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ieee symposium on large data Analysis and visualization

作者： Ruan, Guangchen Zhang, Hui Indiana Univ Sch Informat & Comp Bloomington IN 47405 USA Indiana Univ Pervas Technol Inst Bloomington IN 47405 USA

ISBN: (纸本)9781479952151

With dental imaging data acquired at unprecedented speed and resolution, traditional serial image processing and single-node storage need to be re-examined in a "Bigdata" context. Furthermore, most previous dental computing has focused on the actual imaging acquisition and image analysis tools, while much less research has focused on enabling caries assessment via visual analysis of large dental imaging data. In this paper we present DENVIS, an end-to-end solution for cariologists to manage, mine, visualize, and analyze large dental imaging data for investigative carious lesion studies. DENVIS consists of two main parts: data driven image analysis modules triggered by imaging data acquisition that exploit parallel MapReduce tasks and ingest visualization archive into a distributed NoSQL store, and user driven modules that allow investigative analysis at run time. DENVIS has seen early use by our collaborators in oral health research, where our system has been used to pose and answer domain-specific questions for quantitative assessment of dynamic carious lesion activities.

关键词： dental computing visual knowledge discovery MapReduce I.6.8 [SIMULATION AND MODELING]: Types of Simulation parallel H.5.2 [INFORMATION INTERFACES AND PRESENTATION]: User Interfaces Graphical user interfaces

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Efficient parallel volume rendering of large-scale adaptive mesh refinement data

Efficient parallel volume rendering of large-scale adaptive ...

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2013 3rd ieee symposium on large-Scale data Analysis and visualization, LDAV 2013

作者： Leaf, Nick Vishwanath, Venkatram Insley, Joseph Hereld, Mark Papka, Michael E. Ma, Kwan-Liu University of California Davis United States Argonne National Laboratory United States Northern Illinois University United States

ISBN: (纸本)9781479916597

Adaptive Mesh Refinement is a popular approach for allocating scarce computing resources to the most important portions of the simulation domain. This approach implies spatial compression and the large simulation sizes which necessitate it. We present a novel, cluster- and GPU-parallel rendering scheme for AMR data, which is built on previous work in the GPU ray casting of AMR data. Our approach utilizes the existing AMR structure to subdivide the problem into convexly-bounded chunks and perform static load-balancing. We take advantage of data locality within chunks to interpolate directly between blocks without the need to store ghost cells on the interior boundaries. We also present a novel block decomposition method, and analyze its performance against two alternative methods. Finally, we examine the interactivity of our renderer for multiple datasets, and consider its scalability across a large number of GPUs. © 2013 ieee.

关键词： Volume rendering

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Visualizing business data with generalized treemaps

Visualizing business data with generalized treemaps

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ieee visualization Conference (Vis 2006)/ieee symposium on Information visualization (InfoVis 2006)

作者： Vliegen, Roel van Wijk, Jarke J. van der Linden, Erik-Jan Tech Univ Eindhoven NL-5600 MB Eindhoven Netherlands

Business data is often presented using simple business graphics. These familiar visualizations are effective for providing overviews, but fall short for the presentation of large amounts of detailed information. Treemaps can provide such detail, but are often not easy to understand. We present how standard treemap algorithms can be adapted such that the results mimic familiar business graphics. Specifically, we present the use of different layout algorithms per level, a number of variations of the squarified algorithm, the use of variable borders, and the use of non-rectangular shapes. The combined use of these leads to histograms, pie charts and a variety of other styles.

关键词： information visualization treemap business graphics hierarchical data

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parallel Structured Mesh Generation with Disparity Maps by GPU Implementation

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ieee TRANSACTIONS ON visualization AND COMPUTER graphics 2015年第9期21卷 1045-1057页

作者： Wang, Hongjian Zhang, Naiyu Creput, Jean-Charles Moreau, Julien Ruichek, Yassine UTBM Syst & Transportat Lab SeT Res Inst Transportat Energy & Soc IRTES F-90000 Belfort France

The goal of structured mesh is to generate a compressed representation of the 3D surface, where near objects are provided with more details than objects far from the camera, according to the disparity map. The solution is based on the Kohonens Self-Organizing Map algorithm for the benefits of its ability to generate a topological map according to a probability distribution and its potential to be a natural massive parallel algorithm. The disparity map, which stands for a density distribution that reflects the proximity of objects to the camera, is partitioned into an appropriate number of cell units, in such a way that each cell is associated to a processing unit and responsible of a certain area of the plane. The advantage of the proposed model is that it is decentralized and based on data decomposition. The required processing units and memory are with linearly increasing relationship to the problem size. Experimental results show that our GPU implementation is able to provide near real-time performance with small size disparity maps and the running time increases in a linear way with a very weak increasing coefficient. The proposed method is suitable to deal with large scale problems in a massively parallel way.

关键词： parallel cellular model mesh generation disparity map self-organizing map GPU implementation

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Hybrid Scheduling for parallel Rendering using Coherent Ray Tasks

Hybrid Scheduling for Parallel Rendering using Coherent Ray ...

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1999 ieee symposium on parallel visualization and graphics, PVGS 1999

作者： Reinhard, Erik Chalmers, Alan Jansen, Frederik W. University of Bristol Dept. of Computer Science Merchant Venturers Building Woodland Road BristolBS8 1UB United Kingdom Delft University of Technology Fac. of Information Technology and Systems Zuidplantsoen 4 Delft2628 BZ Netherlands

ISBN: (纸本)1581132379

parallelising ray tracing with a data parallel approach allows rendering of arbitrarily large models, but the inherent load imbalances may lead to severe inefficiencies. To compensate for the uneven load distribution, demand-driven tasks may be split off and scheduled to processors that are less busy. We propose a hybrid scheduling algorithm which brings tasks and data together according to coherence between rays. The amount of demand-driven versus dataparallel tasks is a function of the coherence between rays and the amount of imbalance in the basic data-parallel load. Processing power, communication and memory are three resources which should be evenly used. Our current implementation is assessed against these requirements, showing good scalability and very little communication at the cost of a slightly larger memory overhead.

关键词： Ray tracing

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parallel clustering for visualizing large scientific line data

Parallel clustering for visualizing large scientific line da...

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1st ieee symposium on large-Scale data Analysis and visualization 2011, LDAV 2011

作者： Wei, Jishang Yu, Hongfeng Chen, Jacqueline H. Ma, Kwan-Liu University of California Davis CA United States Sandia National Laboratories United States

ISBN: (纸本)9781467301541

Scientists often need to extract, visualize and analyze lines from vast amounts of data to understand dynamic structures and interactions. The effectiveness of such a visual validation and analysis process mainly relies on a good strategy to categorize and visualize the lines. However, the sheer size of line data produced by state-of-the-art scientific simulations poses great challenges to preparing the data for visualization. In this paper, we present a parallelization design of regression model-based clustering to categorize large line data derived from detailed scientific simulations by leveraging the power of heterogeneous computers. This parallel clustering method employs the Expectation Maximization algorithm to iteratively approximate the optimal data partitioning. First, we use a sorted-balance algorithm to partition and distribute the lines with various lengths among multiple compute nodes. During the following iterative clustering process, regression model parameters are recovered based on the local lines on each individual node, with only a few inter-node message exchanges involved. Meanwhile, the workload of regression model computing is well balanced across the nodes. The experimental results demonstrate that our approach can effectively categorize large line data in a scalable manner to concisely convey dynamic structures and interactions, leading to a visualization that captures salient features and suppresses visual clutter to facilitate scientific exploration of large line data. © 2011 ieee.

关键词： visualization

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A Distributed-Memory parallel Approach for Volume Rendering with Shadows 13

A Distributed-Memory Parallel Approach for Volume Rendering ...

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13th ieee symposium on large data Analysis and visualization (LDAV)

作者： Mathai, Manish Larsen, Matthew Childs, Hank Univ Oregon Eugene OR 97403 USA Luminary Cloud Redwood City CA USA

ISBN: (纸本)9798350330182

We present a parallel, distributed-memory technique that enhances traditional ray-casting volume rendering of large data sets to highlight the depth and perception of interesting volumetric features. The technique introduces a lighting system that accounts for global shadows across distributed MPI nodes while using shared-memory parallelism within each node to compute shading information efficiently. The first stage of the approach involves estimating energy attenuation from a point light source through the global volume, using a reduced spatial resolution representation of the volume, with minimal global communication between nodes. It is then used in the second stage during volume rendering to shade sample points captured during ray-casting, generating a high-quality image. In this work, we study the technique's performance across varying spatial resolutions of the estimated light attenuation using synthetic and real-world volumetric data sets on distributed systems.

关键词： Volume rendering

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STREAMIT: Dynamic visualization and Interactive Exploration of Text Streams

STREAMIT: Dynamic Visualization and Interactive Exploration ...

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4th ieee Pacific visualization symposium

作者： Alsakran, Jamal Chen, Yang Zhao, Ye Yang, Jing Luo, Dongning Kent State Univ Kent OH 98032 USA Univ N Carolina Chapel Hill NC 27515 USA

ISBN: (纸本)9781612849324

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 system streams texts dataset visualization Interactive System performance rivers user-computer interaction Consumers Visual analytics Dynamic systems Exploration graphic images User Interface Device Component

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Amortised Encoding for large High-Resolution Displays 11

Amortised Encoding for Large High-Resolution Displays

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

作者： Friess, Florian Braun, Matthias Reina, Guido Ertl, Thomas Univ Stuttgart Stuttgart Germany

ISBN: (纸本)9781665432832

Both visual detail and a low-latency transfer of image data are required for collaborative exploration of scientific data sets across large high-resolution displays. In this work, we present an approach that reduces the resolution before the encoding and uses temporal upscaling to reconstruct the full resolution image, reducing the overall latency and the required bandwidth without significantly impacting the details perceived by observers. Our approach takes advantage of the fact that humans do not perceive the full details of moving objects by providing a perfect reconstruction for static parts of the image, while non-static parts are reconstructed with a lower quality. This strategy enables a substantial reduction of the encoding latency and the required bandwidth with barely noticeable changes in visual quality, which is crucial for collaborative analysis across display walls at different locations. Additionally, our approach can be combined with other techniques aiming to reduce the required bandwidth while keeping the quality as high as possible, such as foveated encoding. We demonstrate the reduced overall latency, the required bandwidth, as well as the high image quality using different visualisations.

关键词： Human-centered computing visualization systems and tools Computing methodologies graphics systems and interfaces

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A Proposed Framework for Interactive Virtual Reality In Situ visualization of parallel Numerical Simulations 9

A Proposed Framework for Interactive Virtual Reality In Situ...

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9th ieee symposium on large data Analysis and visualization (LDAV)

作者： Gupta, Aryaman Guenther, Ulrik Incardona, Pietro Aydin, Ata Deniz Dachselt, Raimund Gumhold, Stefan Sbalzarini, Ivo F. Tech Univ Dresden Dresden Germany CSBD Dresden Germany MPI CBG Dresden Germany Tech Univ Dresden Interact Media Lab Dresden Cluster Excellence Phys Life Dresden Germany Tech Univ Dresden Cluster Excellence Phys Life Dresden Germany Tech Univ Dresden CSBD Dresden Germany MPI CBG Cluster Excellence Phys Life Dresden Germany

ISBN: (纸本)9781728126050

As computer simulations progress to increasingly complex, nonlinear, and three-dimensional systems and phenomena, intuitive and immediate visualization of their results is becoming crucial. While Virtual Reality (VR) and Natural User Interfaces (NUIs) have been shown to improve understanding of complex 3D data, their application to live in situ visualization and computational steering is hampered by performance requirements. Here, we present the design of a software framework for interactive VR in situ visualization of parallel numerical simulations, as well as a working prototype implementation. Our design is targeted towards meeting the performance requirements for VR, and our work is packaged in a framework that allows for easy instrumentation of simulations. Our preliminary results inform about the technical feasibility of the architecture, as well as the challenges that remain.

关键词： Computing methodologies Massively parallel and high-performance simulations Human-centered computing Virtual reality

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