speeds up plant growth modeling and rendering without compromising image quality. An application for cotton growth modeling and visualization is given in detail to confirm the advantages of the proposed algorithm. © 2010 ieee.

关键词： graphics processing unit

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Combining automated analysis and visualization techniques for effective exploration of high-dimensional data

Combining automated analysis and visualization techniques fo...

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VAST 09 - ieee symposium on Visual Analytics Science and Technology

作者： Tatu, Andrada Albuquerque, Georgia Eisemann, Martin Schneidewind, Jörn Theisel, Holger Magnork, Marcus Keim, Daniel University of Konstanz Germany TU Braunschweig Germany Telefonica o2 Business Intelligence Center Germany University of Magdeburg Germany

ISBN: (纸本)9781424452835

Visual exploration of multivariate data typically requires projection onto lower-dimensional representations. The number of possible representations grows rapidly with the number of dimensions, and manual exploration quickly becomes ineffective or even unfeasible. This paper proposes automatic analysis methods to extract potentially relevant visual structures from a set of candidate visualizations. Based on features, the visualizations are ranked in accordance with a specified user task. The user is provided with a manageable number of potentially useful candidate visualizations, which can be used as a starting point for interactive data analysis. This can effectively ease the task of finding truly useful visualizations and potentially speed up the data exploration task. In this paper, we present ranking measures for class-based as well as non class-based Scatterplots and parallel Coordinates visualizations. The proposed analysis methods are evaluated on different datasets. ©2009 ieee.

关键词： visualization

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