Evaluation of a master-slave parallel evolutionary algorithm applied to artificial intelligence for games in the xeon-phi many-core platform
Evolutionary algorithms are non-deterministic metaheuristic methods that emulate the evolution of species in nature to solve optimization, search, and learning problems. This article presents a parallel implementation of evolutionary algorithms on Xeon Phi for developing an artificial intelligence t...
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| Acceso en línea: | https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_18650929_v697_n_p161_Leopold http://hdl.handle.net/20.500.12110/paper_18650929_v697_n_p161_Leopold |
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paper:paper_18650929_v697_n_p161_Leopold2025-07-30T19:05:17Z Evaluation of a master-slave parallel evolutionary algorithm applied to artificial intelligence for games in the xeon-phi many-core platform Mocskos, Esteban Eduardo Artificial intelligence Evolutionary algorithms Xeon Phi Artificial intelligence Computer architecture Optimization Meta-heuristic methods Micro-benchmarking Parallel evolutionary algorithms Parallel implementations Performance analysis Resource utilizations Technical documentations Xeon Phi Evolutionary algorithms Evolutionary algorithms are non-deterministic metaheuristic methods that emulate the evolution of species in nature to solve optimization, search, and learning problems. This article presents a parallel implementation of evolutionary algorithms on Xeon Phi for developing an artificial intelligence to play the NES Pinball game. The proposed parallel implementation offloads the execution of the fitness function evaluation to Xeon Phi. Multiple evolution schemes are studied to get the most efficient resource utilization. A micro-benchmarking of the Xeon Phi coprocessor is performed to verify the existing technical documentation and obtain detail knowledge of its behavior. Finally, a performance analysis of the proposed parallel evolutionary algorithm is presented, focusing on the characteristics of the evaluated platform. © Springer International Publishing AG 2017. Fil:Mocskos, E. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. 2017 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_18650929_v697_n_p161_Leopold http://hdl.handle.net/20.500.12110/paper_18650929_v697_n_p161_Leopold |
| institution |
Universidad de Buenos Aires |
| institution_str |
I-28 |
| repository_str |
R-134 |
| collection |
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) |
| topic |
Artificial intelligence Evolutionary algorithms Xeon Phi Artificial intelligence Computer architecture Optimization Meta-heuristic methods Micro-benchmarking Parallel evolutionary algorithms Parallel implementations Performance analysis Resource utilizations Technical documentations Xeon Phi Evolutionary algorithms |
| spellingShingle |
Artificial intelligence Evolutionary algorithms Xeon Phi Artificial intelligence Computer architecture Optimization Meta-heuristic methods Micro-benchmarking Parallel evolutionary algorithms Parallel implementations Performance analysis Resource utilizations Technical documentations Xeon Phi Evolutionary algorithms Mocskos, Esteban Eduardo Evaluation of a master-slave parallel evolutionary algorithm applied to artificial intelligence for games in the xeon-phi many-core platform |
| topic_facet |
Artificial intelligence Evolutionary algorithms Xeon Phi Artificial intelligence Computer architecture Optimization Meta-heuristic methods Micro-benchmarking Parallel evolutionary algorithms Parallel implementations Performance analysis Resource utilizations Technical documentations Xeon Phi Evolutionary algorithms |
| description |
Evolutionary algorithms are non-deterministic metaheuristic methods that emulate the evolution of species in nature to solve optimization, search, and learning problems. This article presents a parallel implementation of evolutionary algorithms on Xeon Phi for developing an artificial intelligence to play the NES Pinball game. The proposed parallel implementation offloads the execution of the fitness function evaluation to Xeon Phi. Multiple evolution schemes are studied to get the most efficient resource utilization. A micro-benchmarking of the Xeon Phi coprocessor is performed to verify the existing technical documentation and obtain detail knowledge of its behavior. Finally, a performance analysis of the proposed parallel evolutionary algorithm is presented, focusing on the characteristics of the evaluated platform. © Springer International Publishing AG 2017. |
| author |
Mocskos, Esteban Eduardo |
| author_facet |
Mocskos, Esteban Eduardo |
| author_sort |
Mocskos, Esteban Eduardo |
| title |
Evaluation of a master-slave parallel evolutionary algorithm applied to artificial intelligence for games in the xeon-phi many-core platform |
| title_short |
Evaluation of a master-slave parallel evolutionary algorithm applied to artificial intelligence for games in the xeon-phi many-core platform |
| title_full |
Evaluation of a master-slave parallel evolutionary algorithm applied to artificial intelligence for games in the xeon-phi many-core platform |
| title_fullStr |
Evaluation of a master-slave parallel evolutionary algorithm applied to artificial intelligence for games in the xeon-phi many-core platform |
| title_full_unstemmed |
Evaluation of a master-slave parallel evolutionary algorithm applied to artificial intelligence for games in the xeon-phi many-core platform |
| title_sort |
evaluation of a master-slave parallel evolutionary algorithm applied to artificial intelligence for games in the xeon-phi many-core platform |
| publishDate |
2017 |
| url |
https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_18650929_v697_n_p161_Leopold http://hdl.handle.net/20.500.12110/paper_18650929_v697_n_p161_Leopold |
| work_keys_str_mv |
AT mocskosestebaneduardo evaluationofamasterslaveparallelevolutionaryalgorithmappliedtoartificialintelligenceforgamesinthexeonphimanycoreplatform |
| _version_ |
1840326033813798912 |