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ieee symposium on parallel and large-data visualization and graphics

作者： Moreland, K Wylie, B Pavlakos, C Sandia Natl Labs Livermore CA 94550 USA

ISBN: (纸本)0780372239

Due to the impressive price-performance of today's PC-based graphics accelerator cards, Sandia National Laboratories is attempting to use PC clusters to render extremely large data sets in interactive applications. This paper describes a sort-last parallel rendering system running on a PC cluster that is capable of rendering enormous amounts of geometry onto high-resolution tile displays by taking advantage of the spatial coherency that is inherent in our data. Furthermore, it is capable of scaling to larger sized input data or higher resolution displays by increasing the size of the cluster. Our prototype is now capable of rendering 120 million triangles per second on a 12 mega-pixel display.

关键词： parallel rendering sort-last compositing PC-cluster tile display

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Optimizing Multi-Image Sort-Last parallel Rendering 6

Optimizing Multi-Image Sort-Last Parallel Rendering

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6th ieee symposium on large data Analysis and visualization (LDAV)

作者： Larsen, Matthew Moreland, Kenneth Johnson, Chris R. Childs, Hank Univ Oregon Lawrence Livermore Natl Lab Eugene OR 97403 USA Sandia Natl Labs Livermore CA 94550 USA Univ Utah Salt Lake City UT 84112 USA

ISBN: (纸本)9781509056590

Sort-last parallel rendering can be improved by considering the rendering of multiple images at a time. Most parallel rendering algorithms consider the generation of only a single image. This makes sense when performing interactive rendering where the parameters of each rendering are not known until the previous rendering completes. However, in situ visualization often generates multiple images that do not need to be created sequentially. In this paper we present a simple and effective approach to improving parallel image generation throughput by amortizing the load and overhead among multiple image renders. Additionally, we validate our approach by conducting a performance study exploring the achievable speed-ups in a variety of image-based in situ use cases and rendering workloads. On average, our approach shows a 1.5 to 3.7 fold improvement in performance, and in some cases, shows a 10 fold improvement.

关键词： I.3.6 [Computer graphics]: General I.3.2 [Computer graphics]: graphics Systems-Distributed/network graphics

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parallel Processing and Immersive visualization of Sonar Point Clouds 4

Parallel Processing and Immersive Visualization of Sonar Poi...

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ieee symposium on large data Analysis and visualization

作者： Febretti, Alessandro Richmond, Kristof Doran, Peter Johnson, Andrew Univ Illinois Elect Visualizat Lab Chicago IL 60607 USA Frontier Astronaut LLC Chugwater WY USA Univ Illinois Dept Environm Sci Chicago IL USA

ISBN: (纸本)9781479952151

The investigation of underwater structures and natural features through Autonomous Underwater Vehicles (AUVs) is an expanding field with applications in archaeology, engineering, environmental sciences and astrobiology. Processing and analyzing the raw sonar data generated by automated surveys is challenging due to the presence of complex error sources like water chemistry, zero-depth variations, inertial navigation errors and multipath reflections. Furthermore, the complexity of the collected data makes it difficult to perform effective analysis on a standard display. Point clouds made up of hundreds of millions to billions of points are not uncommon. Highly interactive, immersive visualization is a desirable tool that researchers can use to improve the quality of a final sonar-based data product. In this paper we present a scalable toolkit for the processing and visualization of sonar point clouds on a cluster-based, large scale immersive visualization environment. The cluster is used simultaneously as a parallel processing platform that performs sonar beam-tracing of the source raw data, and as the rendering driver of the immersive display.

关键词： data visualisation geophysics computing hydrological techniques lakes parallel processing rendering (computer graphics) sonar signal processing automated surveys cluster-based immersive visualization environment immersive display rendering driver sonar beam-tracing sonar point clouds Acoustic beams Antarctica data visualization Lakes Sonar Sonar navigation Three-dimensional displays parallel PROCESSING (COMPUTERS) data visualisation sonar three-dimensional displays Acoustic beams lakes sonar signal processing geophysics computing hydrological techniques Antarctica Rendering (computer graphics) visualization

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parallel Partial Reduction for large-Scale data Analysis and visualization 8

Parallel Partial Reduction for Large-Scale Data Analysis and...

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8th ieee symposium on large-Scale data Analysis and visualization (LDAV)

作者： He, Wenbin Guo, Hanqi Peterka, Tom Di, Sheng Cappello, Franck Shen, Han-Wei Ohio State Univ Dept Comp Sci & Engn Columbus OH 43210 USA Argonne Natl Lab Math & Comp Sci Div Lemont IL USA

ISBN: (纸本)9781538668733

We present a novel partial reduction algorithm to aggregate sparsely distributed intermediate results that are generated by data-parallel analysis and visualization algorithms. Applications of partial reduction include flow trajectory analysis, big data online analytical processing, and volume rendering. Unlike traditional full parallel reduction that exchanges dense data across all processes, the purpose of partial reduction is to exchange only intermediate results that correspond to the same query, such as line segments of the same flow trajectory. To this end, we design a three-stage algorithm that minimizes the communication cost: (1) partitioning the result space into groups;(2) constructing and optimizing the reduction partners for each group;and (3) initiating collective reduction operations for all groups concurrently. Both theoretical and empirical analyses show that our algorithm outperforms the traditional methods when the intermediate results are sparsely distributed. We also demonstrate the effectiveness of our algorithm for flow visualization, big log data analysis, and volume rendering.

关键词： I.3.1 [COMPUTER graphics]: Hardware Architecture-parallel processing I.3.2 [COMPUTER graphics]: graphics Systems-Distributed/network graphics

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Multiscale visualization using data cubes

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ieee TRANSACTIONS ON visualization AND COMPUTER graphics 2003年第2期9卷 176-187页

作者： Stolte, C Tang, D Hanrahan, P Stanford Univ Dept Comp Sci Stanford CA 94305 USA

Most analysts start with an overview of the data before gradually refining their view to be more focused and detailed. Multiscale pan-and-zoom systems are effective because they directly support this approach. However, generating abstract overviews of large data sets is difficult and most systems take advantage of only one type of abstraction: visual abstraction. Furthermore, these existing systems limit the analyst to a single zooming path on their data and thus to a single set of abstract views, This paper presents: 1) a formalism for describing multiscale visualizations of data cubes with both data and visual abstraction and 2) a method for independently zooming along one or more dimensions by traversing a zoom graph with nodes at different levels of detail. As an example of how to design multiscale visualizations using our system, we describe four design patterns using our formalism. These design patterns show the effectiveness of multiscale visualization of general relational databases.

关键词： multiscale visualization database visualization graphic formalism

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large-Scale Co-visualization for LAMMPS using vl3 5

Large-Scale Co-Visualization for LAMMPS using vl3

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ieee 5th symposium on large data Analysis and visualization (LDAV)

作者： Rizzi, Silvio Hereld, Mark Insley, Joseph Papka, Michael E. Uram, Thomas Vishwanath, Venkatram Argonne Natl Lab Argonne IL 60439 USA Northern Illinois Univ De Kalb IL USA

ISBN: (纸本)9781467385176

In this poster we propose to interconnect LAMMPS and vl3, our parallel framework for large-scale visualization and analysis. The goal is co-visualization and exploration at interactive frame rates of large-scale atomistic simulations. We describe the architecture of the proposed system, as well as a preliminary implementation that runs on GPU-based visualization clusters.

关键词： I.3.2 [Computing Methodologies]: Computer graphics ??? graphics Systems: Distributed/network graphic Posters visualization large sizes Frame Rate Exploration Building construction ARCHITECTURE

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Jupiter: A toolkit for interactive large model visualization

Jupiter: A toolkit for interactive large model visualization

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ieee symposium on parallel and large-data visualization and graphics

作者： Bartz, D Staneker, D Strasser, W Cripe, B Gaskins, T Orton, K Carter, M Johannsen, A Univ Tubingen WSI GRIS Tubingen Germany

ISBN: (纸本)0780372239

The fast increasing size of datasets in scientific computing, mechanical engineering, or virtual medicine is quickly exceeding the graphics capabilities of modem computers. Toolkits for the large model visualization address this problem by combining efficient geometric techniques, such as occlusion and visibility culling, mesh reduction, and efficient rendering. In this paper, we introduce Jupiter, a toolkit for the interactive visualization of large models which exploits the above mentioned techniques. Jupiter was originally developed by Hewlett-Packard and EAI, and it was recently equipped with new functionality by the University of Tubingen, as being part of the Kelvin project. Earlier this year, an initial version of Jupiter was also released as open source.

关键词： large model visualization toolkit visibility and occlusion culling

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RESEARCH ISSUES IN data MODELING FOR SCIENTIFIC visualization

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ieee COMPUTER graphics AND APPLICATIONS 1994年第2期14卷 70-73页

作者： NIELSON, GM BRUNET, P GROSS, M HAGEN, H KLIMENKO, SV UNIV KAISERSLAUTERN W-6750 KAISERSLAUTERNGERMANY UNIV POLITECN CATALUNA BARCELONASPAIN COMP GRAPH CTR DARMSTADTGERMANY INST HIGH ENERGY PHYS SERPUKHOVRUSSIA

This article summarizes some topics of modeling as they impinge on the future development of scientific data visualization. The benefits from visualization techniques in analyzing data are well established, but to build on these pioneering efforts, one must recognize modeling as a distinct structural component in the larger context of visualization and problem-solving systems. Volume modeling is the entry way to this arena of future development, and model-based rendering describes how scientists will view the results. Important side developments such as multiresolution modeling and model-based segmentation will contribute structural capability to these systems. All of these components ultimately depend on the mathematical foundations of scattered data modeling and on model validation and standards to incorporate this modeling methodology into effective tools for scientific inquiry.< >

关键词： data visualization Rendering (computer graphics) Neoplasms Hurricanes Magnetic resonance imaging Computer graphics Thumb Delay parallel processing Hardware

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Sequence Surveyor: Leveraging Overview for Scalable Genomic Alignment visualization

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ieee TRANSACTIONS ON visualization AND COMPUTER graphics 2011年第12期17卷 2392-2401页

作者： Albers, Danielle Dewey, Colin Gleicher, Michael Univ Wisconsin Madison WI 53706 USA

In this paper, we introduce overview visualization tools for large-scale multiple genome alignment data. Genome alignment visualization and, more generally, sequence alignment visualization are an important tool for understanding genomic sequence data. As sequencing techniques improve and more data become available, greater demand is being placed on visualization tools to scale to the size of these new datasets. When viewing such large data, we necessarily cannot convey details, rather we specifically design overview tools to help elucidate large-scale patterns. Perceptual science, signal processing theory, and generality provide a framework for the design of such visualizations that can scale well beyond current approaches. We present Sequence Surveyor, a prototype that embodies these ideas for scalable multiple whole-genome alignment overview visualization. Sequence Surveyor visualizes sequences in parallel, displaying data using variable color, position, and aggregation encodings. We demonstrate how perceptual science can inform the design of visualization techniques that remain visually manageable at scale and how signal processing concepts can inform aggregation schemes that highlight global trends, outliers, and overall data distributions as the problem scales. These techniques allow us to visualize alignments with over 100 whole bacterial-sized genomes.

关键词： Bioinformatics visualization Perception Theory Scalability Issues Visual Design

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GPU-based Image Compression for Efficient Compositing in Distributed Rendering Applications 11

GPU-based Image Compression for Efficient Compositing in Dis...

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ieee 11th symposium on large data Analysis and visualization (LDAV)

作者： Lipinksi, Riley Moreland, Kenneth Papka, Michael E. Marrinan, Thomas Univ St Thomas St Paul MN 55105 USA Oak Ridge Natl Lab Oak Ridge TN USA Argonne Natl Lab Argonne IL 60439 USA Northern Illinois Univ De Kalb IL 60115 USA

ISBN: (纸本)9781665432832

visualizations of large-scale data sets are often created on graphics clusters that distribute the rendering task amongst many processes. When using real-time GPU-based graphics algorithms, the most time-consuming aspect of distributed rendering is typically the compositing phase - combining all partial images from each rendering process into the final visualization. Compositing requires image data to be copied off the GPU and sent over a network to other processes. While compression has been utilized in existing distributed rendering compositors to reduce the data being sent over the network, this compression tends to occur after the raw images are transferred from the GPU to main memory. In this paper, we present work that leverages OpenGL / CUDA interoperability to compress raw images on the GPU prior to transferring the data to main memory. This approach can significantly reduce the device-to-host data transfer time, thus enabling more efficient compositing of images generated by distributed rendering applications.

关键词： Computing methodologies Computer graphics Image compression Computing methodologies parallel computing methodologies parallel algorithms Massively parallel algorithms

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