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Pacific (formerly Asia-Pacific APVIS) visualization symposium

作者： Sebastian Grottel Michael Krone Katrin Scharnowski Thomas Ertl Visualization Research Center University of Stuttgart Germany

In many different application fields particle-based simulation, like molecular dynamics, are used to study material properties and behavior. Nowadays, simulation data sets consist of millions of particles and thousands of time steps challenging interactive visualization. Direct glyph-based representations of the particle data are important for the visual analysis process and these rendering methods can be optimized to be able to work sufficiently fast with huge data sets. However, the perception of the implicit spatial structures formed by such data is often hindered by aliasing and visual clutter. Especially the depth of these structures can be grasped better if visual cues are applied, even in interactive representations. We hence present a method to apply object-space ambient occlusion, based on local neighborhood information, to large timedependent particle-based data sets without the need for any precomputations. Based on density information collected in real-time, glyph-based representations of the data sets can be visually enhanced without significant impact on the rendering performance allowing to visualize multi-million particle data sets interactively on commodity workstations.

关键词： Rendering (computer graphics) Geometry graphics processing unit visualization data visualization Equations Mathematical model

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Query-driven parallel exploration of large datasets

Query-driven parallel exploration of large datasets

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ieee symposium on large data Analysis and visualization (LDAV)

作者： Atanas Atanasov Madhusudhanan Srinivasan Tobias Weinzierl Technische Universität München Germany King Abdullah University for Science and Technology Saudi Arabia

Recent advances in supercomputing capabilities pose a multi-faceted data retrieval challenge to the exploration and visualisation of the obtained results: the bandwidth between visualisation devices and the high-performance computing (HPC) clusters neither scales with the simulation data nor with the compute power, the total memory footprint of the data on the supercomputer often exceeds the aggregate memory on the visualisation, and the data has to be distributed among several visualisation nodes working in parallel to render a visual. In the present paper, we introduce an on-demand data exploration paradigm that leverages HPC capabilities and distributed visualisation without requiring a large memory footprint on the visualisation cluster. Regions of interest within the data are specified by the user in the form of queries. These queries, augmented by node identifiers on the visualisation cluster, are automatically distributed among multiple compute nodes of the HPC cluster. The compute nodes work in parallel to assemble and merge data in response to the user query until the data distribution matches the visualisation cluster's topology. Query results are then simultaneously streamed to the right visualisation nodes. Our approach allows for interactive exploration of data residing on HPC resources, irrespective of memory footprint. The streaming of data to the visualisation nodes scales with the bandwidth of the interconnecting network and the HPC cluster's domain decomposition, while the latter is hidden from the visualisation and can change dynamically. We demonstrate the capability of our query-driven approach with a turbulent mixing dataset, and show that it supports interactive data exploration on HPC systems.

关键词： data visualization Supercomputers Computational modeling data models Distributed databases Load modeling Topology

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Development, visualization, and Application of the ARIES Systems Code

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ieee TRANSACTIONS ON PLASMA SCIENCE 2012年第3期40卷 552-556页

作者： Carlson, Lane Tillack, Mark Najmabadi, Farrokh Kessel, Charles Univ Calif San Diego Energy Res Ctr La Jolla CA 92093 USA Princeton Plasma Phys Lab Princeton NJ 08540 USA

The ARIES research program has utilized its comprehensive ARIES systems code (ASC) and a new graphical user interface for visualizing the parameter space as important tools in its analysis of fusion power plant designs. Recently, the ASC has undergone modifications to accommodate different divertor designs, each having unique pumping powers, helium and liquid-metal pump thermal heat recovery, and the latest material, fabrication, and costing algorithms. The modifications and changes made to the code have been documented and verified by members of the ARIES team to ensure accuracy of implementation and self-consistency of design. The code has also been modified to display a wider range of input and output files, formulas, and algorithms for a greater degree of transparency and verification. After the changes to the code were completed and the version was locked, the ASC was employed to scan the physics and technology operating space for relevant power plant designs. Four corners of aggressiveness and conservativeness in both physics and technology serve as the boundaries for the scans within which a range of possible tokamaks exist. The Visual ARIES Systems Scanning Tool (VASST) has been used in parallel with the ASC scans to visualize the tremendous amounts of data resulting from these detailed systems scans. Displaying the data in a colorful and intuitive visual environment and giving the user explorative and visual interaction have helped extract meaningful relationships and trends from the data. Initially, broad scans from the ASC and VASST indicated areas of interest where additional detail was needed. Further scans of higher fidelity helped enhance and further refine the database. After the final scans were completed, VASST facilitated in displaying and filtering the large database to choose two "strawmen" data points at two of the four corners of the aggressive/conservative operating space. These points now serve as reference designs, so more detailed design a

关键词： ARIES fusion power plant systems code tokamak Visual ARIES Systems Scanning Tool (VASST) visualization tool

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A Job Scheduling Design for visualization Services Using GPU Clusters

A Job Scheduling Design for Visualization Services Using GPU...

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ieee International Conference on Cluster Computing

作者： Wei-Hsien Hsu Chun-Fu Wang Kwan-Liu Ma Hongfeng Yu Jacqueline H. Chen University of California Davis USA Sandia National Laboratories Livermore Livermore USA

Modern large-scale heterogeneous computers incorporating GPUs offer impressive processing capabilities. It is desirable to fully utilize such systems for serving multiple users concurrently to visualize large data at interactive rates. However, as the disparity between data transfer speed and compute speed continues to increase in heterogeneous systems, data locality becomes crucial for performance. We present a new job scheduling design to support multi-user exploration of large data in a heterogeneous computing environment, achieving near optimal data locality and minimizing I/O overhead. The targeted application is a parallel visualization system which allows multiple users to render large volumetric data sets in both interactive mode and batch mode. We present a cost model to assess the performance of parallel volume rendering and quantify the efficiency of job scheduling. We have tested our job scheduling scheme on two heterogeneous systems with different configurations. The largest test volume data used in our study has over two billion grid points. The timing results demonstrate that our design effectively improves data locality for complex multi-user job scheduling problems, leading to better overall performance of the service.

关键词： Rendering (computer graphics) data visualization Processor scheduling Dynamic scheduling graphics processing unit

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“3D Cloud” in Life Sciences: An innovative framework for remote 2D/3D visualization and collaboration

“3D Cloud” in Life Sciences: An innovative framework for r...

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Annual ieee symposium on Computer-Based Medical Systems

作者： Livia Torterolo Gianluca Papaleo Silvia Scaglione Francesco Ruffino Maurizio Aiello Nice Srl Italy IEIIT CNR National Research Council Genoa Italy

ISBN: (纸本)9781467320498

A wide range of software has been moving to Cloud platforms, except for 3D applications, which require hardware (access to high-end GPU 1 ) and software (use of libraries for 3D graphics like OpenGL or DirectX) not yet supported. Therefore, we here present an innovative technology, enabling “3D Clouds”, i.e. Clouds able to host 3D applications and provide them “as a service”. Achieving this goal can be very useful in Biomedicine and Life Sciences, where 3D visualization and image analysis play a key role. End users are immediately empowered by taking full advantage of high-end graphics cards, fast I/O performance and large memory nodes hosted in "Public or Private 3D Cloud", rather than waiting for the next upgrade of the graphics workstations. Even if the technology supports a wide range of 3D applications, we here present a case study in molecular modeling field, considering crucial aspects of security and data management.

关键词： Security Software data visualization Hardware Computational modeling Collaboration

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Development, visualization, and Application of the ARIES Systems Code

Development, Visualization, and Application of the ARIES Sys...

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symposium on Fusion Engineering

作者： Carlson, Lane Tillack, Mark Najmabadi, Farrokh Kessel, Charles Univ Calif San Diego Energy Res Ctr La Jolla CA 92093 USA Princeton Plasma Phys Lab Princeton NJ 08540 USA

关键词： ARIES fusion power plant systems code tokamak Visual ARIES Systems Scanning Tool (VASST) visualization tool

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SemanticPrism: A multi-aspect view of large high-dimensional data

SemanticPrism: A multi-aspect view of large high-dimensional...

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ieee symposium on Visual Analytics Science and Technology (VAST)

作者： Victor Yingjie Chen Ahmad M Razip Sungahn Ko Cheryl Zhenyu Qian David S. Ebert Computer Graphics Technology Electrical and Computer Engineering Interaction Design Purdue University

VAST 2012 Mini Challenge 1 Award: Outstanding integrated analysis and visualization. We present a visual analytics system SemanticPrism, which aims to analyze large-scale high-dimensional datasets containing logs of a million computers. SemanticPrism visualizes the data from three different perspectives: geo-temporal, time series curve, and pixel visualization. With each perspective, we use semantic zooming to present more detailed information.

关键词： data visualization Time series analysis IP networks Semantics Bars Image color analysis Visual analytics

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Visualizing Network Traffic to Understand the Performance of Massively parallel Simulations

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ieee TRANSACTIONS ON visualization AND COMPUTER graphics 2012年第12期18卷 2467-2476页

作者： Landge, Aaditya G. Levine, Joshua A. Isaacs, Katherine E. Bhatele, Abhinav Gamblin, Todd Schulz, Martin Langer, Steve H. Bremer, Peer-Timo Pascucci, Valerio Univ Utah Sci Comp & Imaging Inst Salt Lake City UT 84112 USA Univ Calif Davis Davis CA USA Lawrence Livermore Natl Lab Livermore CA USA

The performance of massively parallel applications is often heavily impacted by the cost of communication among compute nodes. However, determining how to best use the network is a formidable task, made challenging by the ever increasing size and complexity of modern supercomputers. This paper applies visualization techniques to aid parallel application developers in understanding the network activity by enabling a detailed exploration of the flow of packets through the hardware interconnect. In order to visualize this large and complex data, we employ two linked views of the hardware network. The first is a 2D view, that represents the network structure as one of several simplified planar projections. This view is designed to allow a user to easily identify trends and patterns in the network traffic. The second is a 3D view that augments the 2D view by preserving the physical network topology and providing a context that is familiar to the application developers. Using the massively parallel multi-physics code pF3D as a case study, we demonstrate that our tool provides valuable insight that we use to explain and optimize pF3D's performance on an IBM Blue Gene/P system.

关键词： Performance analysis network traffic visualization projected graph layouts

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Interactive 4D overview and detail visualization in augmented reality

Interactive 4D overview and detail visualization in augmente...

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International symposium on Mixed and Augmented Reality (ISMAR)

作者： Stefanie Zollmann Denis Kalkofen Christof Hoppe Stefan Kluckner Horst Bischof Gerhard Reitmayr Graz University of Technology Siemens Corporate Technology

In this paper we present an approach for visualizing time-oriented data of dynamic scenes in an on-site AR view. visualizations of time-oriented data have special challenges compared to the visualization of arbitrary virtual objects. Usually, the 4D data occludes a large part of the real scene. Additionally, the data sets from different points in time may occlude each other. Thus, it is important to design adequate visualization techniques that provide a comprehensible visualization. In this paper we introduce a visualization concept that uses overview and detail techniques to present 4D data in different detail levels. These levels provide at first an overview of the 4D scene, at second information about the 4D change of a single object and at third detailed information about object appearance and geometry for specific points in time. Combining the three levels of detail with interactive transitions such as magic lenses or distorted viewing techniques enables the user to understand the relationship between them. Finally we show how to apply this concept for construction site documentation and monitoring.

关键词： data visualization Context Abstracts visualization Image color analysis Geometry Rendering (computer graphics)

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TiledRenderer - An object oriented framework for MPI based parallel Rendering

TiledRenderer - An object oriented framework for MPI based p...

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International Conference on parallel Distributed and Grid Computing (PDGC)

作者： Pritam Prakash Shete Venkata Pinaka Pani Kondapi Dinesh M. Sarode Mohini A. Laghate Surojit Kumar Bose Computer Division Bhabha Atomic Research Centre Mumbai Maharashtra India

A visualization of large datasets requires ultra high resolution. data wall systems provide large number of pixels by combining a power of multiple graphics cards. In this paper, we propose and realize an object oriented framework for the Message Passing Interface based parallel rendering. We introduce a GUI based viewer called the TiledRenderer, which is used for viewing pre-recorded high resolution animations as well as images on data walls. We identify a set of design patterns in a development of the TiledRenderer. We talk about benefits of using design patterns for extending our framework for adding the Real Time Streaming Protocol based IP camera support. We demonstrate that use of design patterns facilitates reusing the existing functionality and adding new functionality by providing new classes, rather than modifying the existing classes or functionality. We also discuss about a visualization of tsunami simulation data by using 6×6 data wall and the TiledRenderer.

关键词： Image resolution Message passing Streaming media Synchronization

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