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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41-50 订阅

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Multi-threaded streamline tracing for data-intensive architectures

Multi-threaded streamline tracing for data-intensive archite...

引用

ieee symposium on large data analysis and visualization (ldav)

作者： Ming Jiang Brian Van Essen Cyrus Harrison Maya Gokhale Lawrence Livermore National Laboratory

Streamline tracing is an important tool used in many scientific domains for visualizing and analyzing flow fields. In this work, we examine a shared memory multi-threaded approach to streamline tracing that targets emerging data-intensive architectures. We take an in-depth look at data management strategies for streamline tracing in terms of issues, such as memory latency, bandwidth, and capacity limitations, that are applicable to future HPC platforms. We present two data management strategies for streamline tracing and evaluate their effectiveness for data-intensive architectures with locally attached Flash. We provide a comprehensive evaluation of both strategies by examining the strong and weak scaling implications of a variety of parameters. We also characterize the relationship between I/O concurrency and I/O efficiency to guide the selection of strategy based on use case. From our experiments, we find that using kernel-managed memory-map for out-of-core streamline tracing can outperform optimized user-managed cache.

关键词： Random access memory Concurrent computing Nonvolatile memory Layout Standards Memory management

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Multivariate volume visualization through dynamic projections

Multivariate volume visualization through dynamic projection...

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ieee symposium on large data analysis and visualization (ldav)

作者： Shusen Liu Bei Wang Jayaraman J. thiagarajan Peer-Timo Bremer Valerio Pascucci SCI Institute University of Utah Lawrence Livermore National Laboratory

We propose a multivariate volume visualization framework that tightly couples dynamic projections with a high-dimensional transfer function design for interactive volume visualization. We assume that the complex, high-dimensional data in the attribute space can be well-represented through a collection of low-dimensional linear subspaces, and embed the data points in a variety of 2D views created as projections onto these subspaces. through dynamic projections, we present animated transitions between different views to help the user navigate and explore the attribute space for effective transfer function design. Our framework not only provides a more intuitive understanding of the attribute space but also allows the design of the transfer function under multiple dynamic views, which is more flexible than being restricted to a single static view of the data. For large volumetric datasets, we maintain interactivity during the transfer function design via intelligent sampling and scalable clustering. Using examples in combustion and climate simulations, we demonstrate how our framework can be used to visualize interesting structures in the volumetric space.

关键词： data visualization Principal component analysis Hurricanes Navigation Transfer functions Image color analysis Space exploration

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data-parallel halo finding with variable linking lengths

Data-parallel halo finding with variable linking lengths

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ieee symposium on large data analysis and visualization (ldav)

作者： Wathsala Widanagamaachchi Peer-Timo Bremer Christopher Sewell Li-Ta Lo James Ahrens Valerio Pascuccik SCI Institute University of Utah SCI Institute Lawrence Livermore National Laboratory Los Alamos National Laboratory University of Utah Salt Lake City UT US

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： Joining processes Pistons Vectors Computational modeling Shape Libraries Laboratories

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Improved post hoc flow analysis via Lagrangian representations

Improved post hoc flow analysis via Lagrangian representatio...

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ieee symposium on large data analysis and visualization (ldav)

作者： Alexy Agranovsky David Camp Christoph Garth E. Wes Bethel Kenneth I. Joy Hank Childs University of California Davis Davis CA US Lawrence Berkeley National Laboratories University of Kaiserslauternt Germany University of California Davis University of Oregon Lawrence Berkeley National Laboratory

Fluid mechanics considers two frames of reference for an observer watching a flow field: Eulerian and Lagrangian. the former is the frame of reference traditionally used for flow analysis, and involves extracting particle trajectories based on a vector field. With this work, we explore the opportunities that arise when considering these trajectories from the Lagrangian frame of reference. Specifically, we consider a form where flows are extracted in situ and then used for subsequent post hoc analysis. We believe this alternate, Lagrangian-based form will be increasingly useful, because the Eulerian frame of reference is sensitive to temporal frequency, and architectural trends are causing temporal frequency to drop rapidly on modern supercomputers. We support our viewpoint by running a series of experiments, which demonstrate the Lagrangian form can be more accurate, require less I/O, and be faster when compared to traditional advection.

关键词： Vectors Accuracy Trajectory Interpolation data models Educational institutions data visualization

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CosMovis: Analyzing semantic network of sentiment words in movie reviews

CosMovis: Analyzing semantic network of sentiment words in m...

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ieee symposium on large data analysis and visualization (ldav)

作者： Hyoji Ha Gi-nam Kim Wonjoo Hwang Hanmin Choi Kyungwon Lee Life Media Interdisciplinary Program Ajou University Department of Digital Media Ajou University

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： Motion pictures Heating data visualization Semantics Social network services Electronic mail

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In-situ multi-resolution and temporal data compression for visual exploration of large-scale scientific simulations

In-situ multi-resolution and temporal data compression for v...

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ieee symposium on large data analysis and visualization (ldav)

作者： Henry Lehmann Bernhard Jung Virtual Reality and Multimedia Group Technical University Bergakademie Freiberg Germany Technische Universitat Bergakademie Freiberg Freiberg Sachsen DE

Today's large-scale scientific simulations generate massive data sets that pose challenges both for data storage in HPC environments during the simulation phase and the subsequent data analysis phase. A promising approach for reducing the amount of data written out during simulation run is in-situ compression. However, even the compressed data sets are typically still too large for interactive visual data exploration which calls for multi-resolution data layouts. the recently proposed ISABELA method for lossy in-situ compression was shown to outperform other compression methods for scientific data sets. In this paper, we propose two main extensions to the ISABELA method: (1) an interlaced data layout that supports decompression of multi-resolution views of the data without overhead in the compressed format; (2) a new temporal compression scheme for improving the compression rate by exploiting temporal coherence in the data set. the compressed multi-resolution data can easily be transformed to the VTK AMR (adaptive multi-resolution) data format to support interactive exploration in ParaView and other visualization tools based on VTK. During the simulation phase, there is no significant increase of computational demands for the generation of complete multi-resolution compressed data sets as compared to flat ISABELA compression. During the analysis phase, due to the AMR data layout, our method supports selective loading of regions of interests as well as progressive loading of data sets, thus enabling interactive visualizations of large-scale scientific simulations.

关键词： Splines (mathematics) Signal resolution Abstracts Adaptation models Indexes Approximation methods Approximation algorithms

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Out-of-core visualization of time-varying hybrid-grid volume data

Out-of-core visualization of time-varying hybrid-grid volume...

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ieee symposium on large data analysis and visualization (ldav)

作者： Min Shih Yubo Zhang Kwan-Liu Ma Jayanarayanan Sitaraman Dimitri Mavriplis University of California Davis University of Wyoming

Traditional computational fluid dynamics (CFD) solvers are usually written for a single gridding paradigm such as structured-Cartesian, structured-body-fitted, or unstructured grids. Each type of mesh paradigms has inherent advantages and disadvantages. thus, the methods of coupling multiple mesh paradigms have been developed to facilitate the use of different solvers in different part of the computational domain. However, the complex hybrid gridding paradigm poses challenges to rendering calculations for visualizing the data. this paper describes a volume visualization system for time-varying adaptive moving-body CFD datasets, where the grid system consists of unstructured grids near the body surface, coupled with Structured Adaptive Mesh Refinement (SAMR) grid in the off-body domain. We present two approaches to the hybrid-grid volume ray casting: a KD-tree based single-pass algorithm, and a multi-pass algorithm using the depth peeling technique. the system has a three-level memory hierarchy: GPU memory, main memory, and a solid state drive (SSD). through data caching and prefetching within the memory hierarchy, the latency of time-step swapping can be hidden. Experimental results show that our system allows interactive volume exploration on single-GPU commodity PCs.

关键词： Rendering (computer graphics) Graphics processing units Casting data visualization Legged locomotion Prefetching Runtime

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4th Joint Eurographics - ieee TCVG symposium on visualization, VisSym 2002

4th Joint Eurographics - IEEE TCVG Symposium on Visualizatio...

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4th Joint Eurographics - ieee TCVG symposium on visualization, VisSym 2002

ISBN: (纸本)158113536X

the proceedings contain 31 papers. the topics discussed include: parallel and out-of-core view-dependent isocontour visualization using random data distribution;statistical computation of salient ISO-VALUES;interactive visualization and steering of CFD simulations;adding a scalar value to texture-based vector field representations by local contrast analysis;AUFLIC: an accelerated algorithm for unsteady flow line integral convolution;octreemizer: a hierarchical approach for interactive roaming through very large volumes;comparison of morphological pyramids for multiresolution MIP volume rendering;interactive previewing for transfer function specification in volume rendering;and cell-based first-hit ray casting.

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STREAMIT: Dynamic visualization and Interactive Exploration of Text Streams

STREAMIT: Dynamic Visualization and Interactive Exploration ...

引用

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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Cache-aware sampling strategies for texture-based ray casting on GPU

Cache-aware sampling strategies for texture-based ray castin...

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ieee symposium on large data analysis and visualization (ldav)

作者： Junpeng Wang Fei Yang Yong Cao Virginia Polytechnic Institute and State University Blacksburg VA US Chinese Academy of Sciences

As a major component of volume rendering, the ray casting algorithm is memory-intensive. However, most existing texture-based volume rendering methods blindly map computational resources to texture memory and result in an incoherent access pattern, causing low cache hit rates in certain cases. the distance between samples taken by threads of the same scheduling unit (e.g. a warp of 32 threads in CUDA), of the GPU is a major factor that affects the texture cache hit rate. Based on this fact, we present a new sampling strategy, i.e. warp marching, which displays a novel computation-to-core mapping. In addition, a double buffer approach is introduced and special GPU operations are leveraged to improve the efficiency of parallel executions. To keep a roughly constant rendering performance when rotating the volume, we change our warp marching algorithm, so that samples can be taken along different directions of the volume. As a result, varying texture cache hit rates in different viewing directions are averaged out. through a series of micro-benchmarking and real-life data experiments, we rigorously analyze our sampling strategies, and demonstrate significant performance enhancements over existing sampling methods.

关键词： Instruction sets Graphics processing units Rendering (computer graphics) Benchmark testing Casting Algorithm design and analysis Message systems

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