A high performance agent based modelling framework on graphics card hardware with CUDA

Authors:
Paul Richmond;Simon Coakley;Daniela M. Romano
Affiliations:
University of Sheffield, UK;University of Sheffield, UK;University of Sheffield, UK
Venue:
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
Year:
2009

Citing 1
Cited 5

X-machines as a basis for dynamic system specification

Software Engineering Journal

Research Article: Implications of the Turing completeness of reaction-diffusion models, informed by GPGPU simulations on an XBox 360: Cardiac arrhythmias, re-entry and the Halting problem

Computational Biology and Chemistry
FLAME: simulating large populations of agents on parallel hardware architectures

Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
BehaveRT: a GPU-based library for autonomous characters

MIG'10 Proceedings of the Third international conference on Motion in games
GPU implementation and performance analysis of reactive agents having division and mobility capacities

Multiagent and Grid Systems
A distributed visualization system for crowd simulations

Integrated Computer-Aided Engineering

Quantified Score

Hi-index	0.00

Visualization

Abstract

We present an efficient implementation of a high performance parallel framework for Agent Based Modelling (ABM), exploiting the parallel architecture of the Graphics Processing Unit (GPU). It provides a mapping between formal agent specifications, with C based scripting, and optimised NVIDIA Compute Unified Device Architecture (CUDA) code. The mapping of agent data structures and agent communication is described, and our work is evaluated through a number of simple interacting agent examples. In contrast with an alternative, single machine CPU implementation, a speedup of up to 250 times is reported.