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检索条件"任意字段=4th IEEE Symposium on Large Data Analysis and Visualization, LDAV 2014"

共 68 条记录，以下是1-10 订阅

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Remote visualization of large Scale Fast Dynamic Simulations in a HPC Context 4

Remote Visualization of Large Scale Fast Dynamic Simulations...

引用

ieee symposium on large data analysis and visualization

作者： Vivodtzev, Fabien Bertron, Isabelle CEA French Atom Energy Commiss Paris France

ISBN: (纸本)9781479952151

this paper details the conception of a remote and powerful visualization tool intended to be directly used by physicists in order to better understand the physical phenomena in the field of fast dynamics simulations. the goal is to explore large dataset composed of billions of cells distributed in thousands of domains on a supercomputer. the solution uses the visualization tool VisIt [1] adapted with specific developments based on the knowledge of both the simulation code and the supercomputer architecture used to run the simulations.

关键词： visualization systems and tools Fast dynamics

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Visualizing results in the SALOME platform for large numerical simulations: an integration of ParaView 4

Visualizing results in the SALOME platform for large numeric...

引用

ieee symposium on large data analysis and visualization

作者： Ribes, Alejandro Bruneton, Adrien EDF R&D Paris France CEA Paris France

ISBN: (纸本)9781479952151

SALOME is an Open Source numerical simulation platform that allows the complete realization of a numerical study. Indeed, the user can easily plug his core numerical code in the platform, define the problem geometry, mesh it, define the boundary conditions, run the solver on a supercomputer, visualize the result and analyze the data;all these actions are performed in an integrated and coherent environment. SALOME can deal with large numerical simulations, like the ones found in multi-physics and/or parametric studies. In this context, ParaView has been integrated into the platform to benefit from its capacity to visualize large models. In this abstract we give an overview of the capabilities of SALOME/ParaView.

关键词： large simulations visualization numerical simulation ParaView SALOME

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Movie Analytics: visualization of the Co-starring Network 4

Movie Analytics: Visualization of the Co-starring Network

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ieee symposium on large data analysis and visualization

作者： Haughton, Dominique McLaughlin, Mark-David Mentzer, Kevin Zhang, Changan Bentley Univ Waltham MA USA Univ Paris 01 Paris France Univ Toulouse 1 Toulouse France Cisco Syst San Jose CA USA Epsilon Waltham MA USA

ISBN: (纸本)9781479952151

this poster contributes a novel application of social network visualization techniques to the motion picture industry. We make the case and illustrate with examples that a visualization approach based on k-cores helps alleviate otherwise inextricable memory issues in analyses of the IMDb co-starring network, which contains more than 2.6 million actors displaying over a billion links, with degrees which can rise to about 50,000 and above for the most connected actors.

关键词： Movie Analytics k-core decomposition IMDb

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In-situ Processing and Interactive visualization for large-Scaled Numerical Simulations 4

In-situ Processing and Interactive Visualization for Large-S...

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ieee symposium on large data analysis and visualization

作者： Chen, Fang Flatken, Markus Hotz, Ingrid Gerndt, Andreas German Aerosp Ctr DLR Simulat & Software Technol Cologne Germany

ISBN: (纸本)9781479952151

With the increasing power of the HPC hardware systems, numerical simulations are heading towards exa-scale computing. Early inspection and analysis of on-going large simulations enables domain experts to obtain first insight into their running simulation process and intermediate results. Compared to conventional post-processing, such in-situ processing has the advantage of keeping data in memory, avoiding to store the large amount of raw data to disk, providing on-the-fly analysis, and preventing early failures in the simulation process. In this poster we present a distributed and scalable software infrastructure, which provides distributed insitu data processing, feature extraction and interactive exploration at user's front-end. We have integrated and extended our system to multiple simulation applications, ranging from Lattice-Boltzmann blood flow simulation to grid based simulation for propulsion systems. A user-interactive front-end is integrated to our system, allowing to directly interact with the visualization of running simulations, gain insight, and make decisions.

关键词： data handling

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Space-Time Volumetric Depth Images for In-Situ visualization 4

Space-Time Volumetric Depth Images for In-Situ Visualization

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ieee symposium on large data analysis and visualization

作者： Fernandes, Oliver Frey, Steffen Sadlo, Filip Ertl, thomas Univ Stuttgart Stuttgart Germany

ISBN: (纸本)9781479952151

Volumetric depth images (VDI) are a view-dependent representation that combines the high quality of images with the explorability of 3D fields. By compressing the scalar data along view rays into sets of coherent supersegments, VDIs provide an efficient representation that supports a-posteriori changes of camera parameters. In this paper, we introduce space-time VDIs that achieve the data reduction that is required for efficient in-situ visualization, while still maintaining spatiotemporal flexibility. We provide an efficient space-time representation of VDI streams by exploiting inter-ray and inter-frame coherence, and introduce delta encoding for further data reduction. Our space-time VDI approach exhibits small computational overhead, is easy to integrate into existing simulation environments, and may help pave the way toward exascale computing.

关键词： I.3.3 [Computer Graphics]: Picture/Image Generation I.6.6 [Simulation and Modeling]: Simulation Output analysis

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Visualizing large 3D Geodesic Grid data with Massively Distributed GPUs 4

Visualizing Large 3D Geodesic Grid Data with Massively Distr...

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ieee symposium on large data analysis and visualization

作者： Xie, Jinrong Yu, Hongfeng Ma, Kwan-Liu Univ Calif Davis Davis CA 95616 USA Univ Nebraska Lincoln NE USA

ISBN: (纸本)9781479952151

Geodesic grids become increasingly prevalent in large weather and climate applications. the deluge amount of simulation data demands efficient and scalable visualization capabilities for scientific exploration and understanding. Given the unique characteristics of geodesic grids, no current techniques can scalably visualize scalar fields defined on a geodesic grid. In this paper, we present a new parallel ray-casting algorithm for large geodesic grids using massively distributed GPUs. We construct a spherical quadtree to adaptively partition and distribute the data according to the grid resolution of simulation, and ensure a balanced workload assignment over a large number of processors from different view angles. We have designed and implemented the entire rendering pipeline based on the MPI and CUDA architecture, and demonstrated the effectiveness and scalability of our approach using an example of large application on a supercomputer with thousands of GPUs.

关键词： Supercomputers

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ADR visualization: A Generalized Framework for Ranking large-Scale Scientific data using analysis-Driven Refinement 4

ADR Visualization: A Generalized Framework for Ranking Large...

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ieee symposium on large data analysis and visualization

作者： Nouanesengsy, Boonthanome Woodring, Jonathan Patchett, John Myers, Kary Ahrens, James Los Alamos Natl Lab Los Alamos NM 87544 USA

ISBN: (纸本)9781479952151

Prioritization of data is necessary for managing large-scale scientific data, as the scale of the data implies that there are only enough resources available to process a limited subset of the data. For example, data prioritization is used during in situ triage to scale with bandwidth bottlenecks, and used during focus+context visualization to save time during analysis by guiding the user to important information. In this paper, we present ADR visualization, a generalized analysis framework for ranking large-scale data using analysis -Driven Refinement (ADR), which is inspired by Adaptive Mesh Refinement (AMR). A large-scale data set is partitioned in space, time, and variable, using user-defined importance measurements for prioritization. this process creates a prioritization tree over the data set. Using this tree, selection methods can generate sparse data products for analysis, such as focus+context visualizations or sparse data sets.

关键词： data triage focus plus context large-scale data big data scientific data prioritization adaptive mesh refinement I.3.1 [Computer Graphics]: Hardware Architecture-Parallel processing I.3.3 [Computer Graphics]: Picture/Image Generation-Viewing algorithms

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UnityMol: Interactive Scientific visualization for Integrative Biology 4

UnityMol: Interactive Scientific Visualization for Integrati...

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ieee symposium on large data analysis and visualization

作者： Doutreligne, Sebastien Cragnolini, Tristan Pasquali, Samuela Derreumaux, Philippe Baaden, Marc Univ Paris Diderot Sorbonne Paris Cite CNRS UPR9080 Lab Biochim Theor 13 Rue Pierre & Marie Curie F-75005 Paris France

ISBN: (纸本)9781479952151

A broad challenge facing scientists today is the availability of huge amounts of data from various sources. Computers are required to store, analyze, explore and represent these data in order to extract useful information. With UnityMol, we pursue the ambitious goal to create an interactive virtual laboratory enabling researchers in biology to visualize biomolecular systems, run simulations and interact with physical models and data. Visual effects can enrich the dynamic and immersive aspects. Ultimately, we want to combine an appealing visual feedback already in place with a set of analysis features to extract information about properties of the fascinating biomolecular systems under study.

关键词： biology computing data visualisation molecular biophysics UnityMol biomolecular system visualization data analysis data exploration data representation information extraction integrative biology interactive scientific visualization interactive virtual laboratory visual effect visual feedback Biological system modeling Computational modeling data visualization RNA Solid modeling visualization data visualisation Visual effects biology computing Biological system modeling molecular biology entity modeling Visual Feedback Representation of data Information Extraction Computational modeling visualization information retrieval RNA data analysis

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data-Parallel Halo Finding with Variable Linking Lengths 4

Data-Parallel Halo Finding with Variable Linking Lengths

引用

ieee symposium on large data analysis and visualization

作者： Widanagamaachchi, Wathsala Bremer, Peer-Timo Sewell, Christopher Lo, Li-Ta Ahrens, James Pascucci, Valerio Univ Utah SCI Inst Salt Lake City UT 84112 USA Lawrence Livermore Natl Lab Livermore CA USA Los Alamos Natl Lab Los Alamos NM USA

ISBN: (纸本)9781479952151

State-of-the-art cosmological simulations regularly contain billions of particles, providing scientists the opportunity to study the evolution of the Universe in great detail. However, the rate at which these simulations generate data severely taxes existing analysis techniques. therefore, developing new scalable alternatives is essential for continued scientific progress. Here, we present a dataparallel, friends-of-friends halo finding algorithm that provides unprecedented flexibility in the analysis by extracting multiple linking lengths. Even for a single linking length, it is as fast as the existing techniques, and is portable to multi-threaded many-core systems as well as co-processing resources. Our system is implemented using PISTON and is coupled to an interactive analysis environment used to study halos at different linking lengths and track their evolution over time.

关键词： H.3 [INFORMATION STORAGE AND RETRIEVAL]: Information Search and Retrieval Clustering J.2 [PHYSICAL SCIENCES AND ENGINEERING]: Astronomy

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CosMovis: Analyzing Semantic Network of Sentiment Words in Movie Reviews 4

CosMovis: Analyzing Semantic Network of Sentiment Words in M...

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ieee symposium on large data analysis and visualization

作者： Ha, Hyoji Kim, Gi-nam Hwang, Wonjoo Choi, Hanmin Lee, Kyungwon Ajou Univ Life Media Interdisciplinary Program Suwon 441749 South Korea Ajou Univ Dept Digital Media Suwon 441749 South Korea

ISBN: (纸本)9781479952151

In this paper, we present the new method to easily recognize intricate network and cluster by connecting Multidimensional Scaling( MDS) Map and Social Network Graph, and comprehend the feature of each node using Heatmap visualization. For the sake of this method, this paper used netizen's movie review data. Also, the process is as follow : 1) We calculated the frequency of sentiment word from each movie review. 2) We designed Heatmap visualization which easily apprehends main emotion of netizens which appear in each movie review. 3) We made location of each node reflect the frequency of sentiment word by designing Sentiment-Movie Network made up of combining MDS Map and Socal Network Graph, as well as we embodied Network Graph to make same nodes form cluster. 4) By granting meaning in accordance with characteristic of clustering, we applied asterism graphic to facilitate cognitive interpretation. Our demonstration is available to http://***/cosmovis/.

关键词： Semantic networks Sentiment word analysis Review mining

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