检索结果-内蒙古大学图书馆

ieee 5th symposium on large data analysis and visualization (LDAV)

作者： Li, Shaomeng Gruchalla, Kenny Potter, Kristin Clyne, John Childs, Hank Univ Oregon Eugene OR 97403 USA Natl Renewable Energy Lab Golden CO USA Natl Ctr Atmospher Res Boulder CO 80307 USA Lawrence Berkeley Natl Lab Berkeley CA USA

ISBN: (纸本)9781467385176

I/O is increasingly becoming a significant constraint for simulation codes and visualization tools on modern supercomputers. data compression is an attractive workaround, and, in particular, wavelets provide a promising solution. However, wavelets can be applied in multiple configurations, and the variations in configuration impact accuracy, storage cost, and execution time. While the variation in these factors over wavelet configurations have been explored in image processing, they are not well understood for visualization and analysis of scientific data. To illuminate this issue, we evaluate multiple wavelet configurations on turbulent-flow data. Our approach is to repeat established analysis routines on uncompressed and lossy-compressed versions of a data set, and then quantitatively compare their outcomes. Our findings show that accuracy varies greatly based on wavelet configuration, while storage cost and execution time vary less. Overall, our study provides new insights for simulation analysts and visualization experts, who need to make tradeoffs between accuracy, storage cost, and execution time.

关键词： execution time wavelets flow datas visualization configurations dataset IO tradeoffs Image processing

来源：评论

学校读者我要写书评

暂无评论

PxStream: Remote visualization for Distributed Rendering Frameworks 9

PxStream: Remote Visualization for Distributed Rendering Fra...

引用

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

作者： Marrinan, Thomas Rizzi, Silvio Insley, Joseph A. Long, Lance Renambot, Luc Papka, Michael E. Univ St Thomas Houston TX 77006 USA Argonne Natl Lab Argonne IL 60439 USA Northern Illinois Univ De Kalb IL 60115 USA Univ Illinois Chicago IL USA

ISBN: (纸本)9781728126050

When dealing with extremely large data sets or computationally expensive rendering pipelines, local workstations may not he able to render the full data set or maintain interactive frame rates. In these cases, high-performance graphics clusters can he leveraged for distributed rendering. However, this traditionally has removed real-time feedback from the visualization system. In order to harness the power of distributed rendering and the real-time nature of local rendering, we developed PxStream - a streaming framework to transfer dynamically rendered images from high-performance graphics clusters to remote machines in real-time. PxStream clients can range from a standard computer with single monitor to a cluster-driven tiled display wall. Additionally, the PxStream server supports multiple concurrent endpoints to allow collaborators at different physical locations to simultaneously view the image stream. Initial tests demonstrate that PxStream can simultaneously stream 66 megapixel images to two locations at nearly 50 frames per second.

关键词： Streaming in situ big data analysis ultra-high-resolution visualization high-performance computing

来源：评论

学校读者我要写书评

暂无评论

Adaptive Encoder Settings for Interactive Remote Visualisation on High-Resolution Displays 8

Adaptive Encoder Settings for Interactive Remote Visualisati...

引用

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

作者： Friess, Florian Landwehr, Mathias Bruder, Valentin Frey, Steffen Ertl, Thomas Univ Stuttgart Stuttgart Germany

ISBN: (纸本)9781538668733

We present an approach that dynamically adapts encoder settings for image tiles to yield the best possible quality for a given bandwidth. This reduces the overall size of the image while preserving details. Our application determines the encoding settings in two steps. In the first step, we predict the quality and size of the tiles for different encoding settings using a convolutional neural network. In the second step, we assign the optimal encoder setting to each tile, so that the overall size of the image is lower than a predetermined threshold. Commonly, for tiles that contain complicated structures, a high quality setting is used in order to prevent major information loss, while quality settings are lowered for others to keep the size below the threshold. We demonstrate that we can reduce the overall size of the image while preserving the details in areas of interest using the example of both particle and volume visualisation applications.

关键词： Human-centered computing visualization visualization application domains Scientific visualization Machine learning Machine learning approaches Neural networks

来源：评论

学校读者我要写书评

暂无评论

A Comprehensive Informative Metric for Summarizing HPC System Status 8

A Comprehensive Informative Metric for Summarizing HPC Syste...

引用

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

作者： Hui, Yawei Park, Byung Hoon Engelmann, Christian Oak Ridge Natl Lab Comp Sci & Math Div Oak Ridge TN 37830 USA

ISBN: (纸本)9781538668733

It remains a major challenge to effectively summarize and visualize in a comprehensive form the status of a complex computer system, such as the Titan supercomputer at the Oak Ridge Leadership Computing Facility (OLCF). In the ongoing research highlighted in this poster, we present system information entropy (SIE), a newly developed system metric that leverages the powers of traditional machine learning techniques and information theory. By compressing the multi-variant multi-dimensional event information recorded during the operation of the targeted system into a single time series of SIE, we demonstrate that the historical system status can be sensitively summarized in form of SIE and visualized concisely and comprehensively.

关键词： Human-centered computing Visual analytics General and reference Metrics Mathematics of computing Time series analysis

来源：评论

学校读者我要写书评

暂无评论

A Proposed Framework for Interactive Virtual Reality In Situ visualization of Parallel Numerical Simulations 9

A Proposed Framework for Interactive Virtual Reality In Situ...

引用

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

作者： Gupta, Aryaman Guenther, Ulrik Incardona, Pietro Aydin, Ata Deniz Dachselt, Raimund Gumhold, Stefan Sbalzarini, Ivo F. Tech Univ Dresden Dresden Germany CSBD Dresden Germany MPI CBG Dresden Germany Tech Univ Dresden Interact Media Lab Dresden Cluster Excellence Phys Life Dresden Germany Tech Univ Dresden Cluster Excellence Phys Life Dresden Germany Tech Univ Dresden CSBD Dresden Germany MPI CBG Cluster Excellence Phys Life Dresden Germany

ISBN: (纸本)9781728126050

As computer simulations progress to increasingly complex, nonlinear, and three-dimensional systems and phenomena, intuitive and immediate visualization of their results is becoming crucial. While Virtual Reality (VR) and Natural User Interfaces (NUIs) have been shown to improve understanding of complex 3D data, their application to live in situ visualization and computational steering is hampered by performance requirements. Here, we present the design of a software framework for interactive VR in situ visualization of parallel numerical simulations, as well as a working prototype implementation. Our design is targeted towards meeting the performance requirements for VR, and our work is packaged in a framework that allows for easy instrumentation of simulations. Our preliminary results inform about the technical feasibility of the architecture, as well as the challenges that remain.

关键词： Computing methodologies Massively parallel and high-performance simulations Human-centered computing Virtual reality

来源：评论

学校读者我要写书评

暂无评论

SpRay: Speculative Ray Scheduling for large data visualization 8

SpRay: Speculative Ray Scheduling for Large Data Visualizati...

引用

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

作者： Park, Hyungman Fussell, Donald Navratil, Paul Univ Texas Austin Elect & Comp Engn Austin TX 78712 USA Univ Texas Austin Comp Sci Austin TX 78712 USA Univ Texas Austin Texas Adv Comp Ctr Austin TX 78712 USA

ISBN: (纸本)9781538668733

With modern supercomputers offering petascale compute capability, scientific simulations are now producing terascale data. For comprehensive understanding of such large data, ray tracing is becoming increasingly important for 3D-rendering in visualization due to its inherent ability to convey physically realistic visual information to the user. Implementing efficient parallel ray tracing systems on supercomputers while maximizing locality and parallelism is challenging because of the overhead incurred by ray communication across the cluster of compute nodes and data loading from storage. To address the problem, reordering rendering computations by means of ray batching and scheduling has been proposed to temporarily avoid inherent dependencies in the rendering computations and amortize the cost of expensive data moving operations over ray batches. In this paper, we introduce a novel speculative ray scheduling method that builds upon this insight but radically changes the approach to resolving dependencies by allowing redundant computations to a certain extent. To evaluate the method, we measure the performance of different implementations for both out-of-core and in situ rendering setups. Results show that compared to a well-known scheduling method, our approach on ambient occlusion and path tracing achieves up to 2.3x speedup for the scenes comprising up to billions of triangles extracted from terascale scientific data.

关键词： Human-Centered Computing visualization visualization Techniques Computing Methodologies Computer Graphics Rendering Ray Tracing

来源：评论

学校读者我要写书评

暂无评论

Low-Cost Post Hoc Reconstruction of HPC Simulations at Full Resolution 13

Low-Cost Post Hoc Reconstruction of HPC Simulations at Full ...

引用

13th ieee symposium on large data analysis and visualization (LDAV)

作者： Yousef, Ayman Z. Draeger, Erik W. Randles, Amanda Duke Univ Durham NC 27708 USA Lawrence Livermore Natl Lab Livermore CA 94550 USA

ISBN: (纸本)9798350330182

High performance computing has played a pivotal and ongoing role in the field of computational fluid dynamics, enabling the simulation of increasingly larger-scale models. However, this rapid growth in model and simulation size has outpaced the capabilities of input/output (I/O) operations. Consequently, the conventional approach of saving and outputting data to persistent storage for analysis has become increasingly challenging, limiting the benefits of these advanced models. To address this challenge, we present a method for effectively handling massive-scale simulation data, ensuring its persistence at full spatial and temporal resolution for flexible post hoc analysis. We employ an in situ approach that captures interprocess communicated data, compressing cached data to a fraction of the overall simulation domain. We successfully reconstruct subdomains at full spatial and temporal resolution during post-processing through communication-free rerun using the cached halos. We detail the storage requirements of the new approach and demonstrate the substantial reductions in computational resources required to precisely recapitulate data within a local region of interest.

关键词： data analysis in situ

来源：评论

学校读者我要写书评

暂无评论

Case study: visualization for decision tree analysis in data mining

Case study: Visualization for decision tree analysis in data...

引用

7th ieee symposium on Information visualization (INFOVIS 2001)

作者： Barlow, T Neville, P

ISBN: (纸本)0769513425

Decision trees are one of the most popular methods of data mining. Decision trees partition large amounts of data into smaller segments by applying a series of rules. Creating and evaluating decision trees benefits greatly from visualization of the trees and diagnostic measures of their effectiveness. This paper describes an application, EMTree Results Viewer, that supports decision tree analysis through the visualization of model results and diagnosis. The functionality of the application and the visualization techniques are revealed through an example of churn analysis in the telecommunications industry.

关键词： data structures

来源：评论

学校读者我要写书评

暂无评论

In Situ Exploration of large Dynamic Networks

引用

ieee TRANSACTIONS ON visualization AND COMPUTER GRAPHICS 2011年第12期17卷 2334-2343页

作者： Hadlak, Steffen Schulz, Hans-Joerg Schumann, Heidrun Univ Rostock D-2500 Rostock 1 Germany Graz Univ Technol A-8010 Graz Austria

The analysis of large dynamic networks poses a challenge in many fields, ranging from large bot-nets to social networks. As dynamic networks exhibit different characteristics, e. g., being of sparse or dense structure, or having a continuous or discrete time line, a variety of visualization techniques have been specifically designed to handle these different aspects of network structure and time. This wide range of existing techniques is well justified, as rarely a single visualization is suitable to cover the entire visual analysis. Instead, visual representations are often switched in the course of the exploration of dynamic graphs as the focus of analysis shifts between the temporal and the structural aspects of the data. To support such a switching in a seamless and intuitive manner, we introduce the concept of in situ visualization - a novel strategy that tightly integrates existing visualization techniques for dynamic networks. It does so by allowing the user to interactively select in a base visualization a region for which a different visualization technique is then applied and embedded in the selection made. This permits to change the way a locally selected group of data items, such as nodes or time points, are shown - right in the place where they are positioned, thus supporting the user's overall mental map. Using this approach, a user can switch seamlessly between different visual representations to adapt a region of a base visualization to the specifics of the data within it or to the current analysis focus. This paper presents and discusses the in situ visualization strategy and its implications for dynamic graph visualization. Furthermore, it illustrates its usefulness by employing it for the visual exploration of dynamic networks from two different fields: model versioning and wireless mesh networks.

关键词： Dynamic graph data multiform visualization multi-focus plus context

来源：评论

学校读者我要写书评

暂无评论

Fast Approximation of Persistence Diagrams with Guarantees 11

Fast Approximation of Persistence Diagrams with Guarantees

引用

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

作者： Vidal, Jules Tierny, Julien Sorbonne Univ CNRS Paris France

ISBN: (纸本)9781665432832

This paper presents an algorithm for the efficient approximation of the saddle-extremum persistence diagram of a scalar field. Vidal et al. introduced recently a fast algorithm for such an approximation (by interrupting a progressive computation framework [78]). However, no theoretical guarantee was provided regarding its approximation quality. In this work, we revisit the progressive framework of Vidal et al. [78] and we introduce in contrast a novel approximation algorithm, with a user controlled approximation error, specifically, on the Bottleneck distance to the exact solution. Our approach is based on a hierarchical representation of the input data, and relies on local simplifications of the scalar field to accelerate the computation, while maintaining a controlled bound on the output error. The locality of our approach enables further speedups thanks to shared memory parallelism. Experiments conducted on real life datasets show that for a mild error tolerance (5% relative Bottleneck distance), our approach improves runtime performance by 18% on average (and up to 48% on large, noisy datasets) in comparison to standard, exact, publicly available implementations. In addition to the strong guarantees on its approximation error, we show that our algorithm also provides in practice outputs which are on average 5 times more accurate (in terms of the L-2-Wasserstein distance) than a naive approximation baseline. We illustrate the utility of our approach for interactive data exploration and we document visualization strategies for conveying the uncertainty related to our approximations.

关键词： data analysis Uncertainty Runtime data visualization Parallel processing Approximation algorithms Approximation error

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：