Skip to main content
SpringerLink
Log in

Evolving Dataflow Visualization Environments to Grid Computing

  • Conference paper
Book cover Scientific Visualization: The Visual Extraction of Knowledge from Data

Part of the book series: Mathematics and Visualization ((MATHVISUAL))

  • 1705 Accesses

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

Access this chapter

Log in via an institution
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. AVS/Express website, 2004. http://www.avs.com.

    Google Scholar 

  2. E. W. Bethel and J. Shalf. Grid-distributed visualizations using connectionless protocols. IEEE Computer Graphics and Applications, 23(2):51–59, March/April 2003.

    Article  Google Scholar 

  3. cAVS website, 2004. http://cavs.sdsc.edu.

    Google Scholar 

  4. J. Chin, J. Harting, S. Jha, P.V. Coveney, A.R. Porter, and S. Pickles. Steering in computational science: mesoscale modelling and simulation. Contemporary Physics, 44:417–434, 2003.

    Article  Google Scholar 

  5. D.A. Duce, J.R. Gallop, I.J. Johnson, K. Robinson, C.D. Seelig, and C.S. Cooper. Distributed Cooperative Visualization-Experiences and Issues from MANICORAL Project. In EG Workshop on Visualization in Scientific Computing. Eurographics Association, 1998.

    Google Scholar 

  6. E. Engquist. Steering and visualization of electromagnetic simulations using Globus. In Simulation and Visualization on the Grid, pages 82–97. Springer Series LNCSE, 2000.

    Google Scholar 

  7. I. Foster, J. Insley, G. von Lasewski, C. Kesselman, and M. Thiebaux. Distance visualization: Data exploration on the Grid. IEEE Computer, December:36–43, 1999.

    Google Scholar 

  8. I. Foster, C. Kesselman, and S. Tuecke. The anatomy of the Grid: Enabling scalable virtual organisations. International Journal of High Performance Computing Applications, 15(3):200–222, 2001.

    Article  Google Scholar 

  9. Globus website, 2004. http://www.globus.org.

    Google Scholar 

  10. C. Goodyer, J. Wood, and M. Berzins. A parallel grid based PSE for EHL problems. In J. Fagerholm, J. Haataja, J. Jarvinen, M. Lyly, M. Raback, and V. Savolainen, editors, Applied Parallel Computing Advanced Scientific Computing 6th International Conference, PARA 2002, pp. 521–530. Springer-Verlag, 2002.

    Google Scholar 

  11. R. B. Haber and D. A. McNabb. Visualization Idioms: A Conceptual Model for Scientific Visualization Systems. In B. Shriver, G. M. Neilson, and L. J. Rosenblum, editors, Visualization In Scientific Computing, pp. 74–93. IEEE Computer Society Press, 1990.

    Google Scholar 

  12. T.J. Jankun-Kelly, O. Kreylos, K. Ma, B. Hamann, K.I. Joy, J. Shalf, and E.W. Bethel. Deploying web-based visual exploration tools on the grid. IEEE Computer Graphics and Applications, 23(2):40–50, March/April 2003.

    Article  Google Scholar 

  13. C.R. Johnson, S. Parker, D. Weinstein, and S. Heffernan. Component-based problem solving environments for large-scale scientific computing. Journal on Concurrency and Computation: Practice and Experience, (14):1337–1349, 2002.

    Google Scholar 

  14. R. Marshall, J. Kempf, S. Dyer, and C. Yen. Visualization methods and computational steering for a 3d turbulence model for Lake Erie. ACM SIGGRAPH Computer Graphics, 24(2), 1990.

    Google Scholar 

  15. B. H. McCormick, T. A. DeFanti, and M. D. Brown. Visualization in scientific computing. Computer Graphics, 21(6), 1987.

    Google Scholar 

  16. National Grid Service website, 2004. http://www.ngs.ac.uk.

    Google Scholar 

  17. A. Norton and A. Rockwood. Enabling view-dependent progressive volume visualization on the grid. IEEE Computer Graphics and Applications, 23(2):22–31, March/April 2003.

    Article  Google Scholar 

  18. 2004. http://www.opendx.org.

    Google Scholar 

  19. S. G. Parker and C. R. Johnson. SCIRun: A scientific programming environment for computational steering. In H. W. Meuer, editor, Proceedings of Supercomputer’ 95, New York, 1995. Springer-Verlag.

    Google Scholar 

  20. W. J. Schroeder, K. M. Martin, and W. E. Lorensen. The Visualization Toolkit: An Object Oriented Approach to 3D Graphics. Kitware, Inc., 3rd edition, 2003.

    Google Scholar 

  21. J. Shalf and E. W. Bethel. The Grid and future visualization system architectures. IEEE Computer Graphics and Applications, 23(2):6–9, March/April 2003.

    Article  Google Scholar 

  22. TeraGrid website, 2004. http://www.teragrid.org.

    Google Scholar 

  23. A Tomlin, M. Berzins, J. Ware, and M.J. Pilling. On the use of adaptive gridding methods for modelling chemical transport from multi-scale sources. Atmospheric Environment, 31(18):2945–2959, 1997.

    Article  Google Scholar 

  24. Edward R. Tufte. Visual Explanations: Images and Quantities, Evidence and Narrative. Graphics Press, 1997.

    Google Scholar 

  25. VTK website, 2004. http://public.kitware.com/VTK/.

    Google Scholar 

  26. J. P. R. B. Walton. NAG’s IRIS Explorer. In C. R. Johnson and C. D. Hansen, editors, Visualization Handbook. Academic Press, 2003, in press. Available from http://www.nag.co.uk/doc/TechRep/Pdf/tr203.pdf.

    Google Scholar 

  27. White Rose Grid website, 2004. http://www.wrg.org.uk.

    Google Scholar 

  28. J. D. Wood, H. Wright, and K. W. Brodlie. Collaborative visualization. In R. Yagel and H. Hagen, editors, Proceedings of IEEE Visualization’ 97, pp. 253–259, 1997.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Computing, University of Leeds, Leeds, LS2 9JT, UK

    Ken Brodlie, Sally Mason, Martin Thompson, Mark Walkley & Jason Wood

Authors
  1. Ken Brodlie
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sally Mason
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Martin Thompson
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Mark Walkley
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jason Wood
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Lab. LMC-IMAG, Universite Grenoble I, BP 53, 38041, Grenoble CX 9, France

    Georges-Pierre Bonneau

  2. Visualization and Interactive Systems Institute (VIS), University of Stuttgart, Universitätßtraße 38, 70569, Stuttgart, Germany

    Thomas Ertl

  3. Department of Computer Science and Engineering Ira A. Fulton School of Engineering, Arizona State University, Tempe, AZ, 85287-8809, USA

    Gregory M. Nielson

Rights and permissions

Reprints and permissions

Copyright information

© 2006 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Brodlie, K., Mason, S., Thompson, M., Walkley, M., Wood, J. (2006). Evolving Dataflow Visualization Environments to Grid Computing. In: Bonneau, GP., Ertl, T., Nielson, G.M. (eds) Scientific Visualization: The Visual Extraction of Knowledge from Data. Mathematics and Visualization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-30790-7_23

Download citation

Publish with us

Policies and ethics

Search

Navigation