{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,3,31]],"date-time":"2022-03-31T18:17:44Z","timestamp":1648750664859},"reference-count":13,"publisher":"World Scientific Pub Co Pte Lt","issue":"02","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Model. Simul. Sci. Comput."],"published-print":{"date-parts":[[2013,6]]},"abstract":"<jats:p> Large-scale artificial societies with millions or billions of agents call for high-performance parallel simulation. Prevailing supercomputers with thousands of CPUs and GPUs make it possible to carry out such simulation. The key is to distribute large-scale agents to massive cores of CPUs and GPUs properly for parallel computing with efficient communication and synchronization. For simplicity and efficiency, a modified discrete event system specification (DEVS) is proposed for large-scale artificial society modeling and parallelism is exploited in agent models because similar agents usually share similar behaviors. Through phased synchronization, a two-tier parallel simulation engine is designed with support of MPI and OpenCL where GPU is used as coprocessor. One-sided communication is used for reflection of remote simulation objects and message passing between processes. A general kernel function prototype is elaborately designed and conditionally compiled for execution on both CPU and GPU. An artificial society for epidemic study is used to test the performance on a supercomputer with 1024 CPU cores and 1792 GPU cores. The speedup reaches 3512 for even 2 billion agents with GPU acceleration which is far over 701 when only CPUs are used. It turns out feasible for parallel simulation of large-scale artificial society with GPU as coprocessor. <\/jats:p>","DOI":"10.1142\/s1793962313500050","type":"journal-article","created":{"date-parts":[[2013,1,7]],"date-time":"2013-01-07T02:40:09Z","timestamp":1357526409000},"page":"1350005","source":"Crossref","is-referenced-by-count":1,"title":["PARALLEL SIMULATION OF LARGE-SCALE ARTIFICIAL SOCIETY WITH GPU AS COPROCESSOR"],"prefix":"10.1142","volume":"04","author":[{"given":"GANG","family":"GUO","sequence":"first","affiliation":[{"name":"Research Center of Computational Experiments and Parallel System Technology, National University of Defense Technology, Changsha, Hunan, China 410073, P. R. China"}]},{"given":"BIN","family":"CHEN","sequence":"additional","affiliation":[{"name":"Research Center of Computational Experiments and Parallel System Technology, National University of Defense Technology, Changsha, Hunan, China 410073, P. R. China"}]},{"given":"XIAOGANG","family":"QIU","sequence":"additional","affiliation":[{"name":"Research Center of Computational Experiments and Parallel System Technology, National University of Defense Technology, Changsha, Hunan, China 410073, P. R. China"}]}],"member":"219","published-online":{"date-parts":[[2013,6,20]]},"reference":[{"key":"rf1","first-page":"25","volume":"1","author":"Wang F. Y.","year":"2004","journal-title":"Complex Syst. Complexity Sci."},{"key":"rf2","doi-asserted-by":"publisher","DOI":"10.1109\/MIS.2007.4338496"},{"key":"rf3","doi-asserted-by":"publisher","DOI":"10.7551\/mitpress\/3374.001.0001"},{"key":"rf4","first-page":"20","volume":"22","author":"Parker J.","year":"2011","journal-title":"ACM Trans. Model. Comput. 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