Reinforcement Guided Genetic Algorithm for Application Mapping in Network-on-Chip Architectures: Toward Transparent and Efficient MPSoC Scheduling

In this paper, we present a novel hybrid application mapping framework that integrates Genetic Algorithm (GA) with Reinforcement Learning (RL) to optimize task allocation in 2D Network-on-Chip based Multiprocessor System-on-Chip (NoC-based MPSoC) architectures. The goal is to reduce overall communic...

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Principais autores:	Ahmed Abbas Jasim Al-Hchaimi, Mahmood A. Al-Shareeda, Ahmad Taher Azar, Walid El-Shafai
Formato:	Artigo
Idioma:	Inglês
Publicado em:	IEEE 2025-01-01
Colecção:	IEEE Access
Assuntos:	Network-on-chip application mapping genetic algorithm reinforcement learning MPSoC convergence-aware optimization
Acesso em linha:	https://ieeexplore.ieee.org/document/11184724/
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