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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, 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”