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Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10495/9986
Título : Mapping and Scheduling in Heterogeneous NoC through Population-Based Incremental Learning
Autor : Bolaños Martínez, Freddy
Aedo Cobo, José Edinson
Rivera Vélez, Fredy Alexander
Bagherzadeh, Nader
Palabras clave : Aprendizaje Incremental Basado en la Población
Diseño con ayuda de computador
Multiprocesador
Computer-aided Design
Multiprocessors
Fecha de publicación : 2012
Editorial : Graz University of Technology, Institut für Informationssysteme und Computer Medien (IICM)
Citación : Bolanos, F., Aedo, J.E., Rivera, F., & Bagherzadeh, N. (2012). Mapping and scheduling in heterogeneous NOC through population-based incremental learning. Journal of Universal Computer Science, 18 (7), 901-916.
Abstract : Network-on-Chip (NoC) is a growing and promising communication paradigm for Multiprocessor-System-On-Chip (MPSoC) design, because of its scalability and performance features. In designing such systems, mapping and scheduling are becoming critical stages, because of the increase of both size of the network and application’s complexity. Some reported solutions solve each issue independently. However, a conjoint approach for solving mapping and scheduling allows to take into account both computation and communication objectives simultaneously. This paper shows a mapping and scheduling solution, which is based on a Population-Based Incremental Learning (PBIL) algorithm. The simulation results suggest that our PBIL approach is able to find optimal mapping and scheduling, in a multi-objective fashion. A 2-D heterogeneous mesh was used as target architecture for implementation, although the PBIL representation is suited to deal with more complex architectures, such as 3-D meshes.
Grupo de INV. : Sistemas Embebidos e Inteligencia Computacional (SISTEMIC)
URI : http://hdl.handle.net/10495/9986
ISSN : 0948695x
09486968 E
Aparece en las colecciones: CIA (Centro de Investigaciones Ambientales y de Ingeniería)

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