Skip to main content

A New Scalable Parallel Method for Molecular Dynamics Based on Cell-Block Data Structure

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3358))

Abstract

A scalable parallel algorithm especially for large-scale three dimensional simulations with seriously non-uniform particles distributions is presented. In particular, based on cell-block data structures, this algorithm uses Hilbert space filling curve to convert three-dimensional domain decomposition for load distribution across processors into one-dimensional load balancing problems for which measurement-based multilevel averaging weights(MAW) method can be applied successfully. Against inverse space-filling partitioning(ISP), MAW redistributes blocks by monitoring change of total load in each processor. Numerical experimental results have shown that MAW is superior to ISP in rendering balanced load for large-scale multi-medium MD simulation in high temperature and high pressure physics. Excellent scalability was demonstrated, with a speedup larger than 200 with 240 processors of one MPP. The largest run with 1.1 × 109 particles on 500 processors took 80 seconds per time step.

Research supported by Chinese NSF( 60273030), Chinese 863 program(2002AA104570) and CAEP Funds.

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

Buying options

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

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Zeyao, M., Jinglin, Z.: Dynamic Load Balancing for Short-Range Parallel Molecular Dynamics Simulations. Intern. J. Computer Math. 79, 165–172 (2002)

    Article  MATH  Google Scholar 

  2. Hayashi, R., Horiguchi, S.: Efficiency of Dynamic Load Balancing Based on Permanent Cells for Parallel Molecular Dynamics Simulation. In: Proc. Of IPDPS, Cancun, Mexio, pp. 85–92 (2000)

    Google Scholar 

  3. Pilkington, R., Baden, B.: Dynamic Partitioning of Non-Uniform Structured Workloads with Spacefilling Curves. IEEE Trans. on Parallel and Distributed Systems 7, 288–299 (1996)

    Article  Google Scholar 

  4. Kale, L., Skeel, R., Bhandarkar, M.: NAMD2: Greater Scalability for Parallel Molecular Dynamics. J. Computational Physics 151, 283–312 (1999)

    Article  MATH  Google Scholar 

  5. Sagan, H.: Space-Filling Curves. Springer, New York (1994)

    MATH  Google Scholar 

  6. http://www.cs.sandia.gov/Zoltan/ug_html/ug_alg_hsfc.html

  7. Zeyao, M., Baolin, Z.: Multilayer Averaged Weight Method for Dynamic Load Imbalance Problems. Intern. J. Computer Math. 76, 463–477 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  8. Plimpton, S.: Fast Parallel Algorithms for Short-range Molecular Dynamics. J. of Computational Physics 117, 1–19 (1995)

    Article  MATH  Google Scholar 

  9. Stadler, J., Mikulla, R., Trebin, H.R.: IMD: A Software Package for Molecular Dynamics Studies on Parallel Computes. Intern. J. Modern Physics 8, 1131–1140 (1997)

    Article  Google Scholar 

  10. Roth, J., Gahler, F., Trebin, H.: A Molecular Dynamics Run with 5,180,116,000 Particles. Int. J. Modern Physics C 11, 317–322 (2000)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2004 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Cao, X., Mo, Z. (2004). A New Scalable Parallel Method for Molecular Dynamics Based on Cell-Block Data Structure. In: Cao, J., Yang, L.T., Guo, M., Lau, F. (eds) Parallel and Distributed Processing and Applications. ISPA 2004. Lecture Notes in Computer Science, vol 3358. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30566-8_88

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-30566-8_88

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-24128-7

  • Online ISBN: 978-3-540-30566-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics