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Co-evolutionary high-level test synthesis
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Source Great Lakes Symposium on VLSI archive
Proceedings of the 17th ACM Great Lakes symposium on VLSI table of contents
Stresa-Lago Maggiore, Italy
SESSION: Test and reliability table of contents
Pages: 67 - 72  
Year of Publication: 2007
ISBN:978-1-59593-605-9
Authors
Soheil Aminzadeh  University of Tehran, Tehran, Iran
Saeed Safari  University of Tehran, Tehran, Iran
Sponsors
SIGDA: ACM Special Interest Group on Design Automation
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

The main approach of this paper is utilizing bio-inspired evolutionary strategies for high level test synthesis. In this paper a genetic algorithm (GA) is implemented to schedule a data-flow graph considering latency. Also, module binding is performed with another GA concurrently, considering resource constraints. The register allocation is performed using another GA which minimizes the number of registers. Then a co-evolutionary strategy merges the results of these three solutions, targeting testability improvement. Experimental results show using the proposed approach results in improvement in fault coverage with no or negligible overhead in area and delay.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Soheil Aminzadeh: colleagues
Saeed Safari: colleagues