Parallel Applications Mapping onto Network on Chip Based on Heterogeneous MPSoCs Using Hybrid Algorithms
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 multiobjective problem. Various multiobjective algorithms have been proposed in the litterature 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 paper, we propose to hybridize these two metaheuristics' sets to find good Pareto mapping solutions to optimize the execution time and the energy consumption simultaneously. The undertaken experimental results have shown that the proposed hybrid algorithms give high quality non dominated mapping solutions in a reasonable runtime.
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