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

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, [email protected]

  • 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”


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