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ieee symposium on Information visualization (InfoVis 05)

作者： Fanea, E Carpendale, S Isenberg, T Univ Calgary Dept Comp Sci Calgary AB Canada

ISBN: (纸本)078039464X

parallel Coordinates are a powerful method for visualizing multidimensional data but, when applied to large data sets, they become cluttered and difficult to read. Star Glyphs, on the other hand, can be used to display either the attributes of a data item or the values across all items for a single attribute. Star Glyphs may readily provide a quick impression;however, since the full data set will require multiple glyphs, overall readings are more difficult. We present parallel Glyphs, an interactive integration of the visual representations of parallel Coordinates and Star Glyphs that utilizes the advantages of both representations to offset the disadvantages they have separately. We discuss the role of uniform and stepped colour scales in the visual comparison of non-adjacent items and Star Glyphs. parallel Glyphs provide capabilities for focus-in-context exploration using two types of lenses and interactions specific to the 3D space.

关键词： parallel Glyphs parallel coordinates Star Glyphs multi-dimensional data sets 3D visualization

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A parallel multiresolution volume rendering algorithm for large data visualization

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parallel COMPUTING 2005年第2期31卷 185-204页

作者： Gao, JZ Wang, C Li, LY Shen, HW Ohio State Univ Columbus OH 43210 USA Oak Ridge Natl Lab Oak Ridge TN 37381 USA

We present a new parallel multiresolution volume rendering algorithm for visualizing large data sets. Using the wavelet transform, the raw data is first converted to a multi resolution wavelet tree. To eliminate the data dependency between processors at run-time, and achieve load-balanced rendering, we design a novel algorithm to partition the tree and distribute the data along a hierarchical space-filling curve with error-guided bucketization. Further optimization is achieved by storing reconstructed data at pre-selected tree nodes for each processor based on the available storage resources to reduce the overall wavelet reconstruction cost. At run time, the wavelet tree is first traversed according to the user-specified error tolerance. data blocks of different resolutions that satisfy the error tolerance are then decompressed and rendered to compose the final image in parallel. Experimental results showed that our algorithm can reduce the run-time communication cost to a minimum and ensure a well-balanced workload among processors when visualizing gigabytes of data with arbitrary error tolerances. (c) 2005 Elsevier B.V.. All rights reserved.

关键词： large scale data multiresolution wavelet transform space-filling curve load balancing volume rendering parallel rendering

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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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large volume visualization of compressed time-dependent datasets on GPU clusters

Large volume visualization of compressed time-dependent data...

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symposium on parallel graphics and visualization

作者： Strengert, M Magallón, M Weiskopf, D Guthe, S Ertl, T Univ Stuttgart Inst Visualizat & Interact Syst D-70569 Stuttgart Germany Univ Costa Rica Escuela Fis San Pedro 2060 Costa Rica Univ Tubingen GRIS WSI D-72076 Tubingen Germany

We describe a system for the texture-based direct volume visualization of large data sets on a PC cluster equipped with GPUs. The data is partitioned into volume bricks in object space, and the intermediate images are combined to a final picture in a sort-last approach. Hierarchical wavelet compression is applied to increase the effective size of volumes that can be handled. An adaptive rendering mechanism takes into account the viewing parameters and the properties of the data set to adjust the texture resolution and number of slices. We discuss the specific issues of this adaptive and hierarchical approach in the context of a distributed memory architecture and present corresponding solutions. Furthermore, our compositing scheme takes into account the footprints of volume bricks to minimize the costs for reading from framebuffer, network communication, and blending. A detailed performance analysis is provided for several network, CPU, and GPU architectures-and scaling characteristics of the parallel system are discussed. For example, our tests on a eight-node AMD64 cluster with InfiniBand show a rendering speed of 6 frames per second for a 2048 x 1024 x 1878 data set on a 1024(2) viewport. (c) 2005 Elsevier B.V. All rights reserved.

关键词： graphics systems distributed/network graphics viewing algorithms

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A multiresolution volume rendering framework for large-scale time-varying data visualization

A multiresolution volume rendering framework for large-scale...

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Fourth International Workshop on Volume graphics 2005

作者： Wang, Chaoli Gao, Jinzhu Li, Liya Shen, Han-Wei Ohio State University Columbus OH 43210 United States Oak Ridge National Laboratory Oak Ridge TN 37831 United States

ISBN: (纸本)3905673266

We present a new parallel multiresolution volume rendering framework for large-scale time-varying data visualization using the wavelet-based time-space partitioning (WTSP) tree. Utilizing the wavelet transform, a large-scale time-varying data set is converted into a space-time multiresolution data hierarchy, and is stored in a time-space partitioning (TSP) tree. To eliminate the parent-child data dependency for reconstruction and achieve toad-balanced rendering, we design an algorithm to partition the WTSP tree and distribute the wavelet-compressed data along hierarchical space-filling curves with error-guided bucketization. At run time, the WTSP tree is traversed according to the user-specified time step and tolerances of both spatial and temporal errors. data blocks of different spatio-temporal resolutions are reconstructed and rendered to compose the final image in parallel. We demonstrate that our algorithm can reduce the run-time communication cost to a minimum and ensure a well-balanced workload among processors when visualizing gigabytes of time-varying data on a PC cluster. © The Eurographics Association 2005.

关键词： Wavelet transforms

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A system for interactive volume visualization on the powerwall

A system for interactive volume visualization on the powerwa...

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VIS 05: ieee visualization 2005, Proceedings

作者： Woodward, Paul R. Porter, David H. Knox, Michael R. Andringa, Steven T. Larson, A.J. Stender, Aaron Laboratory for Computational Science and Engineering University of Minnesota United States

No abstract available

关键词： Applications of volume graphics and volume visualization parallel and distributed volume visualization Time-varying volume data Volume rendering of extremely large datasets

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Topological fisheye views for visualizing large graphs

Topological fisheye views for visualizing large graphs

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ieee visualization 2004 Conference

作者： Gansner, ER Koren, Y North, SC AT&T Labs Res Shannon Lab Florham Pk NJ 07932 USA

ISBN: (纸本)0780387793

Graph drawing is a basic visualization tool that works well for graphs having up to hundreds of nodes and edges. At greater scale, data density and occlusion problems often negate its effectiveness. Conventional pan-and-zoom, multiscale, and geometric fisheye views are not fully satisfactory solutions to this problem. As an alternative, we propose a topological zooming method. It precomputes a hierarchy of coarsened graphs that are combined on-the-fly into renderings, with the level of detail dependent on distance from one or more foci. A related geometric distortion method yields constant information density displays from these renderings.

关键词： topological fisheye large graph visualization

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Importance-driven visualization layouts for large time series data

Importance-driven visualization layouts for large time serie...

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ieee symposium on Information visualization (InfoVis 05)

作者： Hao, MC Dayal, U Keim, DA Schreck, T Hewlett Packard Labs Palo Alto CA 94304 USA

ISBN: (纸本)078039464X

Time series are an important type of data with applications in virtually every aspect of the real world. Often a large number of time series have to be monitored and analyzed in parallel. Sets of time series may show intrinsic hierarchical relationships and varying degrees of importance among the individual time series. Effective techniques for visually analyzing large sets of time series should encode the relative importance and hierarchical ordering of the time series data by size and position, and should also provide a high degree of regularity ill order to support comparability by the analyst. In this paper, we present a framework for visualizing large sets of time series. Based on the notion of inter time series importance relationships, we define a set of objective functions that space-filling layout schemes for time series data should obey. We develop an efficient algorithm addressing the identified problems by generating layouts that reflect hierarchy- and importance-based relationships in a regular layout with favorable aspect ratios. We apply our technique to a number of real-world data sets including sales and stock data, and we compare our technique with an aspect ratio aware variant of the well-known TreeMap algorithm. The examples show the advantages and practical usefulness of our layout algorithm.

关键词： information visualization time series space-filling layout generation

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Revealing structure within clustered parallel coordinates displays

Revealing structure within clustered parallel coordinates di...

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ieee symposium on Information visualization (InfoVis 05)

作者： Johansson, J Ljung, P Jern, M Cooper, M Linkoping Univ NVIS S-58183 Linkoping Sweden

ISBN: (纸本)078039464X

In order to gain insight into multivariate data, complex structures must be analysed and understood. parallel coordinates is an excellent tool for visualizing this type of data but has its limitations. This paper deals with one of its main limitations - how to visualize a large number of data items without hiding the inherent structure they constitute. We solve this problem by constructing clusters and using high-precision textures to represent them. We also use transfer functions that operate on the high-precision textures in order to highlight different aspects of the cluster characteristics. Providing pre-defined transfer functions as well as the support to draw customized transfer functions makes it possible to extract different aspects of the data. We also show how feature animation can be used as guidance when simultaneously analysing several clusters. This technique makes it possible to visually represent statistical information about clusters and thus guides the user, making the analysis process more efficient.

关键词： parallel coordinates clustering transfer function feature animation

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A parallel multiresolution volume rendering algorithm for large data visualization

A parallel multiresolution volume rendering algorithm for la...

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symposium on parallel graphics and visualization

作者： Gao, JZ Wang, C Li, LY Shen, HW Ohio State Univ Columbus OH 43210 USA Oak Ridge Natl Lab Oak Ridge TN 37381 USA

关键词： large scale data multiresolution wavelet transform space-filling curve load balancing volume rendering parallel rendering

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