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Erschienen in: The Journal of Supercomputing 7/2024

07.12.2023

A twofold bio-inspired system for mitigating SEUs in the controllers of digital system deployed on FPGA

verfasst von: S. Deepanjali, S. K. Noor Mahammad

Erschienen in: The Journal of Supercomputing | Ausgabe 7/2024

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Abstract

Reconfigurable hardware, extensively employed in mission-critical digital applications like space and military electronics due to its adaptability, encounters the issue of soft errors, especially in control path elements, which could result in functional failure. Various system-level fault tolerance methodologies exist, and this paper implements a bio-inspired fault tolerance technique called evolvable hardware (EHW). The preferred implementation of the EHW system involves hosting the evolutionary algorithm on the processor alongside the reconfigurable hardware. However, this approach encounters delays in the intercommunication of the evolved circuit between the reconfigurable hardware and the processor. To address this issue, the paper proposes a two-tier architecture to achieve absolute fault mitigation in the controller. In this architecture, Tier-1 involves the digital implementation of the genetic algorithm on the reconfigurable hardware to mitigate errors in the controller, while Tier-2 focuses on mitigating errors occurring in Tier-1. The aim is to establish an absolute and self-resilient controller hardware to mitigate faults. The study simulates faults at the target circuit and genetic module as a proof of concept. The proposed two-tier single event upset (SEU) mitigation is deployed on Microsemi’s ProAsic3e FPGA (Field Programmable Gate Array), achieving an average efficiency of 91%. This efficiency is accompanied by ten times lesser resource utilization compared to traditional methodologies and a 30% accelerated speed when compared to hybrid evolvable systems.

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Metadaten
Titel
A twofold bio-inspired system for mitigating SEUs in the controllers of digital system deployed on FPGA
verfasst von
S. Deepanjali
S. K. Noor Mahammad
Publikationsdatum
07.12.2023
Verlag
Springer US
Erschienen in
The Journal of Supercomputing / Ausgabe 7/2024
Print ISSN: 0920-8542
Elektronische ISSN: 1573-0484
DOI
https://doi.org/10.1007/s11227-023-05804-0

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