SciELO - Scientific Electronic Library Online

 
vol.17 número1Algoritmo de retropropagación a través de tiempo para el aprendizaje de redes neuronales recurrentes usando instancias de longitud variableSelección de características utilizando el paradigma de memoria asociativa y computación paralela índice de autoresíndice de materiabúsqueda de artículos
Home Pagelista alfabética de revistas  

Servicios Personalizados

Revista

Articulo

Indicadores

Links relacionados

  • No hay artículos similaresSimilares en SciELO

Compartir


Computación y Sistemas

versión On-line ISSN 2007-9737versión impresa ISSN 1405-5546

Resumen

DIAZ PANDO, Humberto et al. An Application of Fuzzy Logic for Hardware/Software Partitioning in Embedded Systems. Comp. y Sist. [online]. 2013, vol.17, n.1, pp.25-39. ISSN 2007-9737.

Hardware/Software partitioning (HSP) is a key task for embedded system co-design. The main goal of this task is to decide which components of an application are to be executed in a general purpose processor (software) and which ones, on a specific hardware, taking into account a set of restrictions expressed by metrics. In last years, several approaches have been proposed for solving the HSP problem, directed by metaheuristic algorithms. However, due to diversity of models and metrics used, the choice of the best suited algorithm is an open problem yet. This article presents the results of applying a fuzzy approach to the HSP problem. This approach is more flexible than many others due to the fact that it is possible to accept quite good solutions or to reject other ones which do not seem good. In this work we compare six metaheuristic algorithms: Random Search, Tabu Search, Simulated Annealing, Hill Climbing, Genetic Algorithm and Evolutionary Strategy. The presented model is aimed to simultaneously minimize the hardware area and the execution time. The obtained results show that Restart Hill Climbing is the best performing algorithm in most cases.

Palabras llave : Hardware/software co-design; hardware/software partitioning; metaheuristic algorithms.

        · resumen en Español     · texto en Inglés     · Inglés ( pdf )

 

Creative Commons License Todo el contenido de esta revista, excepto dónde está identificado, está bajo una Licencia Creative Commons