A Validity Measure for Fuzzy Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
MediaBench: a tool for evaluating and synthesizing multimedia and communicatons systems
MICRO 30 Proceedings of the 30th annual ACM/IEEE international symposium on Microarchitecture
ACM Computing Surveys (CSUR)
Ranking engineering design concepts using a fuzzy outranking preference model
Fuzzy Sets and Systems
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Fuzzy Models and Algorithms for Pattern Recognition and Image Processing
Fuzzy Models and Algorithms for Pattern Recognition and Image Processing
Conflicting Criteria in Embedded System Design
IEEE Design & Test
Handling Constraints in Multi-Objective GA for Embedded System Design
VLSID '06 Proceedings of the 19th International Conference on VLSI Design held jointly with 5th International Conference on Embedded Systems Design
Efficient design space exploration of high performance embedded out-of-order processors
Proceedings of the conference on Design, automation and test in Europe: Proceedings
Trimaran: an infrastructure for research in instruction-level parallelism
LCPC'04 Proceedings of the 17th international conference on Languages and Compilers for High Performance Computing
Clustering with a genetically optimized approach
IEEE Transactions on Evolutionary Computation
On cluster validity for the fuzzy c-means model
IEEE Transactions on Fuzzy Systems
Platune: a tuning framework for system-on-a-chip platforms
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
A multiobjective genetic approach for system-level exploration in parameterized systems-on-a-chip
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Microprocessors & Microsystems
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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.