%0 Journal Article
%9 ACL : Articles dans des revues avec comité de lecture répertoriées par l'AERES
%A Laville, G.
%A Mazouzi, K.
%A Lang, C.
%A Marilleau, Nicolas
%A Herrmann, B.
%A Philippe, L.
%T MCMAS : a toolkit to benefit from many-core architecure in agent-based simulation
%B Euro-Par 2013 : parallel processing workshops : BigDataCloud, DIHC, FedICI, HeteroPar, HiBB, LSDVE, MHPC, OMHI, PADABS, PROPER, Resilience, ROME, and UCHPC 2013 : revised selected papers
%C Berlin
%D 2014
%E Mey, D.A.
%E Alexander, M.
%E Bientinesi, P.
%E Cannataro, M.
%E Clauss, C.
%E Costan, A.
%E Kecskemet, G.
%E Morin, C.
%E Ricci, L.
%E Sahuquillo, J.
%E Schulz, M.
%E Scarano, V.
%E Scott, S.L.
%E Weidendorfer, J.
%L fdi:010072197
%G ENG
%I Springer
%@ 978-3-642-54419-4
%M ISI:000350859500062
%N 8374
%P 544-554
%R 10.1007/978-3-642-54420-0_53
%U https://www.documentation.ird.fr/hor/fdi:010072197
%> https://www.documentation.ird.fr/intranet/publi/depot/2018-02-09/010072197.pdf
%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. This toolkit promotes few famous algorithms (diffusion, path-finding, population dynamics) which are ready to be used in an Agent Based Model. For other needs, MCMAS is based on a flexible architecture and can easily be enriched by new algorithms thanks to development features. The use of the library is illustrated with two models and their performance analysis.
%S Lecture Notes in Computer Science
%B Euro-Par 2013 : International Conference on Parallel Computing
%8 2013/08/26-27
%$ 122 ; 020