Implementation of Massive Agent Model Using Repast HPC and GPU
Shinsaku Segawa, Shofuku Kin, Hidenori Kawamura, Keiji Suzuki
Agent Based Model (ABM) is efficient for analysis of various
social mechanisms. Recently, there are many studies on massive
agent model to explain more complex social phenomena.
Then, we aim for implementation of large scale simulation
model using Repast HPC toolkit, a platform for massive agent
model. In this article, we build "Schelling Segregation Model"
for spatial model using geospatial data provided
OpenStreetMap, an open source project creating a free editable
map. In this model, agents are located continuous space, not
grid in original. When an agent is "unhappy" and migrates to
new location, it costs agents some simulation time depending on
distance between old location and new one.
This article reports simulation results using Japanese cities and
verification result about execution time.