Distributed and Parallel Systems pp 90-97 | Cite as
Interactive Virtual Reality Volume Visualization on the Grid
Abstract
Grid computing evolves into a standard method for processing large datasets. Consequently most available grid applications focus on high performance computing and high-throughput computing. The interactive visualization of the acquired simulation results can be performed directly on the grid using the Grid Visualization Kernel GVK, which is a grid middleware extension built on top of the Globus Toolkit. An example is the visualization of volume data within Virtual Reality environments, where the data for visualization is generated somewhere on the grid, while the user explores the visual representation at some other place on the grid.
Keywords
grid computing scientific visualization interaction virtual realityPreview
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References
- [1]G. Allen, T. Goodale, E. Seidel: The cactus computational collaboratory: Enabling technologies for relativistic astrophysics,and a toolkit for solving pdes by communities in science and engineering, 7th Symposium on the Frontiers of Massively Parallel Computation-Frontiers 99, IEEE, New York 1999Google Scholar
- [2]C. Cruz-Neira, D. J. Sandin, T. A. DeFanti, R. V. Kenyon, J. C. Hart: The CAVE: audio visual experience automatic virtual environment, Communications of the ACM, Vol. 35, No. 6, pp. 64–72, 1992CrossRefGoogle Scholar
- [3]I. Foster, C. Kesselman: Globus: A Metacomputing Infrastructure Toolkit, Intl. Journal of Supercomputer Applications, Vol. 11, No. 2, pp. 4–18, 1997Google Scholar
- [4]I. Foster, C. Kesselman, S. Tuecke: The Anatomy of the Grid - Enabling Scaleable Virtual Organizations, Intl. Journal of Supercomputer Applications, Vol. 5, No. 3, 2001Google Scholar
- [5]M. Garland, P. S. Heckbert: Surface Simplification Using Quadric Error Metrics, Computer Graphics, Vol. 31, pp. 209–216, 1997Google Scholar
- [6]G. A. Geist, J. A. Kohl P. M. Papadopoulos: CUMULVS: Providing Fault-Tolerance, Visualization and Steering of Parallel Applications, Intl. Journal of High Performance Computing Applications, Vol. 11, No. 3, pp. 224–236, August 1997CrossRefGoogle Scholar
- [7]A. Grimshaw, A. Ferrari, F. Knabe, M. Humphrey: Legion: An Operating System for Wide-Area Computing, IEEE Computer, Vol. 32, No. 5, pp. 29–37, 1999CrossRefGoogle Scholar
- [8]H. Hoppe: Progressive meshes, Proc. ACM SIGGRAPH ’96, pp. 99–108, 1996MathSciNetGoogle Scholar
- [9]G: Humphreys, M. Eldridge, I. Buck, G. Stoll, M. Everett, P. Hanrahan: WireGL: a scalable graphics system for clusters, Proc. ACM SIGGRAPH ’01, pp. 129–140, 2001Google Scholar
- [10]D. Kranzlmiiller, B. Reitinger, I. Hackl, J. Volkert: Voice Controlled Virtual Reality and Its Perspectives for Everyday Life, Proc. APC 2001, Arbeitsplatz-computer 2001, Fachtagung der GI/ITG Fachgruppe APS+PC zum Thema “Pervasive Ubiquitous Computing”, VDE-Verlag, Technical University Munich, Munich, Germany, pp. 101–107, 2001Google Scholar
- [11]D. Kranzlmiiller, G. Kurka, P. Heinzlreiter, J. Volkert: Optimizations in the Grid Visualization Kernel, Proc. of PDIVM 2002, Workshop on Parallel and Distributed Computing in Image Processing, Video Processing and Multimedia, IPDPS 2002 Symposion, Ft. Lauderdale, Florida, April 2002Google Scholar
- [12]J. Leigh, A. E. Johnson, T. A. DeFanti: CAVERN: A Distributed Architecture for Supporting Scalable Persistence and Interoperability in Collaborative Virtual Environments, Journal of Virtual Reality Research, Development and Applica- tions, Vol. 2.2, pp. 217–237, the Virtual Reality Society 1997Google Scholar
- [13]D. A. Lelewer, D. S. Hirschberg: Data Compression, ACM Computing Surveys (CSUR), Vol. 19, No. 3, pp. 261–296, 1987MATHCrossRefGoogle Scholar
- [14]W. E. Lorensen, H. E. Cline: Marching cubes: A high resolution 3D surface construction algorithm, Proc. ACM SIGGRAPH ’87, pp. 163–169, 1987Google Scholar
- [15]L. McMillan, G. Bishop: Plenoptic modeling: an image-based rendering system, Proc. ACM SIGGRAPH ’95, pp. 39–46, 1995Google Scholar
- [16]M. Romberg: The Unicore Architecture: Seamless Access to Distributed Resources, Proc. 8th IEEE Symposion on High Performance Distributed Computing, HPDC 1999, pp. 287–293, Los Alamitos, California, August 1999Google Scholar
- [17]M. Woo, J. Neider, T. Davis, D. Shreiner: OpenGL Programming Guide, Third Edition, Addison Wesley, 1999Google Scholar
- [18]H. Zhang, D. Manocha, T. Hudson, K. Hoff: Visibility Culling using Hierarchical Occlusion Maps, Proc. ACM SIGGRAPH’97, pp. 77–88, 1997Google Scholar