Preference-based multi-objective evolutionary algorithms for power-aware application mapping on NoC platforms

• Published in: Expert systems with applications Vol. 39; no. 3; pp. 2771 - 2782
• Main Authors: Nedjah, Nadia, Carvalho da Silva, Marcus Vinícius, de Macedo Mourelle, Luiza
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 15.02.2012
• Subjects: Combinatorial analysis; Evolutionary; Evolutionary algorithms; Infrastructure; IP (Internet Protocol); IP assignment; IP mapping; Mapping; Methodology; Multi-objective design; Network-on-chip; Optimization; IP mapping; Multi-objective design; IP assignment; Network-on-chip
• ISSN: 0957-4174; 1873-6793
• DOI: 10.1016/j.eswa.2011.08.137

► Preference-based evolutionary multi-objective optimization (EMO). ► Formulation of IP assignment and IP mapping on a network-on-chips. ► Intelligent application mapping on a network-on-chip platform using EMO. ► Comparison of the performance of two multi-objective optimization algorithms. Network-on-chip (NoC) are considered the next generation of communication infrastructure in embedded systems. In the platform-based design methodology, an application is implemented by a set of collaborative intellectual property (IP) blocks. The selection of the most suited set of IPs as well as their physical mapping onto the NoC infrastructure to implement efficiently the application at hand are two hard combinatorial problems that occur during the synthesis process of Noc-based embedded system implementation. In this paper, we propose an innovative preference-based multi-objective evolutionary methodology to perform the assignment and mapping stages. We use one of the well-known and efficient multi-objective evolutionary algorithms NSGA-II and microGA as a kernel. The optimization processes of assignment and mapping are both driven by the minimization of the required silicon area and imposed execution time of the application, considering that the decision maker’s preference is a pre-specified value of the overall power consumption of the implementation.