Skip to main content
SpringerLink
Log in

A Dynamic Parallel Volume Rendering Computation Mode Based on Cluster

  • Conference paper
Computational Science and Its Applications – ICCSA 2005 (ICCSA 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3482))

Included in the following conference series:

Abstract

Based on cluster, a dynamic parallel mode–the MSGD (Master-Slave-Gleaner-Dynamic) mode is presented in this paper. Combining the load balancing with the MSG (Master-Slave-Gleane) mode, this mode brings in a load balancing strategy–task pool, which can coordinate the workload of each node effectively. A volume rendering algorithm called Splatting is used to test the performance of this mode on IBM Cluster1350. The results prove that this mode can effectively increase the total calculation speed and improve the global load balance. In addition this mode has good scalability and is suitable for various parallel volume rendering algorithms with large-scale data volume.

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 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight 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. Li, X., Huang, Z., Cai, X., et al.: Parallel and Distributed Visualization:Techniques and Applications. Defence industry publisher

    Google Scholar 

  2. Li, X., Sun, J., Qi, Z., Zhang, J.: A Modified Parallel Computation Model Based on Cluster. In: Laganá, A., Gavrilova, M.L., Kumar, V., Mun, Y., Tan, C.J.K., Gervasi, O. (eds.) ICCSA 2004. LNCS, vol. 3044, pp. 252–261. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  3. Sun, Z., Zhang, J., Sun, J.: A improved Splatting algorithm for volume rendering. Journal of Tianjin University 36(5) (September 2003)

    Google Scholar 

  4. Wilkinson, B., Allen, M.: Parallel Programming: Techniques and Applications Using Networked Workstations and Parallel Computers. Prentice Hall, Englewood Cliffs (1999)

    Google Scholar 

  5. Ibm.com/redbooks, Building a Linux HPC Cluster with xCAT

    Google Scholar 

  6. Ibm.com/redbooks, Preinstallation Planning

    Google Scholar 

  7. Geist, G.A., Beguelin, A., Dongorra, J., Jiang, W., Manchek, R., Sunderam, V.S.: PVM-Parallel Virtual Machine -A Users’ Guide and Tutorial for Networked Parallel Computing. MIT Press, Cambridge (1994)

    MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. IBM New Technology Center, Tianjin University, Tianjin, 300072, P.R.China

    Weifang Nie, Jizhou Sun, Jing Jin, Xiaotu Li, Jie Yang & Jiawan Zhang

Authors
  1. Weifang Nie
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jizhou Sun
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jing Jin
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Xiaotu Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jie Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Jiawan Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Mathematics and Computer Science, University of Perugia, via Vanvitelli, 1, I-06123, Perugia, Italy

    Osvaldo Gervasi

  2. Department of Computer Science, University of Calgary, 2500 University Drive N.W., T2N 1N4, Calgary, AB, Canada

    Marina L. Gavrilova

  3. William Norris Professor, Head of the Computer Science and Engineering, Department University of Minnesota, USA

    Vipin Kumar

  4. Department of Chemistry, University of Perugia, Via Elce di Sotto, 8, I-06123, Perugia, Italy

    Antonio Laganà

  5. Institute of High Performance Computing, IHCP, 1 Science Park Road, 01-01 The Capricorn, Singapore Science Park II, 117528, Singapore

    Heow Pueh Lee

  6. School of Computing, Soongsil University, Seoul, Korea

    Youngsong Mun

  7. Clayton School of IT, Monash University, 3800, Clayton, Australia

    David Taniar

  8. OptimaNumerics Ltd, Belfast, United Kingdom

    Chih Jeng Kenneth Tan

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Nie, W., Sun, J., Jin, J., Li, X., Yang, J., Zhang, J. (2005). A Dynamic Parallel Volume Rendering Computation Mode Based on Cluster. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2005. ICCSA 2005. Lecture Notes in Computer Science, vol 3482. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11424857_44

Download citation

  • DOI: https://doi.org/10.1007/11424857_44

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25862-9

  • Online ISBN: 978-3-540-32045-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation