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https://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 |
DOI: | 10.3934/jimo.2014.10.383 |
Published version: | http://dx.doi.org/10.3934/jimo.2014.10.383 |
Appears in Collections: | Aurora harvest 4 Electrical and Electronic Engineering publications |
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