An adaptive genetic algorithm for dynamically reconfigurable modules allocation

  • Vincenzo Rana
  • Chiara Sandionigi
  • Marco Santambrogio
  • Donatella Sciuto
Part of the IFIP International Federation for Information Processing book series (IFIPAICT, volume 291)

This paper aims at defining an adaptive genetic algorithm tailored for the allocation of dynamically reconfigurable modules. This algorithm can be tuned at run-time with a set of parameters to best characterize different architectural scenarios (i.e., single device or multi- FPGAs characterized by several kinds of communication infrastructures) and to adapt the performance of the algorithm itself to the scenario in which it has to operate. The proposed approach has been validated on a large set of meaningful combinations of parameters (i.e. changing the mutation or the crossover probability), in order to demonstrate the possibility of performing either a fast or an accurate allocation phase.


Genetic Algorithm Selection Size Initial Population Size Adaptive Genetic Algorithm Free Slot 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag US 2009

Authors and Affiliations

  1. 1.Politecnico di MilanoDipartimento di Elettronica e Informazione MilanoItaly

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