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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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ieee symposium on large data Analysis and visualization 2016, LDAV 2016 - Proceedings

IEEE Symposium on Large Data Analysis and Visualization 2016...

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6th ieee symposium on large-Scale data Analysis and visualization, LDAV 2016

ISBN: (纸本)9781509056590

The proceedings contain 18 papers. The topics discussed include: embedded domain-specific language and runtime system for progressive spatiotemporal data analysis and visualization;SeekAView: an intelligent dimensionality reduction strategy for navigating high-dim data spaces;quantitative exploration of large medieval manuscripts data for the codicological research;parallel distributed, GPU-accelerated, advanced lighting calculations for large-scale volume visualization;interactive visual exploration of a trillion particles;in situ generated probability distribution functions for interactive post hoc visualization and analysis;parallel peak pruning for scalable SMP contour tree computation;topology-aware image compositing using NVLink;scalable rendering of large SPH simulations using an RK-enhanced interpolation scheme on constrained datasets;segmented time series visualization tool for additive manufacturing;a lightweight H.264-based hardware accelerated image compression library;statistical projections for multi-dimensional visual data exploration;formal evaluation strategies for feature tracking;and correlating sub-phenomena in performance data in the frequency domain.

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From cluster to wall with VTK 03

From cluster to wall with VTK

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ieee symposium on parallel and large-data visualization and graphics

作者： Moreland, K Thompson, D Sandia Natl Labs Livermore CA 94550 USA

ISBN: (纸本)078038122X

This paper describes a new set of parallel rendering components for VTK, the visualization Toolkit. The parallel rendering units allow for the rendering of vast quantities of geometry with a focus on cluster computers. Furthermore, the geometry may be displayed on tiled displays at full or reduced resolution. We demonstrate an interactive VTK application processing an isosurface consisting of nearly half a billion triangles and displaying on a power wall with a total resolution of 63 million pixels. We also demonstrate an interactive VTK application displaying the same geometry on a desktop connected to the cluster via a TCP/IP socket over 100BASE-T Ethernet.

关键词： parallel rendering desktop delivery tile display PC cluster Chromium VTK

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Proper orthogonal decomposition based parallel compression for visualizing big data on the K computer

Proper orthogonal decomposition based parallel compression f...

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

作者： Bi, Chongke Ono, Kenji Ma, Kwan-Liu Wu, Haiyuan Imamura, Toshiyuki RIKEN Japan University of California Davis United States Wakayama University Japan

ISBN: (纸本)9781479916597

The development of supercomputers has greatly help us to carry on large-scale computing for dealing with various problems through simulating and analyzing them. visualization is an indispensable tool to understand the properties of the data from supercomputers. Especially, interactive visualization can help us to analyze data from various viewpoints and even to find out some local small but important features. However, it is still difficult to interactively visualize such kind of big data directly due to the slow file I/O problem and the limitation of memory size. For resolving these problems, we proposed a parallel compression method to reduce the data size with low computational cost. Furthermore, the fast linear decompression process is another merit for interactive visualization. Our method uses proper orthogonal decomposition (POD) to compress data because it can effectively extract important features from the data and the resulting compressed data can also be linearly decompressed. Our implementation achieves high parallel efficiency with a binary load-distributed approach, which is similar to the binary-swap image composition used in parallel volume rendering [2]. This approach allows us to effectively utilize all the processing nodes and reduce the interprocessor communication cost throughout the parallel compression calculations. Our test results on the K computer demonstrate superior performance of our design and implementation. © 2013 ieee.

关键词： Supercomputers

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A Prototype for Pipeline-Composable Task-Based visualization Algorithms 12

A Prototype for Pipeline-Composable Task-Based Visualization...

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12th ieee symposium on large-Scale data Analysis and visualization (LDAV)

作者： Petersen, Marvin Werner, Kilian Schnorr, Andrea Kuhlen, Torsten Wolfgang Garth, Christoph Rhein Westfal TH Aachen Aachen Germany Tech Univ Kaiserslautern Kaiserslautern Germany

ISBN: (数字)9781665491563

ISBN: (纸本)9781665491563

For next generation platforms, the paradigm of task-based parallelism has the potential to overcome some of the accompanying challenges. This paradigm has already been applied by the visualization community to specific algorithms and problems. However, one advantage of the task-based paradigm-the interleaving of workshould lead to better utilization of resources and ultimately lower execution times if the paradigm is applied to whole pipelines. In order to investigate this potential, we build a prototype framework for composable task-based parallel visualization algorithms. With this we explore the combination of a strictly task-based approach with the addition of a pipeline layer for visualization algorithms. This additional layer eases the composition of larger task-based parallel visualization applications without the need to explicitly define the exact connection in a task graph between algorithms. In this manner, task-based visualization algorithms can be designed towards a common interface, be easily combined, and still benefit from the advantages of the task-based paradigm across algorithm boundaries, such as latency hiding. We explore the design implications of this combination and show initial results of the scalability and the impact of task interleaving on the runtime of exemplary pipelines.

关键词： task-based parallelism pipeline composition scientific visualization distributed parallel HPX

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visualization and analysis of large data collections: a case study applied to confocal microscopy data

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ieee TRANSACTIONS ON visualization AND COMPUTER graphics 2006年第5期12卷 1251-1258页

作者： de Leeuw, Wim Verschure, Pernette J. van Liere, Robert CWI Ctr Math & Comp Sci NL-1009 AB Amsterdam Netherlands

In this paper we propose an approach in which interactive visualization and analysis are combined with batch tools for the processing of large data collections. large and heterogeneous data collections are difficult to analyze and pose specific problems to interactive visualization. Application of the traditional interactive processing and visualization approaches as well as batch processing encounter considerable drawbacks for such large and heterogeneous data collections due to the amount and type of data. Computing resources are not sufficient for interactive exploration of the data and automated analysis has the disadvantage that the user has only limited control and feedback on the analysis process. In our approach, an analysis procedure with features and attributes of interest for the analysis is defined interactively. This procedure is used for off-line processing of large collections of data sets. The results of the batch process along with "visual summaries" are used for further analysis. visualization is not only used for the presentation of the result, but also as a tool to monitor the validity and quality of the operations performed during the batch process. Operations such as feature extraction and attribute calculation of the collected data sets are validated by visual inspection. This approach is illustrated by an extensive case study, in which a collection of confocal microscopy data sets is analyzed.

关键词： biomedical visualization features in volume data sets large data set visualization

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ieee Pacific visualization symposium

IEEE Pacific Visualization Symposium

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11th ieee Pacific visualization symposium, PacificVis 2018

ISBN: (纸本)9781538614242

The proceedings contain 29 papers. The topics discussed include: optimal algorithms for compact linear layouts;development of an integrated visualization system for phenotypic character networks;image and distribution based volume rendering for large data sets;topologically controlled lossy compression;information guided data sampling and recovery using bitmap indexing;in situ prediction driven feature analysis in jet engine simulations;access pattern learning with long short-term memory for parallel particle tracing;dynamic data repartitioning for load-balanced parallel particle tracing;uncertainty visualization for secondary structures of proteins;and modeling and visualization of uncertainty-aware geometry using multi-variate normal distributions.

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Visualizing Hierarchical Performance Profiles of parallel Codes Using CallFlow

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ieee TRANSACTIONS ON visualization AND COMPUTER graphics 2021年第4期27卷 2455-2468页

作者： Huu Tan Nguyen Bhatele, Abhinav Jain, Nikhil Kesavan, Suraj P. Bhatia, Harsh Gamblin, Todd Ma, Kwan-Liu Bremer, Peer-Timo Univ Calif Davis Dept Comp Sci Davis CA 95616 USA Univ Maryland Dept Comp Sci College Pk MD 20742 USA NVIDIA Inc Santa Clara CA 95050 USA Lawrence Livermore Natl Lab Ctr Appl Sci Comp Livermore CA 94551 USA

Calling context trees (CCTs) couple performance metrics with call paths, helping understand the execution and performance of parallel programs. To identify performance bottlenecks, programmers and performance analysts visually explore CCTs to form and validate hypotheses regarding degraded performance. However, due to the complexity of parallel programs, existing visual representations do not scale to applications running on a large number of processors. We present CallFlow, an interactive visual analysis tool that provides a high-level overview of CCTs together with semantic refinement operations to progressively explore CCTs. Using a flow-based metaphor, we visualize a CCT by treating execution time as a resource spent during the call chain, and demonstrate the effectiveness of our design with case studies on large-scale, production simulation codes.

关键词： data visualization Tools visualization Layout Vegetation Histograms Measurement Performance analysis software visualization visual analytics hierarchical data coordinated and multiple views

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Evaluation of Pointing Ray Techniques for Distant Object Referencing in Model-Free Outdoor Collaborative Augmented Reality

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ieee TRANSACTIONS ON visualization AND COMPUTER graphics 2022年第11期28卷 3896-3906页

作者： Li, Yuan Tahmid, Ibrahim A. Lu, Feiyu Bowman, Doug A. Virginia Tech Ctr Human Comp Interact Blacksburg VA 24061 USA Virginia Tech Dept Comp Sci Blacksburg VA 24061 USA

Referencing objects of interest is a common requirement in many collaborative tasks. Nonetheless, accurate object referencing at a distance can be challenging due to the reduced visibility of the objects or the collaborator and limited communication medium. Augmented Reality (AR) may help address the issues by providing virtual pointing rays to the target of common interest. However, such pointing ray techniques can face critical limitations in large outdoor spaces, especially when the environment model is unavailable. In this work, we evaluated two pointing ray techniques for distant object referencing in model-free AR from the literature: the Double Ray technique enhancing visual matching between rays and targets, and the parallel Bars technique providing artificial orientation cues. Our experiment in outdoor AR involving participants as pointers and observers partially replicated results from a previous study that only evaluated observers in simulated AR. We found that while the effectiveness of the Double Ray technique is reduced with the additional workload for the pointer and human pointing errors, it is still beneficial for distant object referencing.

关键词： Augmented Reality Collaboration Ray visualization Model-Free Outdoor

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Making a Case for Green High-Performance visualization via Embedded graphics Processors 32

Making a Case for Green High-Performance Visualization via E...

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32nd ieee International parallel and Distributed Processing symposium (IPDPS)

作者： Adhinarayanan, Vignesh Dutta, Bishwajit Feng, Wu-chun Virginia Tech Dept Comp Sci Blacksburg VA 24061 USA Virginia Tech Dept Elect & Comp Engn Blacksburg VA 24061 USA Virginia Tech Dept Comp Sci & Elect & Comp Engn Blacksburg VA 24061 USA

ISBN: (纸本)9781538655559

This paper makes a case for using low-power embedded GPUs for the purpose of executing high-performance scientific visualization tasks. We compare the greenness (i.e., power, energy, and energy-delay product -> EDP) of an embedded GPU with a CPU for commonly encountered visualization tasks using two real-world applications: (1) Modeling for Prediction Across Scale Ocean (MPAS-O) and (2) Particular Ensembles (PE). Our preliminary results show that the low-power embedded GPU is capable of handling complex visualization tasks while consuming less than 50% of the energy consumed by a CPU server. In addition, we find that the embedded GPU outperforms the CPU with dynamic voltage-frequency scaling (DVFS) enabled in a majority of the cases.

关键词： graphics processing units data visualization Task analysis Central Processing Unit Pipelines"

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