Optimizing system-on-chip verifications with multi-objective genetic evolutionary algorithms | Zendy

Adriel Cheng | Zendy; ChengChew Lim | Zendy

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Optimizing system-on-chip verifications with multi-objective genetic evolutionary algorithms

Author(s) -

Adriel Cheng,

ChengChew Lim

Publication year - 2013

Publication title -

journal of industrial and management optimization

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.325

H-Index - 32

eISSN - 1553-166X

pISSN - 1547-5816

DOI - 10.3934/jimo.2014.10.383

Subject(s) - computer science , selection (genetic algorithm) , evolutionary algorithm , genetic algorithm , genetic programming , mathematical optimization , machine learning , mathematics

Verification of semiconductor chip designs is commonly driven by single goal orientated measures. With increasing design complexities, this approach is no longer effective. We enhance the effectiveness of coverage driven design verifications by applying multi-objective optimization techniques. The technique is based on genetic evolutionary algorithms. Difficulties with conflicting test objectives and selection of tests to achieve multiple verification goals in the genetic evolutionary framework are also addressed.Adriel Cheng and Cheng-Chew Li

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