Application of Supercomputer Technologies for Simulation of Socio-Economic Systems

Vladimir V. Okrepilov, Valery L. Makarov, Alber R. Bakhtizin, Svetlana N. Kuzmina

Abstract


To date, an extensive experience has been accumulated in investigation of problems related to quality, assessment of management systems, modeling of economic system sustainability.

The studies performed have created a basis for formation of a new research area — Economics of Quality. Its tools allow to use opportunities of model simulation for construction of the mathematical models adequately reflecting the role of quality in natural, technical, social regularities of functioning of the complex socioeconomic systems.

Extensive application and development of models, and also system modeling with use of supercomputer technologies, on our deep belief, will bring the conducted researches of social and economic systems to essentially new level. Moreover, the current scientific research makes a significant contribution to model simulation of multi-agent social systems and that isn’t less important, it belongs to the priority areas in development of science and technology in our country.

This article is devoted to the questions of supercomputer technologies application in public sciences, first of all, — regarding technical realization of the large-scale agent-focused models (AFM). The essence of this tool is that owing to increase in power of computers it became possible to describe the behavior of many separate fragments of a difficult system, as social and economic systems represent. The article also deals with the experience of foreign scientists and practicians in launching the AFM on supercomputers, and also the example of AFM developed in CEMI RAS, stages and methods of effective calculating kernel display of multi-agent system on architecture of a modern supercomputer will be analyzed.

The experiments on the basis of model simulation on forecasting the population of St. Petersburg according to three scenarios as one of the major factors influencing the development of social and economic system and quality of life of the population are presented in the conclusion.


Keywords


Agent-based model; demographic projection; model simulation; quality of life; quality management methods; socioeconomic system; supercomputer technologies; scenario estimates; economics of quality

Full Text:

PDF

References


Okrepilov V. V. (2013). Ekonomika kachestva kak metodologicheskaya osnova upravleniya regionami [Economy of ualityas methodological basis of management of regions]. Ekonomika i upravleniya [Economics and management], 1 (87), 8-14.

Deissenberg, C., Hoog, S. van der & Herbert, D. (2008, June). EURACE: A Massively Parallel Agent-Based Model of the European Economy. Document de Travail, 39.

Roberts, D. J., Simoni, D. A. & Eubank, S. (2007). A National Scale Microsimulation of Disease Outbreaks. RTI International. Research Triangle Park. Blacksburg: Virginia Bioinformatics Institute.

Bisset, K., Chen, J., Feng, X., Kumar, V. S. A. & Marathe, M. (2009). EpiFast: A fast algorithm for large scale realistic epidemic simulations on distributed memory systems. Yorktown Heights, New York; 2009:430–439. Proceedings of 23rd ACM International Conference on Supercomputing (ICS’09).

Epstein, J. M. (2009, August). Modeling to Contain Pandemics. Nature, volume 460, 687.

Collier, N. (2012, February 23). Repast HPC Manual. Available at: http://repast.sourceforge.net (date of access: 2013, May).

Keith, R. B., Jiangzhuo, C., Xizhou, F., Kumar, A. V. S. & Madhav, V. M. (2009). EpiFast: A Fast Algorithm for Large Scale Realistic Epidemic Simulations on Distributed Memory Systems ICS’09. June 8–12. N.Y.: Yorktown Heights.

Ambrosiano, N. (2006). Avian Flu Modeled on Supercomputer. Los Alamos National Laboratory NewsLetter, 7, 8, 32.

Makarov, V. L., Bakhtizin, A. R., Vasenin, V. A., Roganov, V. A. & Trifonov I. A. (2011). Sredstva superkompyuternykh sistem dlya raboty s agent-orientirovannymi modelyami [Services of supercomputer systems for work with agent-focused models], 3.

Babkin, A. V. & Shamin, L. K. (2008). Analiz primeneniya metodologicheskikh podkhodov k upravleniyu ekonomicheskimi sistemami [The methodological approache application analysis to economic system management]. Nauchno-tekhnicheskie vedomosti SPbGU. Ekonomicheskie nauki [Scientific and Technical Journal of Peter the Great St. Petersburg Polytechnical University. Economic Sciences], 1(53), 18-22.

Zusev, G. Yu. & Plotnikov, V. A. (2011). Sotsialnyye zakonomernosti i rol cheloveka v sovremennom ekonomicheskom razvitii [Social regularities and role of himan being in modern economic development]. Nauchno-tekhnicheskie vedomosti Sankt-Peterburgskogo gosudarstvennogo politekhnicheskogo universiteta [Scientific and Technical Journal of Peter the Great St. Petersburg Polytechnical University. Economic Sciences], 2, 119, 22-26.

Gnevko, V. (2012). Municipalities — roots of democracy and economics. USA: Society and Science press, 295.

Epstein, J. M. & Axtell, R. L. (1996). Growing Artificial Societies: Social Science from the Bottom Up. Ch. V. Cambridge, Massachusetts: MIT Press.

Parker, J. (2007). A Flexible, Large-Scale, Distributed Agent Based Epidemic Model. Center on Social and EconomicDynamics. Working Paper, 52, 25.

Lynar, T. M., Herbert, R. D. & Chivers, W. J. (2009). Implementing an Agent Based Auction Model on a Cluster of Reused Workstations. International J. of Computer Applications in Technology, 34, 4, 13-24.




DOI: https://doi.org/10.15826/recon.2015.2.016

Copyright (c) 2018 Vladimir V. Okrepilov, Valery L. Makarov, Alber R. Bakhtizin, Svetlana N. Kuzmina

© R-Economy, ISSN 2412-0731