Publication Details
Fault Tolerance Analysis and Self-Healing Strategy of Autonomous, Evolvable Hardware Systems
Otero Andres
Mora Javier
De la Torre Eduardo
Sekanina Lukáš, prof. Ing., Ph.D. (DCSY)
Riesgo Teresa
Evolvable Hardware, Fault Tolerance, Self-Healing, Autonomous Systems, FPGA, Partial Dynamic Reconfiguration
This paper presents an analysis of the fault tolerance achieved by an autonomous, fully embedded evolvablehardware system, which uses a combination of partial dynamic reconfiguration and an evolutionary algorithm (EA). Itdemonstrates 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).
@inproceedings{BUT76495,
author="Ruben {Salvador} and Andres {Otero} and Javier {Mora} and Eduardo {De la Torre} and Lukáš {Sekanina} and Teresa {Riesgo}",
title="Fault Tolerance Analysis and Self-Healing Strategy of Autonomous, Evolvable Hardware Systems",
booktitle="Proc. of the 2011 International Conference on ReConFigurable Computing and FPGAs",
year="2011",
pages="164--169",
publisher="IEEE Computer Society",
address="Los Alamitos",
isbn="978-0-7695-4551-6",
url="https://www.fit.vut.cz/research/publication/9831/"
}