Optimization of Total Energy and Reduction of Computer Resources in Some Applications of the Ab-initio LMTO Package
Kamieniarz Grzegorz 1,2*, Sobczak Paweł 1
1Institute of Physics, Adam Mickiewicz University, Poznań, Poland
2Max Planck Institute for the Physics of Complex System, Dresden, Germany
*e-mail: gjk@amu.edu.pl
Received:
Rec. December 11, 2006
DOI: 10.12921/cmst.2007.13.01.13-22
OAI: oai:lib.psnc.pl:627
Abstract:
The computer resources needed to run the TB LMTO code have been reduced using a genetic algorithm in computations of the total energy requiring the interactive user-dependent mode. A computer program has been developed to search for the total energy minima and perform calculations in the background. The number of runs and output files is determined by the size of population and not by the number of scans of the configuration space.
Key words:
computer resources optimization, LMTO ab-initio package, solid-state physics simulations
References:
[1] G. Krier, O. Jepsen, A. Burkhardt and O. K. Andersen, The TB – LMTO – ASA program, Max – Planck – Institut für Festkörperforschung Heisenbergstr. 1, D-70569 Stuttgart, Federal Republic of Germany.
[2] J. H. Holland, Adaptation in natural and artificial systems: An introductory analysis with applications to biology, control, and artificial intelligence, University of Michigan Press, Ann Arbor 1975.
[3] D. E. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley, Publishing Company, Inc., Massachusetts, 1989.
[4] D. E. Goldberg, The Design of Innovation: Lessons from and for Competent Genetic Algorithms, Kluwer Academic Publishers, 2002.
[5] C. W. Ahn and R. S. Ramakrishna, A Genetic Algorithm for Shortest Path Routing Problem and the Sizing of Populations, IEEE Transactions on Evolutionary Computation 6(6) (2002).
[6] R. Wyrzykowski, J. Dongarra, M. Paprzycki and J. Waśniewski, (Eds.), Parallel Processing and Applied Mathematics, 5th International Conference, PPAM 2003 Częstochowa, Poland, September 2003 Revised Papers, Springer LNCS 3019.
[7] A. Ayuela, J. Enkovaara and R. M. Nieminen, Ab initio study of tetragonal variants in Ni2MnGa alloy, J. Phys.: Condens. Matter 14, 5325-5336 (2002).
The computer resources needed to run the TB LMTO code have been reduced using a genetic algorithm in computations of the total energy requiring the interactive user-dependent mode. A computer program has been developed to search for the total energy minima and perform calculations in the background. The number of runs and output files is determined by the size of population and not by the number of scans of the configuration space.
Key words:
computer resources optimization, LMTO ab-initio package, solid-state physics simulations
References:
[1] G. Krier, O. Jepsen, A. Burkhardt and O. K. Andersen, The TB – LMTO – ASA program, Max – Planck – Institut für Festkörperforschung Heisenbergstr. 1, D-70569 Stuttgart, Federal Republic of Germany.
[2] J. H. Holland, Adaptation in natural and artificial systems: An introductory analysis with applications to biology, control, and artificial intelligence, University of Michigan Press, Ann Arbor 1975.
[3] D. E. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley, Publishing Company, Inc., Massachusetts, 1989.
[4] D. E. Goldberg, The Design of Innovation: Lessons from and for Competent Genetic Algorithms, Kluwer Academic Publishers, 2002.
[5] C. W. Ahn and R. S. Ramakrishna, A Genetic Algorithm for Shortest Path Routing Problem and the Sizing of Populations, IEEE Transactions on Evolutionary Computation 6(6) (2002).
[6] R. Wyrzykowski, J. Dongarra, M. Paprzycki and J. Waśniewski, (Eds.), Parallel Processing and Applied Mathematics, 5th International Conference, PPAM 2003 Częstochowa, Poland, September 2003 Revised Papers, Springer LNCS 3019.
[7] A. Ayuela, J. Enkovaara and R. M. Nieminen, Ab initio study of tetragonal variants in Ni2MnGa alloy, J. Phys.: Condens. Matter 14, 5325-5336 (2002).
