Expediting GA-Based Evolution Using Group Testing Techniques for Reconfigurable Hardware

Oreifej, Rashad S.; Sharma, Carthik A.; DeMara, Ronald F.

doi:10.1109/reconf.2006.307760

Cited by 19 publications

(11 citation statements)

References 13 publications

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“…This is readily incorporated within the configuration selection step of CRR. The genetic operators are then applied only to that isolated stage to attempt recovery, thus providing an approach to extend the CRR method to larger circuits while remaining computationally tractable [Oreifej06].…”

Section: Resultsmentioning

confidence: 99%

Autonomic fault-handling and refurbishment using throughput-driven assessment

DeMara

Zhang

Sharma

2011

Applied Soft Computing

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Section: Resultsmentioning

confidence: 99%

Autonomic fault-handling and refurbishment using throughput-driven assessment

DeMara

Zhang

Sharma

2011

Applied Soft Computing

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“…This has been analyzed in [5], [10] and [11], in combination with EHW. Apart from using the EA as a method for finding an optimized solution to solve a problem, this technique works as a self-healing technique because faulty designs are treated as sub-optimal solutions in the evolution, and therefore they are discarded in favor of a better solution, so the fault is avoided, or healed.…”

Section: Analysis Of the State Of The Artmentioning

confidence: 99%

A Novel FPGA-based Evolvable Hardware System Based on Multiple Processing Arrays

Gallego¹,

Mora²,

Otero³

et al. 2013

2013 IEEE International Symposium on Parallel &Amp; Distributed Processing, Workshops and PHD Forum

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Abstract-In this paper, an architecture based on a scalable and flexible set of Evolvable Processing arrays is presented. FPGA-native Dynamic Partial Reconfiguration (DPR) is used for evolution, which is done intrinsically, letting the system to adapt autonomously to variable run-time conditions, including the presence of transient and permanent faults. The architecture supports different modes of operation, namely: independent, parallel, cascaded or bypass mode. These modes of operation can be used during evolution time or during normal operation. The evolvability of the architecture is combined with fault-tolerance techniques, to enhance the platform with self-healing features, making it suitable for applications which require both high adaptability and reliability. Experimental results show that such a system may benefit from accelerated evolution times, increased performance and improved dependability, mainly by increasing fault tolerance for transient and permanent faults, as well as providing some fault identification possibilities. The evolvable HW array shown is tailored for window-based image processing applications.

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“…A refinement on both these last two references is shown in [12]. It presents a GA-based evolution schema using Combinatorial Group Testing [13] to show the benefits of utilizing location information of the faulty resources to reduce the search space.…”

Section: Related Workmentioning

confidence: 99%

Fault Tolerance Analysis and Self-Healing Strategy of Autonomous, Evolvable Hardware Systems

Salvador

Otero

Mora

et al. 2011

2011 International Conference on Reconfigurable Computing and FPGAs

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Abstract-This paper presents an analysis of the fault tolerance achieved by an autonomous, fully embedded evolvable hardware system, which uses a combination of partial dynamic reconfiguration and an evolutionary algorithm (EA). It demonstrates that the system may self-recover from both transient and cumulative permanent faults. This self-adaptive system, based on a 2D array of 16 (4×4) Processing Elements (PEs), is tested with an image filtering application. Results show that it may properly recover from faults in up to 3 PEs, that is, more than 18% cumulative permanent faults. Two fault models are used for testing purposes, at PE and CLB levels. Two self-healing strategies are also introduced, depending on whether fault diagnosis is available or not. They are based on scrubbing, fitness evaluation, dynamic partial reconfiguration and in-system evolutionary adaptation. Since most of these adaptability features are already available on the system for its normal operation, resource cost for self-healing is very low (only some code additions in the internal microprocessor core).

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Expediting GA-Based Evolution Using Group Testing Techniques for Reconfigurable Hardware

Cited by 19 publications

References 13 publications

Autonomic fault-handling and refurbishment using throughput-driven assessment

Autonomic fault-handling and refurbishment using throughput-driven assessment

A Novel FPGA-based Evolvable Hardware System Based on Multiple Processing Arrays

Fault Tolerance Analysis and Self-Healing Strategy of Autonomous, Evolvable Hardware Systems

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