Title
Sustainability Assurance Modeling For Sram-Based Fpga Evolutionary Self-Repair
Keywords
Autonomous fault-refurbishment; Dynamic resource allocation; Evolvable hardware; Fault modeling; Field programmable gate arrays (FPGAs); Genetic algorithms (GAs); Reliability; Sustainability
Abstract
A quantitative stochastic design technique is developed for evolvable hardware systems with self-repairing, replaceable, or amorphous spare components. The model develops a metric of sustainability which is defined in terms of residual functionality achieved from pools of amorphous spares of dynamically configurable logic elements, after repeated failure and recovery cycles. At design-time the quantity of additional resources needed to meet mission availability and lifetime requirements given the fault-susceptibility and recovery capabilities are assured within specified constraints. By applying this model to MCNC benchmark circuits mapped onto Xilinx Virtex-4 Field Programmable Gate Array (FPGA) with reconfigurable logic resources, we depict the effect of fault rates for aging-induced degradation under Time Dependent Dielectric Breakdown (TDDB) and interconnect failure under Electromigration (EM). The model considers a population-based genetic algorithm to refurbish hardware resources which realize repair policy parameters and decaying reparability as a complete case-study using published component failure rates.
Publication Date
1-13-2014
Publication Title
IEEE SSCI 2014 - 2014 IEEE Symposium Series on Computational Intelligence - IEEE ICES: 2014 IEEE International Conference on Evolvable Systems, Proceedings
Number of Pages
17-22
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/ICES.2014.7008717
Copyright Status
Unknown
Socpus ID
84946689274 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84946689274
STARS Citation
Oreifej, Rashad S.; Al-Haddad, Rawad; Ashraf, Rizwan A.; and Demara, Ronald F., "Sustainability Assurance Modeling For Sram-Based Fpga Evolutionary Self-Repair" (2014). Scopus Export 2010-2014. 8863.
https://stars.library.ucf.edu/scopus2010/8863