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检索条件"任意字段=IEEE Symposium on Parallel and Large-Data Visualization and Graphics"

共 1197 条记录，以下是231-240 订阅

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Interactive visualization of High-Dimensional Petascale Ocean data 7

Interactive Visualization of High-Dimensional Petascale Ocea...

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ieee 7th symposium on large data Analysis and visualization (LDAV)

作者： Ellsworth, David A. Henze, Christopher E. Nelson, Bron C. NASA CSRA Ames Res Ctr Washington DC 20546 USA NASA Ames Res Ctr Washington DC USA

ISBN: (纸本)9781538606179

We describe an application for interactive visualization of 5 petabytes of time-varying multivariate data from a high-resolution global ocean circulation model. The input data are 10311 hourly (ocean time) time steps of various 2D and 3D fields from a 22-billion point 1/48-degree "lat-lon cap" configuration of the MIT General Circulation Model (MITgcm). We map the global horizontal model domain onto our 128-screen (8x16) tiled display wall to produce a canonical tiling with approximately one MITgcm grid point per display pixel, and using this tiling we encode the entire time series for multiple native and computed scalar quantities at a collection of ocean depths. We reduce disk bandwidth requirements by converting the model's floating point data to 16-bit fixed point values, and compressing those values with a lossless video encoder, which together allow synchronized playback at 24 time steps per second across all 128 displays. The application allows dynamic assignment of any two encoded tiles to any display, and has multiple interfaces for quickly specifying various orderly arrangements of tiles. All subsequent rendering is done on the fly, with run time control of colormaps, transfer functions, histogram equalization, and labeling. The two data streams on each screen can be rendered independently and combined in various ways, including blending, differencing, horizontal/vertical wipes, and checkerboarding. The two data streams on any screen can optionally be displayed as a scatterplot in their joint attribute space. All scatterplots and map-view plots from the same x/y location and depth are linked so they all show the current brushable selection. Ocean scientists have used the system, and have found previously unidentified features in the data.

关键词： J.2 [Physical Sciences and Engineering]: Earth and atmospheric sciences I.6.6 [Simulation and Modeling]: Simulation Output Analysis I.3.8 [Computer graphics]: Applications

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Scalable Architecture for Anomaly Detection and visualization in Power Generating Assets 31

Scalable Architecture for Anomaly Detection and Visualizatio...

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31st ieee International parallel and Distributed Processing symposium Workshops (IPDPS)

作者： Jain, Paras Tailor, Chirag Ford, Sam Ding, Liexiao (Richard) Phillips, Michael Liu, Fang (Cherry) Gebraeel, Nagi Chau, Duen Horng (Polo) Georgia Inst Technol Coll Comp Atlanta GA 30332 USA Georgia Inst Technol H Milton Stewart Sch Ind & Syst Engn Atlanta GA 30332 USA Georgia Inst Technol Partnership Adv Comp Environm Atlanta GA 30332 USA

ISBN: (纸本)9780769561493

Power-generating assets (e.g., jet engines, gas turbines) are often instrumented with tens to hundreds of sensors for monitoring physical and performance degradation. Anomaly detection algorithms highlight deviations from predetermined benchmarks with the goal of detecting incipient faults. We are developing an integrated system to address three key challenges within analyzing sensor data from power-generating assets: (1) difficulty in ingesting and analyzing data from large numbers of machines;(2) prevalence of false alarms generated by anomaly detection algorithms resulting in unnecessary downtime and maintenance;and (3) lack of an integrated visualization that helps users understand and explore the flagged anomalies and relevant sensor context in the energy domain. We present preliminary results and our key findings in addressing these challenges. Our system's scalable event ingestion framework, based on OpenTSDB, ingests nearly 400,000 sensor data samples per seconds using a 30 machine cluster. To reduce false alarm rates, we leverage the False Discovery Rate (FDR) algorithm which significantly reduces the number of false alarms. Our visualization tool presents the anomalies and associated content flagged by the FDR algorithm to inform users and practitioners in their decision making process. We believe our integrated platform will help reduce maintenance costs significantly while increasing asset lifespan. We are working to extend our system on multiple fronts, such as scaling to more data and more compute nodes (70 in total).

关键词： False discovery rate visualization OpenTSDB power asset energy sensor

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GPU parallel Implementation of Gas Plume Detection in Hyperspectral Video Sequences

GPU Parallel Implementation of Gas Plume Detection in Hypers...

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ieee International symposium on Geoscience and Remote Sensing (IGARSS)

作者： Huimin Yu Zebin Wu Jie Wei Yang Xu Jocelyn Chanussot Andrea L. Bertozzi Linlin Shi Zhihui Wei School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China CNRS GIPSA-lab Grenoble France Department of Mathematics University of California Los Angeles(UCLA) USA

Gas plume detection is a challenging task in the field of remote sensing. Due to sensor development, it is now possible to detect and track chemical gas plumes with hyperspectral video sequences (HVS). For the purpose of high detection accuracy, it is important to explore spectral characteristic, and take full advantages of spatial continuity and temporal consistency in HVS. However, the high computational complexity and the large amount of data limit its application in time-critical scenarios. In this paper, we propose a GPU parallel implementation of gas plume detection in HVS, which properly exploits shared memory and intrinsic concurrency of the CUDA blocks, as well as parallel workload assignment and resource allocation. The experimental results demonstrate the proposed GPU parallel method has a considerable acceleration factor while retaining the same detection accuracy compared with the serial and multicore version.

关键词： graphics processing units TV Sparse matrices Hyperspectral imaging Instruction sets Computational modeling

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A Three-Level parallel Algorithm For MrBayes 3.2 15

A Three-Level Parallel Algorithm For MrBayes 3.2

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15th ieee International symposium on parallel and Distributed Processing with Applications (ISPA) / 16th ieee International Conference on Ubiquitous Computing and Communications (IUCC)

作者： Zhao, Mingjie Ren, Qiang Wang, Yilin Deng, Ruikang Ren, Mingming Wang, Gang Liu, Xiaoguang Nankai Univ Nankai Baidu Joint Lab Tianjin Peoples R China

ISBN: (纸本)9781538637906

MrBayes is a popular bioinformatics software that is widely used in phylogenetic analysis. The core algorithm of Mrbayes is Metropolis Coupled Markov Chain Monte Carlo (MC3). However, when dealing with large data sets, MC3 algorithm is too slow to meet researcher's requirements. Although several parallelizations have been proposed for MrBayes, such as MPI (Message Passing Interface) based MrBayes, GPU (graphics Processing Unit) based MrBayes, there is still no efficient parallel algorithm to fully utilize computing power of modern CPU and computer architecture. This paper (a) presents a new three-level hybrid parallel algorithm, include data-level parallelism (DLP), thread-level parallelism (TLP), and process-level parallelism (PLP), which can be used on most modern multi-core computers;(b) compares the performance of different combinations of parallel strategies on real-world protein data sets. The experimental results show that, this hybrid parallel algorithm does convert more computing powers into higher speedup. Furthermore, the proposed algorithm's speedup is near the speedup on one GPU at the same data sets. This algorithm is fit for practical use in phylogenetic inferences.

关键词： MrBayes SIMD hybrid parallel computing

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Comparison of Road Accident Black Spot Searching Methods

Comparison of Road Accident Black Spot Searching Methods

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International symposium on Computational Intelligence and Informatics

作者： Sándor Szénási Imre Felde Gábor Kertész László Nádai John von Neumann Faculty of Informatics Óbuda University Budapest Hungary

The localisation of road accident hotspots (areas of the public road network, where the number of accidents is higher than expected based on the average values) is one of the main tasks of road safety experts. Analysing these locations can help to avoid further traffic accidents and personal injuries (most of all, fatal accidents). There are several already known methods in literature for this purpose and this paper contains a comparison between the most frequently used ones: sliding-window method (using constant and variable window size), 2D sliding-window method (using constant and variable window width and height), Density-based spatial clustering of applications with noise (DBSCAN) based data-mining method (which is also a spatial method). This paper takes into account the latest technical developments in the field (available high computational capability, accuracy given by the Global Positioning System, usage of graphics accelerators and further parallel devices, etc.), The evaluation contains both the qualitative and quantitative aspects; considering accuracy, processing speed, parameter sensibility, etc.

关键词： Roads Global Positioning System Microsoft Windows Road accidents Informatics data visualization

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Achieving portable performance for wavelet compression using data parallel primitives

Achieving portable performance for wavelet compression using...

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17th Eurographics symposium on parallel graphics and visualization, EGPGV 2017

作者： Li, Shaomeng Marsaglia, Nicole Chen, Vincent Sewell, Christopher Clyne, John Childs, Hank University of Oregon OR United States National Center for Atmospheric Research United States Los Alamos National Laboratory United States

ISBN: (纸本)9783038680345

We consider the problem of wavelet compression in the context of portable performance over multiple architectures. We contribute a new implementation of the wavelet transform algorithm that uses data parallel primitives from the VTK-m library. Because of the data parallel primitives approach, our algorithm is hardware-agnostic and yet can run on many-core architectures. We also study the efficacy of this implementation over multiple architectures against hardware-specific comparators. Results show that our performance is portable, scales well, and is comparable to native implementations. Finally, we argue that compression times for large data sets are likely fast enough to fit within in situ constraints, adding to the evidence that wavelet transformation could be an effective in situ compression operator. © 2017 The Author(s).

关键词： Metadata

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Performance Evaluation of Priority Queues for Fine-Grained parallel Tasks on GPUs 25

Performance Evaluation of Priority Queues for Fine-Grained P...

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25th ieee International symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS)

作者： Baudis, Nikolai Jacob, Florian Andelfinger, Philipp Karlsruhe Inst Technol Inst Telemat Karlsruhe Germany

ISBN: (纸本)9781538627631

graphics processing units (GPUs) are increasingly applied to accelerate tasks such as graph problems and discrete-event simulation that are characterized by irregularity, i.e., a strong dependence of the control flow and memory accesses on the input. The core data structure in many of these irregular tasks are priority queues that guide the progress of the computations and which can easily become the bottleneck of an application. To our knowledge, currently no systematic comparison of priority queue implementations on GPUs exists in the literature. We close this gap by a performance evaluation of GPU-based priority queue implementations for two applications: discrete-event simulation and parallel A* path searches on grids. We focus on scenarios requiring large numbers of priority queues holding up to a few thousand items each. We present performance measurements covering linear queue designs, implicit binary heaps, splay trees, and a GPU-specific proposal from the literature. The measurement results show that up to about 500 items per queue, circular buffers frequently outperform tree-based queues for the considered applications, particularly under a simple parallelization of individual item enqueue operations. We analyze profiling metrics to explore classical queue designs in light of the importance of high hardware utilization as well as homogeneous computations and memory accesses across GPU threads.

关键词： graphics processing units Computational modeling Instruction sets data structures Synchronization Analytical models

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EuroVis 2017 - Eurographics / ieee VGTC Conference on visualization 2017, Posters

EuroVis 2017 - Eurographics / IEEE VGTC Conference on Visual...

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19th Eurographics / ieee VGTC Conference on visualization, EuroVis 2017

ISBN: (纸本)9783038680444

The proceedings contain 35 papers. The topics discussed include: structuring and visualizing knowledge in soil science;towards an adaptive framework for real-time visualization of streaming big data;Diggersdiaries: using text analysis to support exploration and reading in a large document collection;memory efficient parallel ray-casting algorithm for unstructured grid volume rendering;evaluating cognitive load: force-directed layout vs. chord layout;visualization of the forever 27 club;visualization taxonomy based on the specification of user's goal and data dimensions;and an interactive visual representation to explore association with hierarchical social circles.

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A High-Dimensional data Quality Metric using Pareto Optimality

A High-Dimensional Data Quality Metric using Pareto Optimali...

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19th Eurographics / ieee VGTC Conference on visualization, EuroVis 2017

作者： Post, Tobias Wischgoll, Thomas Hamann, Bernd Hagen, Hans Computer Graphics and HCI Group University of Kaiserslautern Germany Advanced Visual Data Analysis Group Wright State University United States Department of Computer Science University of California Davis United States

ISBN: (纸本)9783038680444

The representation of data quality within established high-dimensional data visualization techniques such as scatterplots and parallel coordinates is still an open problem. This work offers a scale-invariant measure based on Pareto optimality that is able to indicate the quality of data points with respect to the Pareto front. In cases where datasets contain noise or parameters that cannot easily be expressed or evaluated mathematically, the presented measure provides a visual encoding of the environment of a Pareto front to enable an enhanced visual inspection. © 2017 The Author(s) Eurographics Proceedings © 2017 The Eurographics Association.

关键词： data visualization

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An application-aware data replacement policy for interactive large-scale scientific visualization

An application-aware data replacement policy for interactive...

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ieee International symposium on parallel and Distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Lina Yu Hongfeng Yu Hong Jiang Jun Wang University of Nebraska-Lincoln Lincoln Nebraska USA University of Texas at Arlington Arlington Texas USA University of Iowa Iowa City IA USA

The unprecedented amounts of data generated from large scientific simulations impose a grand challenge in data analytics, and I/O simply becomes a major performance bottleneck. To address this challenge, we present an application-aware I/O optimization technique in support of interactive large-scale scientific visualization. We partition a scientific data into blocks, and carefully place data blocks in a memory hierarchy according to a characterization of data access patterns of user visualization operations. We conduct an empirical study to explore the parameter space to derive optimal solutions. We use real-world large-scale simulation datasets to demonstrate the effectiveness of our approach.

关键词： data visualization Cameras data models Prefetching Computational modeling Rendering (computer graphics) Octrees

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