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HDF: an update and future directions

HDF: an update and future directions

引用

ieee International symposium on Geoscience and Remote Sensing (IGARSS)

作者： M. Folk R.E. McGrath N. Yeager NCSN/University of Illinois Champaign IL USA

HDF (Hierarchical data Format) is a scientific data management project providing basic tools for managing scientific data, and support for scientists who use HDF software (http://***/). HDF products include two distinct data formats, HDF4 and HDF5, supporting libraries for reading and writing HDF data, and utilities for working with HDF. Available since 1988, HDF has become a standard for scientific data archiving and data sharing. The range of users of HDF is illustrated in tabular form. HDF is the underlying format for the HDF-EOS standard (http://***/) and consequently is the target format for a large amount of remotely sensed data. HDF5 is a completely new version of HDF that provides an improved format and more general data model, supports efficient storage of very large datasets, and is supported by an I/O library that runs on both serial and parallel platforms. The home of the HDF project is the National Center for Supercomputing Applications (NCSA) at the University of Illinois at Urbana-Champaign (***.).

关键词： Software libraries Java Application software data visualization data analysis Project management Software tools Writing Earth Observing System Remote sensing

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Reducing data Distribution Bottlenecks by Employing data visualization Filters 99

Reducing Data Distribution Bottlenecks by Employing Data Vis...

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Proceedings of the 8th ieee International symposium on High Performance Distributed Computing

作者： Ernest Franke Michael Magee

ISBN: (纸本)9780769502878

Between 1994 and 1997, researchers at Southwest Research Institute (SwRI) investigated methods for distributing parallel computation and data visualization under the support of an internally funded Research Initiative Program entitled the Advanced visualization Technology Project (AVTP). A hierarchical data cache architecture was developed to provide a flexible interface between the modeling or simulation computational processes and data visualization programs. Compared to conventional post facto data visualization approaches, this data cache structure provides many advantages including simultaneous data access by multiple visualization clients, comparison of experimental and simulated data, and visual analysis of computer simulation as computation proceeds. However, since the data cache was resident on a single workstation, this approach did not address the issue of scalability of methods for avoiding the data storage bottleneck by distributing the data across multiple networked workstations. Scalability through distributed database approaches is being investigated as part of the Applied visualization using Advanced Network Technology Infrastructure (AVANTI) *** paper describes a methodology currently under development that is intended to avoid bottlenecks that typically arise as the result of data consumers (e.g. visualization applications) that must access and process large amounts of data that has been generated and resides on other hosts, and which must pass through a central data cache prior to being used by the data consumer. The methodology is based on a fundamental paradigm that the end result (visualization) rendered by a data consumer can, in many cases, be produced using a reduced data set that has been distilled or filtered from the original data set. In the most basic case, the filtered data used as input to the data consumer may simply be a proper subset of massive data sets that have been distributed among hosts. For the general case, howeve

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parallel performance visualization using moments of utilization data 1

Parallel performance visualization using moments of utilizat...

引用

1st Merged International parallel Processing symposium/symposium on parallel and Distributed Processing (IPPS/SPDP 1998)

作者： Godin, TJ Quinn, MJ Pancake, CM Oregon State Univ Dept Comp Sci Corvallis OR 97331 USA

ISBN: (纸本)0818684038

We propose a new parallel performance visualization scheme, based on a simple moment analysis of processor utilization data. This method combines the scalability advantages of statistical summaries with the more revealing processor utilization information of Gantt charts. it scales well to large numbers of processors, requiring only storage constant in execution time.

关键词： data visualization

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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

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Hypervolume visualization: A challenge in simplicity

Hypervolume visualization: A challenge in simplicity

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ieee symposium on Volume visualization

作者： Bajaj, CL Pascucci, V Rabbiolo, G Schikore, DR Univ Texas Dept Comp Sci Austin TX 78712 USA

ISBN: (纸本)1581131054

Hyper-volume visualization is designed to provide simple and fully explanatory images that give comprehensive insights into the global structure of scalar fields of any dimension. The basic idea is to have a dimension independent viewing system that scales nicely with the geometric dimension of the dataset and that can be combined with classical approaches like isocontouring and animation of slices of no data. We completely abandon (for core simplicity) rendering techniques, such as hidden surface removal or lighting or radiosity, that enhance three dimensional realism and concentrate on the real-time display of images that highlight structural (topological) features of the no dataset (holes, tunnels, cavities, depressions, extrema, etc). Hyper-volume visualization on the one hand is a generalization of direct parallel projection methods in volume rendering. To achieve efficiency (and real-time performance on a graphics workstation) we combine the advantages of (i) a hierarchical representations of the hyper-volume data for multiresolution display and (ii) generalized object space splatting combined with texture-mapped graphics hardware acceleration. The development of a system that implements display techniques for multidimensional datasets requires careful design of both algorithms and user interfaces that scale linearly with the dimension of the input geometric space. This is a major challenge since straightforward generalizations of standard techniques that are suitable for display of 3D data yield exceedingly intricate interfaces. For example, a view manipulation graphical user interface is usually based on a rotation of the object about Cartesian rotation axes, with possibly unit quaternions internal representations for the rotation group. Unfortunately the number of independent rotation axes grows quadratically with dimension(three in 3D to six in 4D to ten in 5D to fifteen in 6D space). Going back to the basics of parallel projections, we develop an alternat

关键词： Graphical user interfaces

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Proceedings of the 1998 ieee symposium on Information visualization

作者： Ankerst, Mihael Berchtold, Stefan Keim, Daniel A. Univ of Munich Munich Germany

The order and arrangement of dimensions (variates) in crucial for the effectiveness of a large number of visualization techniques such as parallel coordinates, scatterplots, recursive pattern, and many others. In this paper, we describe a systematic approach to arrange the dimensions according to their similarity. The basic idea is to rearrange the data dimensions such that dimensions showing a similar behavior are positioned next to each other. For the similarity clustering of dimensions we need to define similarity measures which determine the partial or global similarity of dimensions. We then consider the problem of finding an optimal one- or two-dimensional arrangement of the dimensions based on their similarity. Theoretical considerations show that both, the one- and the two-dimensional arrangement problem are surprisingly hard problems, i.e. they are NP-complete. Our solution of the problem is therefore based on heuristic algorithms. An empirical evaluation using a number of different visualization techniques shows the high impact of our similarity clustering of dimensions on the visualization results.

关键词： Sorting

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Probabilistic segmentation of volume data for visualization using SOM-PNN classifier

Probabilistic segmentation of volume data for visualization ...

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1998 ieee symposium on Volume visualization, VVS 1998

作者： Ma, Feng Wang, Wenping Tsang, Wai Wan Tang, Zesheng Xia, Shaowei Tong, Xin Department of Automation Tsinghua University Beijing100084 China Department of Computer Science University of Hong Kong Pokfulam Road Hong Kong Hong Kong Department of Computer Science Tsinghua University Beijing100084 China

ISBN: (纸本)1581131054

We present a new probabilistic classifier, called SOM-PNN classifier, for volume data classification and visualization. The new classifier produces probabilistic classification with Bayesian confidence measure which is highly desirable in volume rendering. Based on the SOM map trained with a large training data set, our SOM-PNN classifier performs the probabilistic classification using the PNN algorithm. This combined use of SOM and PNN overcomes the shortcomings of the parametric methods, the non-parametric methods, and the SOM method. The proposed SOM-PNN classifier has been used to segment the CT sloth data and the 20 human MRI brain volumes resulting in much more informative 3D rendering with more details and less artifacts than other methods. Numerical comparisons demonstrate that the SOM-PNN classifier is a fast, accurate and probabilistic classifier for volume rendering. Copyright 1998 ieee.

关键词： Wavelet transforms

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Proceedings of the 1998 ieee symposium on Volume visualization, VVS 1998

Proceedings of the 1998 IEEE Symposium on Volume Visualizati...

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1998 ieee symposium on Volume visualization, VVS 1998

ISBN: (纸本)1581131054

The proceedings contain 18 papers. The topics discussed include: coloring voxel-based objects for virtual endoscopy;probabilistic segmentation of volume data for visualization using SOM-PNN classifier;semi-automatic generation of transfer functions for direct volume rendering;adaptive perspective ray casting;a real-time volume rendering architecture using an adaptive resampling scheme for parallel and perspective projections;an exact interactive time visibility ordering algorithm for polyhedral cell complexes;volume animation using the skeleton tree;3D scan conversion of CSG models into distance volumes;adding shadows to a texture-based volume renderer;edge presentation in volume rendering using splatting;using distance maps for accurate surface representation in sampled volumes;wavelet based adaptive interpolation for volume rendering;object voxelization by filtering;an accurate method for voxelizing polygon meshes;extracting ISO-valued features in 4-dimensional scalar fields;and opaci@-weighted color interpolation for volume sampling.

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Hypervolume visualization: a challenge in simplicity

Hypervolume visualization: a challenge in simplicity

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ieee symposium on Volume visualization and graphics

作者： C.L. Bajaj V. Pascucci G. Rabbiolo D.R. Schikore Department of Computer Sciences and TICAM University of Technology Austin TX USA Department of Mathematics Purdue University West Lafayette IN USA Center for Applied Scientific Computing Lawrence Livemore National Laboratory Livermore CA USA

Hypervolume visualization is designed to provide simple and fully explanatory images that give comprehensive in-sights into the global structure of scalar fields of any dimension. The basic idea is to have a dimension independent viewing system that scales nicely with the geometric dimension of the dataset and that can be combined with classical approaches like isocontouring and animation of slices of nD data. One completely abandons (for core simplicity) rendering techniques, such as hidden surface removal or lighting or radiosity, that enhance three dimensional realism and concentrate on the real-time display of images that highlight structural (topological) features of the no dataset (holes, tunnels, cavities, depressions, extrema, etc.). Hypervolume visualization on the one hand is a generalization of direct parallel projection methods in volume rendering. To achieve efficiency (and real-time performance on a graphics workstation) the authors combine the advantages of (i) a hierarchical representations of the hypervolume data for multiresolution display and (ii) generalized object space splatting combined with texture-mapped graphics hardware acceleration. The main results of the paper are thus both a multiresolution direct rendering algorithm and scalable graphical user interface that provides global views of scalar fields in any dimension, while maintaining the fundamental characteristics of ease of use, and quick exploratory user interaction.

关键词： Rendering (computer graphics) graphics Animation Three dimensional displays data visualization Workstations Hardware Acceleration Graphical user interfaces

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Probabilistic segmentation of volume data for visualization using SOM-PNN classifier

Probabilistic segmentation of volume data for visualization ...

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ieee symposium on Volume visualization and graphics

作者： Feng Ma Wenping Wang Wai Wan Tsang Zesheng Tang Shaowei Xia Xin Tong Tsinghua University China University of Hong Kong Hong Kong China

We present a new probabilistic classifier, called SOM-PNN classifier, for volume data classification and visualization. The new classifier produces probabilistic classification with Bayesian confidence measure which is highly desirable in volume rendering. Based on the SOM map trained with a large training data set, our SOM-PNN classifier performs the probabilistic classification using the PNN algorithm. This combined use of SOM and PNN overcomes the shortcomings of the parametric methods, the nonparametric methods, and the SOM method. The proposed SOM-PNN classifier has been used to segment the CT sloth data and the 20 human MRI brain volumes resulting in much more informative 3D rendering with more details and less artifacts than other methods. Numerical comparisons demonstrate that the SOM-PNN classifier is a fast, accurate and probabilistic classifier for volume rendering.

关键词： data visualization Bayesian methods Volume measurement Training data Humans Magnetic resonance imaging

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