The application of graph decomposition to development of large scale agent-based economic models

In this work we describe the application of the graph decomposition algorithms for the development of a scalable high-performance agent-based model of population of Russia described in terms of demography, migration and transport flows. The simulated system consists of agents representing individuals and sets of links to other agents, which represent the social interactions of individual. Individual agents in the model participate in several independent processes, for which different sets of social links is important such as family and neighbors. To perform a load balancing of agents between cluster computer nodes the METIS graph decomposition algorithm was used. These algorithms allow to split the graph of agents and links into parts of similar size with least possible number of links between them. A number of numerical experiments was carried out for test model to estimate the influence of the parameters of the model on scalability.