Using MOCCA Component Environment for Modeling of Gold Clusters
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Using MOCCA Component Environment for Modeling of Gold Clusters. Maciej Malawski 1 , Micha ł Placek 3 , Marian Bubak 1,2 1 Institute of Computer Science AGH, Mickiewicza 30, 30-059 Kraków, Poland 2 Academic Computer Centre CYFRONET, Nawojki 11, 30-950 Kraków, Poland

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Using mocca component environment for modeling of gold clusters

Using MOCCA Component Environment for Modeling of Gold Clusters

Maciej Malawski1, Michał Placek3, Marian Bubak1,2

1Institute of Computer Science AGH, Mickiewicza 30, 30-059 Kraków, Poland

2Academic Computer Centre CYFRONET, Nawojki 11, 30-950 Kraków, Poland

3Faculty of Physics and Applied Computer Science AGH

Al. Mickiewicza 30, 30-059 Krakow, Poland

{bubak,malawski}@agh.edu.pl, placek@fatcat.ftj.agh.edu.pl

  • Clusters of atoms

    • Very interesting forms between isolated atoms or molecules and solid state

    • Important for the technology of constructing nanoscale devices.

  • Modeling of clusters

    • Several energy minimization methods such as MDSA or L-BFGS,

    • Choosing an empirical potential

    • Highly compute-intensive

    • The optimal result depends on the number of possible iterations and initial configurations for each simulation run.

  • MOCCA

    • Common Component Architecture compliant distributed framework

    • Based on H2O resource sharing platform

  • Features:

    • Facilitated deployment - easy mechanisms for creation of components on distributed shared resources - using H2O;

    • Efficient communication - both for distributed and local components – using RMIX;

    • Flexible - allow flexible configuration of components and various application scenarios;

    • Support native components, i.e. components written in non-Java programming languages and compiled for specific architecture – on-going work

From sequential code to distributed components

Component application distributed on multiple H2O kernels

  • Advantages of component-based approach

    • Flexibility of composition: from local to distributed configurations

    • Additional minimization methods pluggable as components

    • Multiple inputs and outputs possible: text file or GUI (future work)

  • Experiences with distributed environment

    • Multiple annealing components running over many machines

    • Support for multiple ports and connections in MOCCA

  • Future improvements

    • From static do dynamic deployment configuration

    • Tests in Peer-to-Peer environment

    • Application performance tuning

    • Native components

Example application deployment scenario

Performance tests on a PC cluster

  • Athlon MP 1800MHz

  • 8 CPUs

  • Fast Ethernet

  • SUN Java J2SE 1.4.2

Example results

References

  • European Research Network on Foundations, Software Infrastructures and Applications for Large Scale Distributed, GRID and Peer-to-Peer Technologies. http://www.coregrid.net/

  • M. Malawski, D. Kurzyniec, V. Sunderam, MOCCA - Towards a Distributed CCA Framework for Metacomputing, Proceedings of 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Joint Workshop - HIPS-HPGC, April 4-8, 2005, Denver, Colorado, USA, IEEE Computer Society Press, 2005, pp. 174a.

  • N.T. Wilson and R.L. Johnston: Modeling Gold clusters with an Empirical Many-body Potential, Eur. Phys. J. D 12, 161-169 (2000)

  • CCA forum. The Common Component Architecture (CCA) Forum home page, 2005, http://www.cca-forum.org/.

http://www.icsr.agh.edu.pl/mambo/mocca

This research is partly funded by the European Commission Project „CoreGRID”