A Routing based Genetic Algorithm for Task Mapping on MPSoC - Rocha, Hiago; Beck, Antonio Carlos; Maia, Sílvia; Kreutz, Márcio; Pereira, Monica (Anais do Simpósio Brasileiro de Engenharia de Sistemas Computacionais (SBESC); 2020: Anais do X Simpósio Brasileiro de Engenharia de Sistemas Computacionais, 2020)
This work proposes an optimized task mapping solution called Routing Model-based Genetic Algorithm (RMGA) that combines task mapping and routing problems using an Integer Linear Programming (ILP) model as a fitness function. We compared our proposed RMGA with other Genetic Algorithms (GA) that address the mapping problem using a classical flow×distance fitness function evaluation. Experimental results evaluating communication latency demonstrate that the proposed algorithm outperforms two GAs from literature. It presents up to 30% lower delay when simulating tasks communication pattern of six different applications and varying packet injection rate and NoC dimension. Additionally, RMGA presents the lowest delay of more than 70% in all simulated scenarios compared to the other GAs.