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• W2977331393 abstract "This paper presents a modified version of the well-known Particle Swarm Optimization (PSO) algorithm as an alternative for the single-objective Genetic Algorithm (GA) that is currently the state-of-the-art method to map real-time applications tasks onto Multiple Processors System-on-a-Chip (MPSoC) using preemptive capable wormhole-based Network-on-a-Chip (NoC) as their communication architecture. A statistical study based on an experimental setup has been performed to compare the GA-based task mapper and the proposed method by using a real-time application as a benchmark, as well as a group of randomly generated ones. Preliminary results have shown that our method is capable of achieving quicker convergence than the GA-based method, and it even produces better results when the application utilization is smaller than the available processing capacity, i.e., a fully schedulable mapping solution exists." @default.
• W2977331393 created "2019-10-10" @default.
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• W2977331393 date "2019-08-26" @default.
• W2977331393 modified "2023-09-28" @default.
• W2977331393 title "An adaptive discrete particle swarm optimization for mapping real-time applications onto network-on-a-chip based MPSoCs" @default.
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• W2977331393 doi "https://doi.org/10.1145/3338852.3339835" @default.
• W2977331393 hasPublicationYear "2019" @default.
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