Title
Expediting Ga-Based Evolution Using Group Testing Techniques For Reconfigurable Hardware
Abstract
Autonomous repair and refurbishment of reprogrammable logic devices using Genetic Algorithms can improve the fault tolerance of remote mission-critical systems. The goal of increasing availability by minimizing the repair time is addressed in this paper using a CGT-pruned Genetic Algorithm. The proposed method utilizes resource performance information obtained using Combinatorial Group Testing (CGT) techniques to evolve refurbished configurations in fewer generations than conventional genetic algorithms. A 3-bit x 2-bit Multiplier circuit was evolved using both conventional and CGT-pruned genetic algorithms. Results show that the new approach yields completely refurbished configurations 37.6% faster than conventional genetic algorithms. In addition it is demonstrated that for the same circuit, refurbishment of partially-functional configurations is a more tractable problem than designing the configurations when using genetic algorithms as results show the former to take 80% fewer generations. © 2006 IEEE.
Publication Date
12-1-2006
Publication Title
Proceedings of the 2006 IEEE International Conference on Reconfigurable Computing and FPGA's, ReConFig 2006
Number of Pages
106-113
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/RECONF.2006.307760
Copyright Status
Unknown
Socpus ID
46449103069 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/46449103069
STARS Citation
Oreifej, Rashad S.; Sharma, Carthik A.; and DeMara, Ronald F., "Expediting Ga-Based Evolution Using Group Testing Techniques For Reconfigurable Hardware" (2006). Scopus Export 2000s. 7637.
https://stars.library.ucf.edu/scopus2000/7637