Parallel Applications Mapping onto Network on Chip Based on Heterogeneous MPSoCs Using Hybrid Algorithms

Dihia Belkacemi, Mehammed Daoui, Samia Bouzefrane and Youcef Bouchebaba
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Dihia Belkacemi: LARI Laboratory, Tizi-Ouzou University, Algeria, Algeria
Mehammed Daoui: LARI Laboratory, Tizi-Ouzou University, Algeria, Algeria
Samia Bouzefrane: Conservatoire National des Arts et Métiers, Paris, France
Youcef Bouchebaba: Onera, Palaiseau, France

International Journal of Distributed Systems and Technologies (IJDST), 2019, vol. 10, issue 2, 37-63

Abstract: Mapping parallel applications onto a network on chip (NoC) that is based on heterogeneous MPSoCs is considered as an instance of an NP-hard and a multi-objective problem. Various multi-objective algorithms have been proposed in the literature to handle this issue. Metaheuristics stand out as highly appropriate approaches to deal with this kind of problem. These metaheuristics are classified into two sets: population-based metaheuristics and single solution-based ones. To take advantage of the both sets, the trend is to use hybrid solutions that have shown to give better results. In this article, the authors propose to hybridize these two metaheuristics sets to find good Pareto mapping solutions to optimize the execution time and the energy consumption simultaneously. The experimental results have shown that the proposed hybrid algorithms give high quality non-dominated mapping solutions in a reasonable runtime.

Date: 2019
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