Title: IP assignment for efficient NoC-based system design using multi-objective particle swarm optimisation

Authors: Maamar Bougherara; Nadia Nedjah; Luiza De Macedo Mourelle; Rym Rahmoun; Amel Sadok; Djamel Bennouar

Addresses: Computer, Mathematics, and Physics for Agriculture and Forests Laboratory, LIMPAF, Bouira University, Rue Drissi Yahia, Bouira, Algeria ' Postgraduate Program in Electronics Engineering, State University of Rio de Janeiro University, Rua São Francisco Xavier, 524, sala 5145-F Maracanã, Rio de Janeiro, RJ, CEP 20550-900, Brazil ' Postgraduate Program in Electronics Engineering, State University of Rio de Janeiro University, Rua São Francisco Xavier, 524, sala 5145-F Maracanã, Rio de Janeiro, RJ, CEP 20550-900, Brazil ' Ecole Normale Supérieure de Kouba, B.P N° 92 16308 Vieux-Kouba Algeries, Algeria ' Ecole Normale Supérieure de Kouba, B.P N° 92 16308 Vieux-Kouba Algeries, Algeria ' Computer, Mathematics, and Physics for Agriculture and Forests Laboratory, LIMPAF, Bouira University, Rue Drissi Yahia, Bouira, Algeria

Abstract: Network-on-chip (NoC) is considered the next generation of communication in embedded system. In this case, an application is implemented by a set of collaborative intellectual propriety blocks (IPs). The selection of the most suited block from a library of IPs is an NP-complete problem. In this paper, we use multi-objective particle swarm optimisation (MOPSO) to yield the best selection of IP to implement efficiently a given application on a NoC infrastructure. In this purpose, MOPSO is exploited to obtain an assignment that minimises the requirements for power, hardware area and the total execution of the application. We show that the achieved solutions are better that those obtained by other multi-objective optimisation algorithms.

Keywords: network-on-chip; NoC; IP assignment; multi-objective design; particle swarm optimisation; PSO.

DOI: 10.1504/IJBIC.2018.096483

International Journal of Bio-Inspired Computation, 2018 Vol.12 No.4, pp.203 - 213

Received: 09 Feb 2018
Accepted: 09 Aug 2018
Published online: 04 Dec 2018 *

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