Laville G. auteur aut IRD Lang C. auteur aut IRD Herrmann B. auteur aut IRD Philippe L. auteur aut IRD Mazouzi K. auteur aut IRD Marilleau Nicolas auteur aut IRD text journalArticle eng text/pdf born digital access 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. specialized Multi-agent systems parallel computing GPGPU many-core 122 11 1 15-31 2015 1574-1702 https://www.documentation.ird.fr/hor/fdi:010068858 10.3233/mgs-150227 1574-1702 [F B010068858] https://www.documentation.ird.fr/hor/fdi:010068858 https://www.documentation.ird.fr/intranet/publi/2017/02-recup-esci/010068858.pdf Accès réservé (Intranet de l'IRD) IRD - Base Horizon / Pleins textes 2017-04-04 2017-08-23 fdi:010068858 fre