Title: A comparison between evolutionary and local search techniques applied to NoC design space exploration
Authors: Jefferson Silva; Sílvia M.D.M. Maia; Monica Magalhães; Márcio E. Kreutz
Addresses: Federal Institute of Rio Grande do Norte – IFRN, Natal, RN, Brazil ' Department of Informatics and Applied Mathematics, Federal University of Rio Grande do Norte – UFRN, Natal, RN, Brazil ' Department of Informatics and Applied Mathematics, Federal University of Rio Grande do Norte – UFRN, Natal, RN, Brazil ' Department of Informatics and Applied Mathematics, Federal University of Rio Grande do Norte – UFRN, Natal, RN, Brazil
Abstract: Networks on chip emerged as a communication architecture that overcame the limitations of bus architecture. As more cores were being incorporated in a single die, shared communication architectures reached out limitations in terms of scalability and performance. However, the NoC-based communication architecture has many configuration parameters leading to a huge design space to be covered during the design phase. Aiming to find optimised configurations, some methods should be employed to explore the design space and speed up this process. This paper investigates three techniques, genetic algorithm, memetic algorithm, and iterated local search. Results have shown the lowest execution time for ILS when compared with the other two. In relation to the quality of the solution, the MME overcame both in almost all scenarios, even considering execution time or number of evaluation as stop criteria.
Keywords: evolutionary computing; networks on chip; NoC; genetic algorithm; iterated local search; ILS; memetic algorithm; design space exploration.
DOI: 10.1504/IJICA.2020.111225
International Journal of Innovative Computing and Applications, 2020 Vol.11 No.4, pp.193 - 203
Received: 22 Aug 2019
Accepted: 26 Nov 2019
Published online: 16 Nov 2020 *