Skip to main content

Grid Services for 3D Data Analysis in Virtual Laboratories

  • Conference paper
Grid Enabled Remote Instrumentation

Part of the book series: Signals and Communication Technology ((SCT))

Abstract

We present a Grid-aware application for the extraction of isosurfaces from volumetric data sets. This is an important issue in the design of a virtual laboratory since it permits to analyze data produced by different types of scientific instruments. After a short description of the basic functionalities we focus on the issues for the efficient use of Grid resources. Our implementation is designed following a Grid service approach and adopts Globus Toolkit 4 as middleware. The main advantages of the use of the Grid are the possibility of processing huge data sets and of satisfying more requests simultaneously.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. A Grid Application Toolkit and Testbed, http://www.gridlab.org/.

  2. Andronico G, Ardizzone V, Barbera R, Catania R, Carrieri A, Falzone A, Giorgio E, La Rocca G, Monforte S, Pappalardo M, Passaro G, Platania G (2005). {“GILDA: The Grid INFN Virtual Laboratory for Dissemination Activities”}. Proceedings of the First International Conference on Testbeds and Research Infrastructures for the DEvelopment of NeTworks and COMmunities (TRIDENTCOM’05), 304–305.

    Google Scholar 

  3. Andújar C, Brunet P, Chica A, Navazo I, Rossignac J, Vinacua A (2005). “Optimizing the Topological and Combinatorial Complexity of Isosurfaces”. Computer-Aided Design 37:8, 847–857.

    Article  Google Scholar 

  4. Baker P, Bethel W, Clyne J, Fulcomer S, Hathaway B, Kohl J, Moran P, Parker S (2003). “DiVA: Distributed Visualization Framework Component Interface”. Proceedings of Workshop Findings Document.

    Google Scholar 

  5. Clematis A, Corana A, D’Agostino D, Gianuzzi V, Merlo A (2006). “Resorurce Selection and Application Execution in a Grid: A Migration Experience from GT2 to GT4”. Proceedings of the International Symposium on Grid computing, high-performAnce and Distributed Applications (GADA), LNCS 4276, Springer, 1132–1142.

    Chapter  Google Scholar 

  6. Clematis A, D’Agostino D (2006). “Parallel Remote Visualization for the Grid”. Dongarra J, Zima H, Hoisie A, Yang LT, Di Martino B (eds) Engineering the Grid: Status and Perspective, American Scientific Publishers, 521–536.

    Google Scholar 

  7. D’Agostino D (2006). “Designing Parallel Programs for 3D Data Processing on Distributed Architectures”. PhD Thesis, DISI-TH-2006-03, Università di Genova, Genova.

    Google Scholar 

  8. Foster I (2006). “Globus Toolkit Version 4: Software for Service Oriented Systems”. Journal of Computer Science and Technology 21:4, 513–520.

    Article  Google Scholar 

  9. Garland M, Heckbert PS (1997). “Surface Simplification Using Quadric Error Metrics”. Computer Graphics 31, 209–216.

    Google Scholar 

  10. Gotsman C, Gumhold S, Kobbelt L (2002). “Simplification and Compression of 3D Meshes”. Iske A, Quak E, Floater MS (eds) Tutorials on Multiresolution in Geometric Modelling, Springer-Verlag, 319–361.

    MATH  Google Scholar 

  11. Gropp W, Lusk E, Doss N, Skjellum A (1996). “High-Performance, Portable Implementation of the MPI Message Passing Interface Standard”. Parallel Computing 22:6, 789–828.

    Article  Google Scholar 

  12. Heinzlreiter P, Kranzlmuller D (2003). “Visualization Services on the Grid: The Grid Visualization Kernel”. Parallel Processing Letters 13:2, 135–148.

    Article  MathSciNet  Google Scholar 

  13. Heymann E, Senar MA, Fernández E, Fernández A, Salt J (2004). “Managing MPI Applications in Grid Environments”. Proceedings of the Second European Across Grids Conference (AxGrids 2004), LNCS 3165, Springer, 42–50.

    Google Scholar 

  14. Kranzlmuller D, Kurka G, Heinzlreiter P, Volkert J (2002). “Optimizations in the Grid Visualization Kernel”. Proceedings of Workshop on Parallel and Distributed Computing in Image Processing, Video Processing, and Multimedia, 129–135.

    Google Scholar 

  15. Lacour S, P’erez C, Priol T (2005). “Generic Application Description Model: Toward Automatic Deployment of Applications on Computational Grids”. The 6th IEEE/ACM International Workshop on Grid Computing (Grid2005), Springer.

    Google Scholar 

  16. Ligon III WB, Ross RB (2001). “PVFS: Parallel Virtual File System”. Beowulf Cluster Computing with Linux, MIT Press, 391–430.

    Google Scholar 

  17. Lorensen WE, Cline HE (1987). “Marching Cubes: A High Resolution 3D Surface Construction Algorithm”. Computer Graphics (Proceedings of SIGGRAPH 87) 21:4, 163–169.

    Article  Google Scholar 

  18. Lumb I, Smith C (2004). “Scheduling Attributes and Platform LSF”. Grid Resource Management: State of the Art and Future Trends, Kluwer Academic, 171–182.

    Chapter  Google Scholar 

  19. Remote Instrumentation in Next-Generation Grids (RINGrid), http://www.gup.uni-linz.ac.at/ringrid/.

  20. Rossignac J (1999). “Edgebreaker: Connectivity Compression for Triangle Meshes”. IEEE Transactions on Visualization and Computer Graphics 5:1, 47–61.

    Article  MathSciNet  Google Scholar 

  21. Shalf J, Bethel EW (2003). “The Grid and Future Visualization System Architectures”. IEEE Computer Graphics and Applications 23:2, 6–9.

    Article  Google Scholar 

  22. Sipos G, Kacsuk P (2006). “Multi-grid, Multi-user Workflows in the P-GRADE Portal”. Journal of Grid Computing 3:3–4, 221–238.

    Google Scholar 

  23. The Digital Imaging and Communications in Medicine standard (DICOM), ftp://medical. nema.org/medical/dicom/.

    Google Scholar 

  24. The Grid Development Tools for Eclipse, http://ds.informatik.uni-marburg.de/MAGE/gdt/.

  25. The Grid enabled Remote Instrumentation with Distributed Control and Computation (GRIDCC), http://www.gridcc.org/.

  26. The Object File Format (OFF), http://www.dcs.ed.ac.uk/home/mxr/gfx/3d/OFF.spec.

    Google Scholar 

  27. The Virtual Reality Model Language (VRML), http://www.web3d.org/.

  28. The Visible Human Project, http://www.nlm.nih.gov/research/visible/visible_human.html.

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer Science+Business Media, LLC

About this paper

Cite this paper

Clematis, A., Corana, A., D’Agostino, D., Gianuzzi, V., Merlo, A. (2009). Grid Services for 3D Data Analysis in Virtual Laboratories. In: Davoli, F., Meyer, N., Pugliese, R., Zappatore, S. (eds) Grid Enabled Remote Instrumentation. Signals and Communication Technology. Springer, New York, NY. https://doi.org/10.1007/978-0-387-09663-6_32

Download citation

  • DOI: https://doi.org/10.1007/978-0-387-09663-6_32

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-0-387-09662-9

  • Online ISBN: 978-0-387-09663-6

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics