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

• Published in: 2011 International Conference on Reconfigurable Computing and FPGAs pp. 164 - 169
• Main Authors: Salvador, Ruben, Otero, Andres, Mora, Javier, de la Torre, Eduardo, Sekanina, Lukas, Riesgo, Teresa
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.11.2011
• Subjects: Arrays; Autonomous Systems; Circuit faults; Evolvable Hardware; Fault diagnosis; Fault tolerance; Fault tolerant systems; Field programmable gate arrays; FPGA; Hardware; Partial Dynamic Reconfiguration; Self-Healing
• ISBN: 9781457717345; 1457717344
• ISSN: 2325-6532
• DOI: 10.1109/ReConFig.2011.37

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).