Fuzzy decision making in embedded system design

DI NUOVO, Alessandro, PALESI, Maurizio, PATTI, Davide, ASCIA, Giuseppe and CATANIA, Vincenzo (2006). Fuzzy decision making in embedded system design. In: Hardware/Software Codesign and System Synthesis, 2006. CODES+ISSS '06. Proceedings of the 4th International Conference. IEEE, 223-228.

Full text not available from this repository.
Link to published version:: https://doi.org/10.1145/1176254.1176309


The use of Application Specific Instruction-set Processors (ASIP) is a solution to the problem of increasing complexity in embedded systems design. One of the major challenges in ASIP design is Design Space Exploration (DSE), because of the heterogeneity of the objectives and parameters involved. Typically DSE is a multi- objective search problem, where performance, power, area, etc. are the different optimization criteria. The output of a DSE strategy is a set of candidate design solutions called a Pareto-optimal set. Choosing a solution for system implementation from the Pareto- optimal set can be a difficult task, generally because Pareto-optimal sets can be extremely large or even contain an infinite number of solutions. In this paper we propose a methodology to assist the decision-maker in analysis of the solutions to multi-objective problems. By means of fuzzy clustering techniques, it finds the reduced Pareto subset, which best represents all the Pareto solutions. This optimal subset will be used for further and more accurate (but slower) analysis. As a real application example we address the optimization of area, performance, and power of a VLIW-based embedded system.

Item Type: Book Section
Departments - Does NOT include content added after October 2018: Faculty of Science, Technology and Arts > Department of Computing
Identification Number: https://doi.org/10.1145/1176254.1176309
Page Range: 223-228
Depositing User: Alessandro Di Nuovo
Date Deposited: 17 Feb 2016 17:07
Last Modified: 18 Mar 2021 18:30
URI: https://shura.shu.ac.uk/id/eprint/11216

Actions (login required)

View Item View Item


Downloads per month over past year

View more statistics