检索结果-内蒙古大学图书馆

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

作者： Wang, Feng Wald, Ingo Johnson, Chris R. Univ Utah Inst Sci Salt Lake City UT 84112 USA Intel Corp Santa Clara CA 95051 USA NVIDIA Santa Clara CA USA

ISBN: (纸本)9781728126050

Recent advances in large-scale simulations have resulted in volume data of increasing size that stress the capabilities of off-the-shelf visualization tools. Users suffer from long data loading times, because large data must be read from disk into memory prior to rendering the first frame. In this work, we present a volume renderer that enables high-fidelity interactive visualization of large volumes on multi-core CPU architectures. Compared to existing CPU-based visualization frameworks, which take minutes or hours for data loading, our renderer allows users to get a data overview in seconds. Using a hierarchical representation of raw volumes and ray-guided streaming. we reduce the data loading time dramatically and improve the user's interactivity experience. We also examine system design choices with respect to performance and scalability. Specifically, we evaluate the hierarchy generation time, which has been ignored in most prior work, but which can become a significant bottleneck as data scales. Finally, we create a module on top of the OSPRay ray tracing framework that is ready to be integrated into general-purpose visualization frameworks such as Paraview.

关键词： large-scale visualization visualization techniques Progressive Rendering visualization design and evaluation methods

来源：评论

学校读者我要写书评

暂无评论

Efficient parallel out-of-core isosurface extraction 03

Efficient parallel out-of-core isosurface extraction

引用

ieee symposium on parallel and large-data visualization and graphics

作者： Zhang, HJ Newman, TS Univ Alabama Dept Comp Sci Huntsville AL 35899 USA

ISBN: (纸本)078038122X

A new approach for large dataset isosurface extraction is presented. The approach's aim is efficient parallel isosurfacing when the dataset cannot be processed entirely in-core. The approach focuses on reducing the memory requirement and optimizing disk I/O while achieving a balanced load. In particular, an accurate model of isosurface extraction time is exploited to evenly distribute work across processors. The approach achieves processing efficiency by also avoiding unnecessary processing for portions of the dataset that are not intersected by the isosurface. To reduce the redundant computations and the storage requirements, a flexible, variably-granular data structure is utilized, thereby achieving excellent time and space performance.

关键词： isosurface extraction load balancing out-of-core parallel processing

来源：评论

学校读者我要写书评

暂无评论

large volume visualization of compressed time-dependent datasets on GPU clusters

引用

parallel COMPUTING 2005年第2期31卷 205-219页

作者： Strengert, M Magallón, M Weiskopf, D Guthe, S Ertl, T Univ Stuttgart Inst Visualizat & Interact Syst D-70569 Stuttgart Germany Univ Costa Rica Escuela Fis San Pedro 2060 Costa Rica Univ Tubingen GRIS WSI D-72076 Tubingen Germany

We describe a system for the texture-based direct volume visualization of large data sets on a PC cluster equipped with GPUs. The data is partitioned into volume bricks in object space, and the intermediate images are combined to a final picture in a sort-last approach. Hierarchical wavelet compression is applied to increase the effective size of volumes that can be handled. An adaptive rendering mechanism takes into account the viewing parameters and the properties of the data set to adjust the texture resolution and number of slices. We discuss the specific issues of this adaptive and hierarchical approach in the context of a distributed memory architecture and present corresponding solutions. Furthermore, our compositing scheme takes into account the footprints of volume bricks to minimize the costs for reading from framebuffer, network communication, and blending. A detailed performance analysis is provided for several network, CPU, and GPU architectures-and scaling characteristics of the parallel system are discussed. For example, our tests on a eight-node AMD64 cluster with InfiniBand show a rendering speed of 6 frames per second for a 2048 x 1024 x 1878 data set on a 1024(2) viewport. (c) 2005 Elsevier B.V. All rights reserved.

关键词： graphics systems distributed/network graphics viewing algorithms

来源：评论

学校读者我要写书评

暂无评论

An efficient and scalable parallel algorithm for out-of-core isosurface extraction and rendering

引用

JOURNAL OF parallel AND DISTRIBUTED COMPUTING 2007年第5期67卷 592-603页

作者： Wang, Qin Jaja, Joseph Varshney, Amitabh Univ Maryland Dept Elect & Comp Engn Inst Adv Comp Studies College Pk MD 20742 USA Univ Maryland Dept Comp Sci Inst Adv Comp Studies College Pk MD 20742 USA

We consider the problem of isosurface extraction and rendering for large scale time-varying data. Such data sets have been appearing at an increasing rate especially from physics-based simulations, and can range in size from hundreds of gigabytes to tens of terabytes. Isosurface extraction and rendering is one of the most widely used visualization techniques to explore and analyze such data sets. A common strategy for isosurface extraction involves the determination of the so-called active cells followed by a triangulation of these cells based on linear interpolation, and ending with a rendering of the triangular mesh. We develop a new simple indexing scheme for out-of-core processing of large scale data sets, which enables the identification of the active cells extremely quickly, using more compact indexing structure and more effective bulk data movement than previous schemes. Moreover, our scheme leads to an efficient and scalable implementation on multiprocessor environments in which each processor has access to its own local disk. In particular, our parallel algorithm provably achieves load balancing across the processors independent of the isovalue, with almost no overhead in the total amount of work relative to the sequential algorithm. We conduct a large number of experimental tests on the University of Maryland visualization Cluster using the Richtmyer-Meshkov instability data set, and obtain results that consistently validate the efficiency and the scalability of our algorithm. (C) 2007 Elsevier Inc. All rights reserved.

关键词： parallel isosurface extraction scientific visualization

来源：评论

学校读者我要写书评

暂无评论

Mapping High-Fidelity Volume Rendering for Medical Imaging to CPU, GPU and Many-Core Architectures

引用

ieee TRANSACTIONS ON visualization AND COMPUTER graphics 2009年第6期15卷 1563-1570页

作者： Smelyanskiy, Mikhail Holmes, David Chhugani, Jatin Larson, Alan Carmean, Douglas M. Hanson, Dennis Dubey, Pradeep Augustine, Kurt Kim, Daehyun Kyker, Alan Lee, Victor W. Nguyen, Anthony D. Seiler, Larry Robb, Richard Intel Corp Santa Clara CA 95051 USA Mayo Clin Rochester MN 55905 USA

Medical volumetric imaging requires high fidelity, high performance rendering algorithms. We motivate and analyze new volumetric rendering algorithms that are suited to modern parallel processing architectures. First, we describe the three major categories of volume rendering algorithms and confirm through an imaging scientist-guided evaluation that ray-casting is the most acceptable. We describe a thread- and data-parallel implementation of ray-casting that makes it amenable to key architectural trends of three modern commodity parallel architectures: multi-core, GPU, and an upcoming many-core Intel (R) architecture code-named Larrabee. We achieve more than an order of magnitude performance improvement on a number of large 3D medical datasets. We further describe a data compression scheme that significantly reduces data-transfer overhead. This allows our approach to scale well to large numbers of Larrabee cores.

关键词： Volume Compositing parallel Processing Many-core Computing Medical Imaging graphics Architecture GPGPU

来源：评论

学校读者我要写书评

暂无评论

Interactive exploratory visualization of 2D vector fields

引用

COMPUTER graphics FORUM 2008年第3期27卷 983-990页

作者： Isenberg, Tobias Everts, Maarten H. Grubert, Jens Carpendale, Sheelagh Univ Groningen NL-9700 AB Groningen Netherlands Univ Calgary Calgary AB T2N 1N4 Canada

In this paper we present several techniques to interactively explore representations of 2D vector fields. Through a set of simple hand postures used on large, touch-sensitive displays, our approach allows individuals to custom design glyphs (arrows, lines, etc.) that best reveal patterns of the underlying dataset. Interactive exploration of vector fields is facilitated through freedom of glyph placement, glyph density control, and animation. The custom glyphs can be applied individually to probe specific areas of the data but can also be applied in groups to explore larger regions of a vector field. Re-positionable sources front which glyphs-animated according to the local vector field-continue to emerge are used to examine the vector field dynamically. The combination of these techniques results in an engaging visualization with which the user can rapidly explore and analyze varying types of 2D vector fields, using a virtually infinite number of custom-designed glyphs.

关键词： I.3.6 [Computer graphics]: Methodology and Techniques—Interaction techniques I.3.m [Computer graphics]: Miscellaneous—visualization

来源：评论

学校读者我要写书评

暂无评论

EG PGV 2012 - 12th Eurographics symposium on parallel graphics and visualization

EG PGV 2012 - 12th Eurographics Symposium on Parallel Graphi...

引用

12th Eurographics symposium on parallel graphics and visualization, EG PGV 2012

ISBN: (纸本)9783905674354

The proceedings contain 15 papers. The topics discussed include: HyperFlow: a heterogeneous dataflow architecture;PISTON: a portable cross-platform framework for data-parallel visualization operators;explicit cache management for volume ray-casting on parallel architectures;GLuRay: ray tracing in scientific visualization applications using OpenGL interception;a study of ray tracing large-scale scientific data in parallel visualization applications;dynamic scheduling for large-scale distributed-memory ray tracing;fast collision culling in large-scale environments using GPU mapping function;light propagation maps on parallel graphics architectures;polygonization of implicit surfaces on multi-core architectures with SIMD instructions;load-balanced multi-GPU ambient occlusion for direct volume rendering;parallel rendering on hybrid multi-GPU clusters;and auto splats: dynamic point cloud visualization on the GPU.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Dax toolkit: A proposed framework for data analysis and visualization at extreme scale

Dax toolkit: A proposed framework for data analysis and visu...

引用

1st ieee symposium on large-Scale data Analysis and visualization 2011, LDAV 2011

作者： Moreland, Kenneth Ayachit, Utkarsh Geveci, Berk Ma, Kwan-Liu Sandia National Laboratories United States Kitware Inc. United States University of California Davis CA United States

ISBN: (纸本)9781467301541

Experts agree that the exascale machine will comprise processors that contain many cores, which in turn will necessitate a much higher degree of concurrency. Software will require a minimum of a 1,000 times more concurrency. Most parallel analysis and visualization algorithms today work by partitioning data and running mostly serial algorithms concurrently on each data partition. Although this approach lends itself well to the concurrency of current high-performance computing, it does not exhibit the appropriate pervasive parallelism required for exascale computing. The data partitions are too small and the overhead of the threads is too large to make effective use of all the cores in an extreme-scale machine. This paper introduces a new visualization framework designed to exhibit the pervasive parallelism necessary for extreme scale machines. We demonstrate the use of this system on a GPU processor, which we feel is the best analog to an exascale node that we have available today. © 2011 ieee.

关键词： data visualization

来源：评论

学校读者我要写书评

暂无评论

The feature tree: Visualizing feature tracking in distributed AMR datasets 03

The feature tree: Visualizing feature tracking in distribute...

引用

ieee symposium on parallel and large-data visualization and graphics

作者： Chen, J Silver, D Jiang, L Rutgers State Univ Dept Elect & Comp Engn Piscataway NJ 08855 USA

ISBN: (纸本)078038122X

In this paper, we describe a feature extraction and tracking algorithm for AMR (Adaptive Mesh Refinement) datasets that operates within a distributed computing environment. Because features can span multiple refinement levels and multiple processors, tracking must be performed across time, across levels, and across processors. The resulting visualization is represented as a "Feature Tree". A feature will now contain multiple parts corresponding to different levels of refinements. The feature tree allows a viewer to determine that a feature splits or merges at the next refinement level, and allows a viewer to extract and isolate a multi-level isosurface and watch how that surface changes over both time and space. The algorithm is implemented within a computational steering environment which enables the visualization routines to operate on the data in-situ (while the simulation is ongoing).

关键词： scientific visualization AMR visualization feature tracking distributed visualization problem solving environment

来源：评论

学校读者我要写书评

暂无评论

Using PVM and MPI for co-processed, distributed and parallel scientific visualization 12th

引用

10 Workshops held in conjunction with 12th International parallel symposium and 9th symposium on parallel and Distributed Processing, IPPS/SPDP 1998

作者： Haimes, Robert Jordan, Kirk E. Department of Aeronautics and Astronautics Massachusetts Institute of Technology United States IBM Corporation 404 Wyman Street WalthamMA02254 United States

ISBN: (纸本)3540643591

This paper discusses the combined use of MPI and PVM in the parallel visualization tool kit, pV3. The implementation provides for efficient co-processed, distributed parallel visualization of large-scale 3D time dependent simulations. The primary goals of pV3 include the ability;to handle large-scale transient 3D simulations, to take full advantage of available hardware encompassing both parallel compute engines and graphics workstations, to visualize the data as the computation progresses, to interact and interrogate the data as its computed, and to steer the simulation by adjusting parameters obtaining immediate feedback from the changes. Based on a client/server model, the original implementation of pV3 was founded on PVM. The client portion executes coupled closely with the application code and ‘extracts’ from the distributed data volume, in place, lower dimensional data. The distilled data is transferred to the interactive server portion of pV3 (executing on a graphics workstation) where the rendering and display are performed. This unique architecture frees up the compute engine(s) from dealing with the graphics, and reduces the large data-set to a size that can be rapidly transported to the server using standard network connections. There are some drawbacks in using PVM on parallel machines which stem from TCP/IP communications. These include, in some instances, not taking full advantage of the hardware interconnect on the machine as communication must occur with the graphics workstation. This can result in smaller messages and increased latency. In addition, pV3’s dynamic attachment required that the graphics workstation be accessible from each node on the machine with PVM's ‘group’ functionality intact, which poses a problem on some parallel systems. The pV3 ‘concentrator’ module was designed to overcome such problems on distributed memory platforms. All pV3 messages on the parallel machine use the high-speed interconnect via the MPI protocol. Communication

关键词： Engines

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：