%0 Journal Article
%9 ACL : Articles dans des revues avec comité de lecture répertoriées par l'AERES
%A Laville, G.
%A Lang, C.
%A Herrmann, B.
%A Philippe, L.
%A Mazouzi, K.
%A Marilleau, Nicolas
%T MCMAS : a toolkit for developing agent-based simulations on many-core architectures
%D 2015
%L fdi:010068858
%G ENG
%J Multiagent and Grid Systems
%@ 1574-1702
%K Multi-agent systems ; parallel computing ; GPGPU ; many-core
%M ISI:000359189600002
%N 1
%P 15-31
%R 10.3233/mgs-150227
%U https://www.documentation.ird.fr/hor/fdi:010068858
%> https://www.documentation.ird.fr/intranet/publi/2017/02-recup-esci/010068858.pdf
%V 11
%W Horizon (IRD)
%X Multi-agent models and simulations are used to describe complex systems in domains such as biological, geographical or ecological sciences. The increasing model complexity results in a growing need for computing resources and motivates the use of new architectures such as multi-cores and many-cores. Using them efficiently however remains a challenge in many models as it requires adaptations tailored to each program, using low-level code and libraries. In this paper we present MCMAS a generic toolkit allowing an efficient use of many-core architectures through already defined data structures and kernels. The toolkit provides few famous algorithms as diffusion, path-finding or population dynamics that are frequently used in an agent based models. For further needs, MCMAS is based on a flexible architecture that can easily be enriched by new algorithms thanks to development features. The use of the library is illustrated with three models and their performance analysis.
%$ 122