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| Titel: |
MCMAS: A toolkit for developing agent-based simulations on many-core architectures |
| Auteur: |
Laville, Guillaume Lang, Christophe Herrmann, Bénédicte Philippe, Laurent Mazouzi, Kamel Marilleau, Nicolas |
| Verschenen in: |
Multiagent and grid systems |
| Paginering: | Jaargang 11 (2015) nr. 1 pagina's 15-31 |
| Jaar: |
2015-04-16 |
| Inhoud: |
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. |
| Uitgever: |
IOS Press |
| Bronbestand: |
Elektronische Wetenschappelijke Tijdschriften |
Details van artikel 56 van 88 gevonden artikelen
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