Large-Scale Social Simulation, Dealing with Complexity Challenges in High Performance Environments

Author:

Montañola-Sales C.1,Rubio-Campillo X.2,Casanovas-Garcia J.1,Cela-Espín J. M.1,Kaplan-Marcusán A.3

Affiliation:

1. Universitat Politècnica de Catalunya – Barcelona Supercomputing Center, Spain

2. Barcelona Supercomputing Center, Spain

3. Universitat Autònoma de Barcelona, Spain

Abstract

Advances on information technology in the past decades have provided new tools to assist scientists in the study of social and natural phenomena. Agent-based modeling techniques have flourished recently, encouraging the introduction of computer simulations to examine behavioral patterns in complex human and biological systems. Real-world social dynamics are very complex, containing billions of interacting individuals and an important amount of data (both spatial and social). Dealing with large-scale agent-based models is not an easy task and encounters several challenges. The design of strategies to overcome these challenges represents an opportunity for high performance parallel and distributed implementation. This chapter examines the most relevant aspects to deal with large-scale agent-based simulations in social sciences and revises the developments to confront technological issues.

Publisher

IGI Global

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3. Chandak, A., & Browne, J. C. (1983). Vectorization of discrete event simulation. In Proceedings of the 1983 International Conference on Parallel Processing (pp. 359).

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1. Exploring Emergence within Social Systems with Agent Based Models;Interdisciplinary Applications of Agent-Based Social Simulation and Modeling;2014

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