Behavioral Simulations in MapReduce

In many scientific domains, researchers are turning to large-scale behavioral simulations to better understand real-world phenomena. While there has been a great deal of work on simulation tools from the high-performance computing community, behavioral simulations remain challenging to program and automatically scale in parallel environments. In this paper we present BRACE (Big Red Agent-based Computation Engine), which extends the MapReduce framework to process these simulations efficiently across a cluster. We can leverage spatial locality to treat behavioral simulations as iterated spatial joins and greatly reduce the communication between nodes. In our experiments we achieve nearly linear scale-up on several realistic simulations. Though processing behavioral simulations in parallel as iterated spatial joins can be very efficient, it can be much simpler for the domain scientists to program the behavior of a single agent. Furthermore, many simulations include a considerable amount ...

• Type: Journal
• Year: 2010
• Where: CORR
• Authors: Guozhang Wang, Marcos Antonio Vaz Salles, Benjamin Sowell, Xun Wang, Tuan Cao, Alan J. Demers, Johannes Gehrke, Walker M. White
• Keywords: Behavioral Simulations, CORR 2010, Education, Large-scale Behavioral Simulations, Simulation