Application of an Adaptive Genetic Algorithm for Task Mapping Optimisation on a Wormhole-based Real-time Network-on-Chip - de Barros, Jesse; Ayala-Rincón, Mauricio; Quintero, Carlos (Anais do Simpósio Brasileiro de Engenharia de Sistemas Computacionais (SBESC); 2019: Anais do IX Simpósio Brasileiro de Engenharia de Sistemas Computacionais, 2019)
The task mapping problem of real-time applications onto a homogeneous multiple processors system-on-a-chip (MPSoC) is an NP-hard problem that can be addressed using search-based heuristic methods. A particular case is the priority preemptive wormhole-based Network-on-a-Chip (NoC) communication architecture that takes into consideration the end-to-end schedulability analysis. In this paper, we present a parameter Adaptive Genetic Algorithm (AGA) capable of efficiently achieving schedulable task placements. In our experiments, we perform analytic methods in different scenarios with multiple synthetically generated real-time applications, as well as various platforms with a ranging number of processors to provide a statistical study comparing our algorithm against a standard genetic algorithm approach.