Ronald F. DeMara, Kening Zhang, and Carthik A. Sharma
University of Central Florida
"Autonomic Fault-Handling and Refurbishment Using Throughput-Driven Assessment"
Applied Soft Computing, In Press, 25 January 2010.

An Evolvable Hardware paradigm for autonomic regeneration called Competitive Runtime Reconfiguration (CRR) is
developed whereby an individual’s performance is assessed using the dynamic properties of the population rather than a static
fitness function. CRR employs a Sliding Evaluation Window of recent throughput data and a periodically-updated Outlier
Threshold which avoids the extensive downtime associated with exhaustive Genetic Algorithm (GA) based evaluation. The
relative fitness measure favors graceful degradation by leveraging the behavioral diversity among the individuals in the
population. Throughput-driven assessment identifies configurations whose discrepancy values violate the Outlier Threshold and
are thus selected for modification using Genetic Operators. Application of CRR to FPGA-based logic circuits demonstrates the
identification of configurations impacted by a set of randomly-injected stuck-at faults. Furthermore, regeneration of
functionality can be observed within a few hundred repair iterations. The viable throughput of the CRR system during the
repair process was maintained at greater than 91.7% of the fault-free throughput rate under a number of circuit scenarios. CRR
results are also compared with alternative soft computing approaches for autonomous refurbishment using the MCNC-91
benchmarks.