Evolutionary algorithms for the mapping of pipelined applications onto heterogeneous embedded systems

  • Authors:

  • Marco Branca;Lorenzo Camerini;Fabrizio Ferrandi;Pier Luca Lanzi;Christian Pilato;Donatella Sciuto;Antonino Tumeo

  • Affiliations:

  • Politecnico di Milano, Milano, Italy;Politecnico di Milano, Milano, Italy;Politecnico di Milano, Milano, Italy;Politecnico di Milano, Milano, Italy;Politenico di Milano, Milano, Italy;Politecnico di Milano, Milano, Italy;Politecnico di Milano, Milano, Italy

  • Venue:
  • Proceedings of the 11th Annual conference on Genetic and evolutionary computation
  • Year:
  • 2009

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Abstract

In this paper, we compare four algorithms for the mapping of pipelined applications on a heterogeneous multiprocessor platform implemented using Field Programmable Gate Arrays (FPGAs) with customizable processors. Initially, we describe the framework and the model of pipelined application we adopted. Then, we focus on the problem of mapping a set of pipelined applications onto a heterogeneous multiprocessor platform and consider four search algorithms: Tabu Search, Simulated Annealing, Genetic Algorithms, and the Bayesian Optimization Algorithm. We compare the performance of these four algorithms on a set of synthetic problems and on two real-world applications (the JPEG image encoding and the ADPCM sound encoding). Our results show that on our framework the Bayesian Optimization Algorithm outperforms all the other three methods for the mapping of pipelined applications.