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ieee symposium on large data Analysis and visualization (LDAV)

作者： Timothy Luciani Rebecca Hachey Daniel Q. Oliphant Brian A. Cherinka G. Elisabeta Marai Department of Computer Science University of Pittsburgh Pittsburgh PA USA Department of Physics and Astronomy University of Pittsburgh Pittsburgh PA USA

These preliminary results show that pixel-based overlays have the potential to generate scalable, graphical representations of astronomy data. This approach may allow us to overcome bandwidth and screen-space current limitations in astronomy database visualization by following a WebGL - PHP client-server architecture. The advantages of this approach are its versatility and visual scalability (to the pixel level), enabling the visual analysis of large datasets. The resulting versatility allows for flexible control over the visualization and the client-side scripts. Accessing graphics hardware through WebGL further provides the users with a rich, graphics-accelerated web experience. Preliminary feedback from astronomy researchers emphasizes the benefits of visual analysis to this field.

关键词： Astronomy databases Telescopes data visualization Prototypes Google

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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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Distributed terascale volume visualization using distributed shared virtual memory

Distributed terascale volume visualization using distributed...

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ieee symposium on large data Analysis and visualization (LDAV)

作者： Johanna Beyer Markus Hadwiger Jens Schneider Won-Ki Jeong Hanspeter Pfister KAUST Saudi Arabia Harvard University USA

Each cluster node is running its own pipeline for ray-casting, virtual vol- ume and memory management, and paging. Ray-casting is per- formed on a huge virtual 3D volume, which is conceptually given on a regular grid in 3D. However, this volume is virtual because the data that are sampled by the ray-caster are only created on demand (i.e., read from disk or reconstructed on-the-fly), as determined by the actual visibility of small cubical blocks or memory pages of 32 voxels each. In order to be able to adapt the data resolution used for ray-casting to the output screen resolution, we represent the whole virtual volume as a virtual octree multi-resolution hier- archy, which is mapped to a large shared virtual memory address space.

关键词： Rendering (computer graphics) graphics processing unit Octrees Three dimensional displays data visualization Switches

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Sort-First parallel Volume Rendering

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ieee TRANSACTIONS ON visualization AND COMPUTER graphics 2011年第8期17卷 1164-1177页

作者： Moloney, Brendan Ament, Marco Weiskopf, Daniel Moeller, Torsten Oregon Heath Sci Univ AIRC Portland OR 97239 USA Univ Stuttgart VISUS Visualizat Res Ctr D-70569 Stuttgart Germany Simon Fraser Univ Sch Comp Sci Burnaby BC V5A 1S6 Canada

Sort-first distributions have been studied and used far less than sort-last distributions for parallel volume rendering, especially when the data are too large to be replicated fully. We demonstrate that sort-first distributions are not only a viable method of performing data-scalable parallel volume rendering, but more importantly they allow for a range of rendering algorithms and techniques that are not efficient with sort-last distributions. Several of these algorithms are discussed and two of them are implemented in a parallel environment: a new improved variant of early ray termination to speed up rendering when volumetric occlusion occurs and a volumetric shadowing technique that produces more realistic and informative images based on half angle slicing. Improved methods of distributing the computation of the load balancing and loading portions of a subdivided data set are also presented. Our detailed test results for a typical GPU cluster with distributed memory show that our sort-first rendering algorithm outperforms sort-last rendering in many scenarios.

关键词： Volume rendering sort-first parallelization visualization dynamic load balancing early ray termination shadow ray coherence

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visualization of High-Dimensional Point Clouds Using Their Density Distribution's Topology

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ieee TRANSACTIONS ON visualization AND COMPUTER graphics 2011年第11期17卷 1547-1559页

作者： Oesterling, Patrick Heine, Christian Jaenicke, Heike Scheuermann, Gerik Heyer, Gerhard Univ Leipzig Inst Informat D-04009 Leipzig Germany Heidelberg Univ Interdisciplinary Ctr Sci Comp IWR D-69120 Heidelberg Germany

We present a novel method to visualize multidimensional point clouds. While conventional visualization techniques, like scatterplot matrices or parallel coordinates, have issues with either overplotting of entities or handling many dimensions, we abstract the data using topological methods before presenting it. We assume the input points to be samples of a random variable with a high-dimensional probability distribution which we approximate using kernel density estimates on a suitably reconstructed mesh. From the resulting scalar field we extract the join tree and present it as a topological landscape, a visualization metaphor that utilizes the human capability of understanding natural terrains. In this landscape, dense clusters of points show up as hills. The nesting of hills indicates the nesting of clusters. We augment the landscape with the data points to allow selection and inspection of single points and point sets. We also present optimizations to make our algorithm applicable to large data sets and to allow interactive adaption of our visualization to the kernel window width used in the density estimation.

关键词： Clustering pattern analysis point clouds graphs topology

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A Workflow-based Cooperative Project Management System

A Workflow-based Cooperative Project Management System

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10th International symposium on Distributed Computing and Applications to Business, Engineering and Science (DCABES)

作者： Chen, Yi Hou, Kun Wang, Rui Beijing Technol & Business Univ Coll Comp & Informat Engn Beijing Peoples R China

ISBN: (纸本)9780769544151

In modern large enterprises, a complex project is usually composed of a series of processes and needs many persons with different roles cooperating with each other within limited time and investment. A workflow-based cooperative project management system (CPMS) that can support multi-user working is presented in this paper. The system is based on Browser/Server architecture that contains User Interface, Business Logic and data Access three layers in which the core is an XPDL-based workflow engine. A series of cooperative mechanisms such as inclusive gateway, exclusive gateway and parallel gateway are designed to achieve the definition, configuration, and control of the workflow, the assignment, submission and approval of project tasks, the allocation and configuration of project resource. The version control techniques for workflow designs, project plans and project documents are also presented. CPMS has been used in an international enterprise that needs to manage thousands of projects each year. The application result demonstrates that the system can satisfy the needs of cooperative project management.

关键词： Workflow Project management Cooperative work visualization

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Scalable parallel building blocks for custom data analysis

Scalable parallel building blocks for custom data analysis

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ieee symposium on large data Analysis and visualization (LDAV)

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

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.

关键词： Algorithm design and analysis Libraries data structures Computational modeling data models Merging Sorting

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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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ieee symposium on large data Analysis and visualization (LDAV)

作者： Steven Martin Han-Wei Shen Ohio State University USA

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 B 2 .” The bounds, B 1 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.

关键词： Histograms Linear programming Equations Rendering (computer graphics) Context Optimization data visualization

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Revisiting wavelet compression for large-scale climate data using JPEG 2000 and ensuring data precision

Revisiting wavelet compression for large-scale climate data ...

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ieee symposium on large data Analysis and visualization (LDAV)

作者： Jonathan Woodring Susan Mniszewski Christopher Brislawn David DeMarle James Ahrens Los Alamos National Laboratory USA Kitware Inc. USA

We revisit wavelet compression by using a standards-based method to reduce large-scale data sizes for production scientific computing. Many of the bottlenecks in visualization and analysis come from limited bandwidth in data movement, from storage to networks. The majority of the processing time for visualization and analysis is spent reading or writing large-scale data or moving data from a remote site in a distance scenario. Using wavelet compression in JPEG 2000, we provide a mechanism to vary data transfer time versus data quality, so that a domain expert can improve data transfer time while quantifying compression effects on their data. By using a standards-based method, we are able to provide scientists with the state-of-the-art wavelet compression from the signal processing and data compression community, suitable for use in a production computing environment. To quantify compression effects, we focus on measuring bit rate versus maximum error as a quality metric to provide precision guarantees for scientific analysis on remotely compressed POP (parallel Ocean Program) data.

关键词： data visualization Transform coding Image coding Bit rate Quantization Wavelet transforms

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Keynote address: Immersive exploration of large datasets

Keynote address: Immersive exploration of large datasets

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Pacific (formerly Asia-Pacific APVIS) visualization symposium

作者： Arie Kaufman State University of New York Stony Brook USA

Scientists, engineers and physicians are now confronted with a fire hose of data. Immersive visualization environments provide these users with a novel way of interacting and reasoning with large datasets. They allow them to utilize the entirety of their visual bandwidth, effectively engulfing the user in the data and enabling collaborative interaction. We present a custom-built 5-wall Cave environment, called the Immersive Cabin (IC). It is driven by a GPU cluster for both computation and 3D stereo rendering. We also propose a conformal deformation rendering pipeline for the visualization of datasets on partially-immersive platforms. Combined with a range of interaction and navigation tools, our system can support numerous interactive applications of large datasets. Several demonstrations include architectural visualization, urban planning, medical visualization, simulation and rendering of physical phenomena, and entertainment. Current visualization displays, however, have not kept up with the explosive growth in data size and resolution, which is beginning to match the resolution of the visuals that surround us in daily life. To ameliorate this challenge, we have developed a life-like, realistic immersion into the petascale data to be explored, appropriately called The RealityDeck. It is a one-of-a kind pioneering G-pixel immersive and collaborative display system - a unique assembly of high-res display panels, GPU cluster, sensors, networking, computer vision, and human-computer interaction technologies.

关键词： data visualization Conferences Rendering (computer graphics) visualization Wireless sensor networks Awards activities

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