Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/81923
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Type: Journal article
Title: Optimizing system-on-chip verifications with multi-objective genetic evolutionary algorithms
Author: Cheng, A.
Lim, C.
Citation: Journal of Industrial and Management Optimization, 2014; 10(2):383-396
Publisher: American Institute of Mathematical Sciences
Issue Date: 2014
ISSN: 1547-5816
1553-166X
Statement of
Responsibility: 
Adriel Cheng and Cheng-Chew Lim
Abstract: 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.
Keywords: Multi-objective optimization; genetic evolutionary algorithms; Pareto optimization; system-on-chip verification; coverage driven verification.
Rights: Copyright status unknown
RMID: 0020133618
DOI: 10.3934/jimo.2014.10.383
Appears in Collections:Electrical and Electronic Engineering publications

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