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14th symposium on large data analysis and visualization

作者： Wald, Ingo Zellmann, Stefan Amstutz, Jefferson Wu, Qi Griffin, Kevin Jaros, Milan Wesner, Stefan NVIDIA Santa Clara CA 95051 USA Univ Cologne Cologne Germany Univ Calif Davis Davis CA USA VSB Tech Univ Ostrava IT4Innovat Ostrava Czech Republic

ISBN: (纸本)9798331516932;9798331516925

We propose and discuss a paradigm that allows for expressing data-parallel rendering with the classically non-parallel ANARI API. We propose this as a new standard for data-parallel rendering, describe two different implementations of this paradigm, and use multiple sample integrations into existing applications to show how easy it is to adopt, and what can be gained from doing so.

关键词： anari distributed rendering ray tracing sci-vis

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A QUICK AND FEATURE BASED visualization ALGORITHM FOR large-SCALE FLOW data

A QUICK AND FEATURE BASED VISUALIZATION ALGORITHM FOR LARGE-...

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ieee International Geoscience and Remote Sensing symposium

作者： Zhong Liang Chi Tian He Zhang Xin Chinese Acad Sci Inst Remote Sensing Applicat Beijing 100101 Peoples R China

ISBN: (纸本)9781424433940

To analyze large amounts of numerical data, one of the most useful approaches is to use scientific visualization to transform them into graphical images. Flow visualization as one of the challenging topics has played important roles in oceanic data analysis. There are many techniques have been presented in the past decade, but most of them can't get high performance to visualize large-scale flow data in real time. To deduce the computational complexity brought by large flow dataset, feature-based expression will be a helpful way. However, how to get the result images quickly without costing much time for feature extraction and analysis is a very important problem to deal. Based on the common characteristic of flow and the unchangeable scale feather of spiral line, we present a new distributing strategy which needn't locate feature points very accurately and didn't rely on the type of feature fields. The visualization procedure not only can straight forward automatically but also can be changed with user's interactive command. The flow data obtained from the South Sea of China was verified and simulated. The result shows that this method using spiral strategy not templates to setting the seeds to emphasize the interesting fields is much faster and flexible, especially in large-scale flow data visualization

关键词： seeds distribution streamline feature field spiral line appending grid controller

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A Flow visualization Using Parallel 3D Line Integral Convolution for large Scale Unstructured Grid data 8

A Flow Visualization Using Parallel 3D Line Integral Convolu...

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

作者： Liao, Yangguang Matsui, Hiroaki Kreylos, Oliver Kellogg, Louise H. Univ Calif Davis KeckCAVE Davis CA 95616 USA Univ Calif Davis CIG Davis CA USA

ISBN: (纸本)9781538668733

One of the greatest challenges facing scientists doing large computation of vector fields in a distributed parallel setting is the need for optimal parallel algorithms for flow visualization. To address this need, we present a new flow visualization method based on parallel 3D line integral convolution (LIC). Our approach uses the fact that 3D LIC only needs limited local information to design an embarrassingly parallel model with a trade-off between the additional memory cost of external cells and the time cost for communication. All data required for each process can be stored in either a local data block or the external cells which are sets of exterior data surrounding the local partition. One problem for parallel LIC is that equal domain size decomposition of the data cannot guarantee balanced parallel processes. To achieve a load-balanced visualization process, we repartition data using an estimate of the LIC computation time. In addition, to minimize the memory cost, we introduce a vector-driven external cell expansion method to reduce the required memory cost. We find that we can use fewer external cells with minimal loss of visual quality. We evaluate the performance of our visualization method by first comparing its parallel scalability with traditional integral field line visualization. Next, we compare our new partition method with other data partition methods to verify that the workload of our model is more balanced. Finally, we compare our external cell expansion method with a traditional layer-based external cell expansion method. Consequently, together with the new partition and external cell expansion methods, our parallel 3D LIC visualization proves to be an efficient and well-balanced parallel flow visualization with limited extra memory cost and a large saving of communication time.

关键词： Flow visualization line integral convolution geodynamo texture-based flow visualization noise model volume illumination GPU programming

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Using Interactive Particle-based Rendering to Visualize a large-scale Time-varying Unstructured Volume with Mixed Cell Types 10

Using Interactive Particle-based Rendering to Visualize a La...

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ieee Pacific visualization symposium (ieee PacificVis)

作者： Zhao, Kun Sakamoto, Naohisa Koyamada, Koji IBM Res Tokyo Tokyo Japan Kobe Univ Kobe Hyogo Japan Kyoto Univ Kyoto Japan

ISBN: (纸本)9781509057382

The primary challenge in the visualization of a large-scale unstructured volume data with mixed cell types is to dissolve a bottleneck caused by visibility sorting of unstructured cells. In this paper, we implement an interactive particle-based rendering method to solve this complex visualization problem. This technique uses opaque particles as the proxy geometry of the mixed unstructured cells so that the visibility sorting process is not needed. This characteristic makes the rendering of mixed-cell unstructured volume efficient. We also construct a resizing function to adjust the particle radius depending on the assigned transfer function so that the transfer function can be adjusted in real time. Furthermore, we develop a time-varying level-of-detail (LOD) rendering to efficiently handle the large-scale time-varying data. This LOD rendering can provide highspeed rendering for animation rendering and high-quality rendering when the animation is stopped at any time step of interest. These features facilitate the detailed analysis of the temporal features of the data.

关键词： unstructured volume large-scale visualization mixed cell time-varying visualization

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Visual analysis on online display advertising data

Visual analysis on online display advertising data

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

作者： Huang, Ling Genome from Yahoo United States

ISBN: (纸本)9781479916597

In recent years online display advertising has grown at a rapid pace. Genome from Yahoo! is the big data buying solution for online display advertising. The goal of our platform is to identify the best opportunity to display an ad to a user who is most likely to take a desired action. Our system contains websites which are visited by several million users per day. The number of attributes related to user events is also of the order of several thousand. Visual analysis has emerged as a powerful technique to facilitate demonstrating data, filtering extreme cases and outliers, exploiting data details, and identifying data analysis tasks. With respect to large-scale online data, the paper presents some use cases on visual analysis at Genome from Yahoo! © 2013 ieee.

关键词： Big data

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3-DIMENSIONAL THERMAL-analysis OF STATOR END-CORE FOR large TURBINE-GENERATORS USING FLOW visualization RESULTS

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ieee TRANSACTIONS ON POWER APPARATUS AND SYSTEMS 1985年第7期104卷 1856-1862页

作者： DOI, S ITO, K NONAKA, S Toshiba Corporation Tokyo Japan

Three-dimensional thermal analysis for the stator end-core of large turbine-generators, which has not been completely solved yet, is developed based on flow velocity measurements using a visual model and on the result... 详细信息

关键词： Testing Stator cores Temperature Eddy currents Distributed computing Thermal conductivity Heat transfer Cooling Ventilation visualization

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WarpIV: In Situ visualization and analysis of Ion Accelerator Simulations

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ieee COMPUTER GRAPHICS AND APPLICATIONS 2016年第3期36卷 22-35页

作者： Rubel, Oliver Loring, Burlen Vay, Jean-Luc Grote, David P. Lehe, Remi Bulanov, Stepan Vincenti, Henri Bethel, E. Wes Lawrence Berkeley Natl Lab Berkeley CA 94720 USA Lawrence Berkeley Natl Lab Div Phys Phys & Life Sci Directorate Berkeley CA 94720 USA Lawrence Berkeley Natl Lab BELLA Ctr Berkeley CA 94720 USA

The generation of short pulses of ion beams through the interaction of an intense laser with a plasma sheath offers the possibility of compact and cheaper ion sources for many applications--from fast ignition and radiography of dense targets to hadron therapy and injection into conventional accelerators. To enable the efficient analysis of large-scale, high-fidelity particle accelerator simulations using the Warp simulation suite, the authors introduce the Warp In situ visualization Toolkit (WarpIV). WarpIV integrates state-of-the-art in situ visualization and analysis using VisIt with Warp, supports management and control of complex in situ visualization and analysis workflows, and implements integrated analytics to facilitate query- and feature-based data analytics and efficient large-scale data analysis. WarpIV enables for the first time distributed parallel, in situ visualization of the full simulation data using high-performance compute resources as the data is being generated by Warp. The authors describe the application of WarpIV to study and compare large 2D and 3D ion accelerator simulations, demonstrating significant differences in the acceleration process in 2D and 3D simulations. WarpIV is available to the public via https://***/berkeleylab/warpiv. The Warp In situ visualization Toolkit (WarpIV) supports large-scale, parallel, in situ visualization and analysis and facilitates query- and feature-based analytics, enabling for the first time high-performance analysis of large-scale, high-fidelity particle accelerator simulations while the data is being generated by the Warp simulation suite. This supplemental material https://***/extra/*** provides more details regarding the memory profiling and optimization and the Yee grid recentering optimization results discussed in the main article. [ABSTRACT FROM PUBLISHER]

关键词： Acceleration Analytical models Computational modeling computer graphics data analysis data models data visualization in situ visualization Ion accelerators ion beams nuclear sciences Object oriented modeling particle beams particle rendering plasma sciences

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Portable and Composable Flow Graphs for In Situ Analytics 11

Portable and Composable Flow Graphs for In Situ Analytics

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

作者： Shudler, Sergei Petruzza, Steve Pascucci, Valerio Bremer, Peer-Timo Lawrence Livermore Natl Lab Livermore CA 94550 USA Utah State Univ Logan UT 84322 USA Univ Utah Salt Lake City UT 84112 USA

ISBN: (纸本)9781665432832

Existing data analysis and visualization algorithms are used in a wide range of simulations that strive to support an increasing number of runtime systems. The BabelFlow framework has been designed to address this situation by providing users with a simple interface to implement analysis algorithms as dataflow graphs portable across different runtimes. The limitation in BabelFlow, however, is that the graphs are not easily reusable. Plugging them into existing in situ workflows and constructing more complex graphs is difficult. In this paper, we introduce LegoFlow, an extension to BabelFlow that addresses these challenges. Specifically, we integrate LegoFlow into Ascent, a flyweight framework for large scale in situ analytics, and provide a graph composability mechanism. This mechanism is an intuitive approach to link an arbitrary number of graphs together to create more complex patterns, as well as avoid costly reimplementations for minor modifications. Without sacrificing portability, LegoFlow introduces complete flexibility that maximizes the productivity of in situ analytics workflows. Furthermore, we demonstrate a complete LULESH simulation with LegoFlow-based in situ visualization running on top of Charm++. It is a novel approach for in situ analytics, whereby the asynchronous tasking runtime allows routines for computation and analysis to overlap. Finally, we evaluate a number of LegoFlow-based filters and extracts in Ascent, as well as the scaling behavior of a LegoFlow graph for Radix-k based image compositing.

关键词： Software and its engineering data flow architectures Human-centered computing visualization Scientific visualization

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Feature Tracking Utilizing a Maximum-Weight Independent Set Problem 9

Feature Tracking Utilizing a Maximum-Weight Independent Set ...

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

作者： Schnorr, Andrea Helmrich, Dirk N. Childs, Hank Kuhlen, Torsten W. Hentschel, Bernd Rhein Westfal TH Aachen Visual Comp Inst JARA HPC Aachen Germany Univ Oregon Eugene OR 97403 USA

ISBN: (纸本)9781728126050

Tracking the temporal evolution of features in time-varying data remains a combinatorially challenging problem. A recent method models event detection as a maximum-weight independent set problem on a graph representation of all possible explanations [35]. However, optimally solving this problem is NP-hard in the general case. Following the approach by Schnorr et al., we propose a new algorithm for event detection. Our algorithm exploits the model-specific structure of the independent set problem. Specifically, we show how to traverse potential explanations in such a way that a greedy assignment provides reliably good results. We demonstrate the effectiveness of our approach on synthetic and simulation data sets, the former of which include ground-truth tracking information which enable a quantitative evaluation. Our results are within 1% of the theoretical optimum and comparable to an approximate solution provided by a state-of-the-art optimization package. At the same time, our algorithm is significantly faster.

关键词： Feature Tracking Graph Optimization Approximation Flow visualization Dissipation Elements

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DPP-PMRF: Rethinking Optimization for a Probabilistic Graphical Model Using data-Parallel Primitives 8

DPP-PMRF: Rethinking Optimization for a Probabilistic Graphi...

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

作者： Lessley, Brenton Perciano, Talita Heinemann, Colleen Camp, David Childs, Hank Bethel, E. Wes Univ Oregon Eugene OR 97403 USA Lawrence Berkeley Natl Lab Berkeley CA USA

ISBN: (纸本)9781538668733

We present a new parallel algorithm for probabilistic graphical model optimization. The algorithm relies on data-parallel primitives (DPPs), which provide portable performance over hardware architecture. We evaluate results on CPUs and GPUs for an image segmentation problem. Compared to a serial baseline, we observe runtime speedups of up to 13X (CPU) and 44X (GPU). We also compare our performance to a reference, OpenMP-based algorithm, and find speedups of up to 7X (CPU).

关键词： Mathematics of computing-Graph algorithms Markov networks Expectation maximization Computing methodologies-Image processing Shared memory

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