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检索条件"任意字段=Proceedings of the 1st Symposium on Applied perception in graphics and visualization"

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1st IEEE symposium on Large-Scale Data Analysis and visualization 2011, LDAV 2011 - proceedings

1st IEEE Symposium on Large-Scale Data Analysis and Visualiz...

引用

1st IEEE symposium on Large-Scale Data Analysis and visualization 2011, LDAV 2011

ISBN: (纸本)9781467301541

The proceedings contain 28 papers. The topics discussed include: visualizing multiscale, multiphysics simulation data: brain blood flow;toward simulation-time data analysis and I/O acceleration on leadership-class systems;atypical behavior identification in large-scale network traffic;revisiting wavelet compression for large-scale climate data using JPEG 2000 and ensuring data precision;histogram spectra for multivariate time-varying volume LOD selection;parallel clustering for visualizing large scientific line data;evaluating the benefits of an extended memory hierarchy for parallel streamline algorithms;parallel in situ indexing for data-intensive computing;incremental, approximate database queries and uncertainty for exploratory visualization;the ParaView coprocessing library: a scalable, general purpose in situ visualization library;and dax toolkit: a proposed framework for data analysis and visualization at extreme scale.

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CERA-TVR: A framework for interactive high-quality teravoxel volume visualization on standard PCs

CERA-TVR: A framework for interactive high-quality teravoxel...

引用

1st IEEE symposium on Large-Scale Data Analysis and visualization 2011, LDAV 2011

作者： Engel, Klaus Siemens AG Germany

ISBN: (纸本)9781467301541

We present a volume visualization framework that allows high-quality interactive rendering of teravoxel scale volume data sets on standard PCs. It is based on a progressive multi-resolution out-of-core volume rendering approach. Data loading is controlled by rays that are cast through the volume data set. The tree structure representing the multi-resolution hierarchy is traversed and updated directly by the GPU during ray casting. Consequently, occluded and empty data is never loaded or rendered. The framework is able to render dense, anisotropic, scalar volume data on regular grids with all common rendering modes. © 2011 IEEE.

关键词： Volume rendering

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Incremental, approximate database queries and uncertainty for exploratory visualization

Incremental, approximate database queries and uncertainty fo...

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1st IEEE symposium on Large-Scale Data Analysis and visualization 2011, LDAV 2011

作者： Fisher, Danyel Microsoft Research 1 Microsoft Way Redmond WA 98052 United States

ISBN: (纸本)9781467301541

Exploratory data visualization calls for iterative analyses, but very large databases are often far too slow to allow interactive exploration. Incremental, approximate database queries exchange precision for speed: by sampling from the full database, the system can resolve queries rapidly. As the sample gets broader, the precision increases at the cost of time. As the precision of the sample value can be estimated, we can represent the range of possible values. This range may be visually represented using uncertainty visualization techniques. This paper outlines the current literature in both incremental approximate queries and in uncertainty visualization. The two fields mesh well: incremental techniques can collect data in interactive time, and uncertainty techniques can show bounded error. © 2011 IEEE.

关键词： visualization

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Histogram spectra for multivariate time-varying volume LOD selection

Histogram spectra for multivariate time-varying volume LOD s...

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1st IEEE symposium on Large-Scale Data Analysis and visualization 2011, LDAV 2011

作者： Martin, steven Shen, Han-Wei Ohio State University United States

ISBN: (纸本)9781467301541

Level of detail techniques are widely applied to minimize sampling error subject to working set size constraints. Typical large data sets being produced today have many variables sampled across time-varying volumes. visualization of these multivariate volumes is commonly phrased in terms of conditional expressions such as "show variable A where variable B is between B 1 and B2." The bounds, B1 and B 2, tend to be specified during the interactive portion of the workflow. Thus, to maximize quality over the salient interval, level of detail selection should also be interactive. We introduce the concept of histogram spectra to quickly and compactly quantify the statistical sensitivity of volumes to sampling. Salient interval volumes of one or more variables are used to select which parts of the histogram spectra are important. The level of detail selection problem, over a time-varying, multivariate, multiresolution volume, is then posed as an integer programming problem using the histogram spectra. We propose an efficient solution enabling interactive LOD selection on large, out-of-core volumes and show its efficacy on two real data sets from different problem domains. © 2011 IEEE.

关键词： visualization

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Subtle gaze manipulation for improved mammography training 11

Subtle gaze manipulation for improved mammography training

引用

8th Annual symposium on applied perception in graphics and visualization, APGV 2011

作者： Sridharan, Srinivas Bailey, Reynold McNamara, Ann Grimm, Cindy Rochester Institute of Technology United States Texas A and M University United States Washington University St. Louis United States

ISBN: (纸本)9781450308892

The ability to direct viewer gaze about an image has important application in medical image training and analysis. We use a novel gaze manipulation technique called Subtle Gaze Direction [Bailey et al. 2009] to guide novice users as they try to identify abnormalities in digital mammogram images. Subtle Gaze Direction is achieved by performing brief image-space modulations on specific regions of the viewer's peripheral vision in order to attract their attention. The viewer's gaze is monitored in real-time and the modulations are terminated before the viewer is allowed to scrutinize them with their high-acuity foveal vision. This approach is preferred to more overt techniques which require permanent alterations to the original images in order to highlight specific areas of interest. In our experiment we use Subtle Gaze Direction to guide novices along the scanpath of an expert radiologist. We hypothesized that this approach would increase the likelihood of novices correctly identifying irregularities in the mammograms.

关键词： Mammography

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The ParaView coprocessing library: A scalable, general purpose in situ visualization library

The ParaView coprocessing library: A scalable, general purpo...

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1st IEEE symposium on Large-Scale Data Analysis and visualization 2011, LDAV 2011

作者： Fabian, Nathan Moreland, Kenneth Thompson, David Bauer, Andrew C. Marion, Pat Gevecik, Berk Rasquin, Michel Jansen, Kenneth E. Sandia National Laboratories United States Kitware Inc. United States University of Colorado Boulder CO United States

ISBN: (纸本)9781467301541

As high performance computing approaches exascale, CPU capability far outpaces disk write speed, and in situ visualization becomes an essential part of an analyst's workflow. In this paper, we describe the ParaView Coprocessing Library, a framework for in situ visualization and analysis coprocessing. We describe how coprocessing algorithms (building on many from VTK) can be linked and executed directly from within a scientific simulation or other applications that need visualization and analysis. We also describe how the ParaView Coprocessing Library can write out partially processed, compressed, or extracted data readable by a traditional visualization application for interactive post-processing. Finally, we will demonstrate the library's scalability in a number of real-world scenarios. © 2011 IEEE.

关键词： Data visualization

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Toward simulation-time data analysis and I/O acceleration on leadership-class systems

Toward simulation-time data analysis and I/O acceleration on...

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1st IEEE symposium on Large-Scale Data Analysis and visualization 2011, LDAV 2011

作者： Vishwanath, Venkatram Hereld, Mark Papka, Michael E. Argonne National Laboratory 9700 South Cass Avenue Argonne IL 60439 United States

ISBN: (纸本)9781467301541

The performance mismatch between computing and I/O components of current-generation HPC systems has made I/O the critical bottleneck for scientific applications. It is therefore critical to make data movement as efficient as possible, and, to facilitate simulation-time data analysis and visualization to reduce the data written to storage. These will be of paramount importance to enabling us to glean novel insights from simulations. We present our work in GLEAN, a flexible framework for data-analysis and I/O acceleration at extreme scale. GLEAN leverages the data semantics of applications, and fully exploits the diverse system topologies and characteristics. We discuss the performance of GLEAN for simulation-time analysis and I/O acceleration with simulations at scale on leadership class systems. © 2011 IEEE.

关键词： Data visualization

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Dax toolkit: A proposed framework for data analysis and visualization at extreme scale

Dax toolkit: A proposed framework for data analysis and visu...

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1st IEEE symposium on Large-Scale Data Analysis and visualization 2011, LDAV 2011

作者： Moreland, Kenneth Ayachit, Utkarsh Geveci, Berk Ma, Kwan-Liu Sandia National Laboratories United States Kitware Inc. United States University of California Davis CA United States

ISBN: (纸本)9781467301541

Experts agree that the exascale machine will comprise processors that contain many cores, which in turn will necessitate a much higher degree of concurrency. Software will require a minimum of a 1,000 times more concurrency. Most parallel analysis and visualization algorithms today work by partitioning data and running mostly serial algorithms concurrently on each data partition. Although this approach lends itself well to the concurrency of current high-performance computing, it does not exhibit the appropriate pervasive parallelism required for exascale computing. The data partitions are too small and the overhead of the threads is too large to make effective use of all the cores in an extreme-scale machine. This paper introduces a new visualization framework designed to exhibit the pervasive parallelism necessary for extreme scale machines. We demonstrate the use of this system on a GPU processor, which we feel is the best analog to an exascale node that we have available today. © 2011 IEEE.

关键词： Data visualization

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Scalable multivariate volume visualization and analysis

Scalable multivariate volume visualization and analysis

引用

1st IEEE symposium on Large-Scale Data Analysis and visualization 2011, LDAV 2011

作者： Guo, Hanqi Xiao, He Lu, Min Yuan, Xiaoru School of EECS Peking University Beijing China Center for Computational Science and Engineering Peking University Beijing China

ISBN: (纸本)9781467301541

In this work, we present an effective and scalable system for multivariate volume data visualization and analysis with a novel Transfer Function (TF) interface design that tightly couples parallel coordinates plots (PCP) and MDS-based dimension projection plots. In our system, the PCP visualizes the data distribution of each variate and the MDS plots project features. Together, they are integrated seamlessly to provide flexible feature classification without context switching between different data presentations during the user interaction. The proposed interface enables users to identify relevant correlation clusters and assign optical properties on them. To further support large scale multivariate volume data visualization and analysis, we develop three integrated parallel systems to accelerate the rendering of PCP, the layout of MDS, as well as parallel rendering of multivarite volume data. Our experiments show that the system is effective in multivariate volume data visualization and its performance is scalable for data sets with different sizes and number of variates. © 2011 IEEE.

关键词： Transfer functions

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Scalable parallel building blocks for custom data analysis

Scalable parallel building blocks for custom data analysis

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1st IEEE symposium on Large-Scale Data Analysis and visualization 2011, LDAV 2011

作者： Peterka, Tom Ross, Robert Gyulassy, Attila Pascucci, Valerio Kendall, Wesley Shen, Han-Wei Lee, Teng-Yok Chaudhuri, Abon Argonne National Laboratory United States University of Utah United States University of Tennessee Knoxville TN United States Ohio State University United States

ISBN: (纸本)9781467301541

We present a set of building blocks that provide scalable data movement capability to computational scientists and visualization researchers for writing their own parallel analysis. The set includes scalable tools for domain decomposition, process assignment, parallel I/O, global reduction, and local neighborhood communicationtasks that are common across many analysis applications. The global reduction is performed with a new algorithm, described in this paper, that efficiently merges blocks of analysis results into a smaller number of larger blocks. The merging is configurable in the number of blocks that are reduced in each round, the number of rounds, and the total number of resulting blocks. We highlight the use of our library in two analysis applications: parallel streamline generation and parallel Morse-Smale topological analysis. The first case uses an existing local neighborhood communication algorithm, whereas the latter uses the new merge algorithm. © 2011 IEEE.

关键词： Data visualization

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