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

Socpus ID

84946689274 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84946689274

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