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N. Shaikh-Husin
Department of Electronic and Computer Engineering, Faculty of Electrical Engineering, Universiti Teknologi Malaysia, Johor
Computer Science & IT Electrical & Electronics Engineering

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Energy-Aware Network-on-Chip Application Mapping Based on Domain Knowledge Genetic Algorithm Yin Zhen Tei; Yuan Wen Hau; N. Shaikh-Husin; Trias Andromeda; M. N. Marsono
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 1: EECSI 2014
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1359.964 KB) | DOI: 10.11591/eecsi.v1.352

Abstract

This paper addresses energy-aware application mapping for large-scale Network-on-chip (NoC). The increasing number of intellectual property (IP) cores in multi-processor system-on-chips (MPSoCs) makes NoC application mapping more challenging to find optimum core-to-topology mapping. This paper proposes an application mapping technique that incorporates domain knowledge into genetic algorithm (GA) to minimize the energy consumption of NoC communication. The GA is initialized with knowledge on network partition whereas the genetic crossover operator is guided with inter-core communication demands. NoC energy estimation is based on analytical energy model and cycle-accurate Noxim simulation. For large-scale NoC, application mapping using knowledge-based genetic operator saves up to 28% energy compared to the one on conventional GA. Adding knowledge-based initial mapping speeds up convergence by 81% and further saves energy by 5% compared to only knowledge-based crossover GA. Furthermore, cycle-accurate simulations of applications with traffic dependency show the effectiveness of the proposed application mapping for large-scale NoC.
Co-Authors Andromeda, Trias M. N. Marsono Yin Zhen Tei Yuan Wen Hau