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Soft-Error Analysis of Self-reconfiguration Controllers for Safety Critical Dynamically Reconfigurable FPGAs

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Applied Reconfigurable Computing. Architectures, Tools, and Applications (ARC 2020)

Abstract

Reconfigurable SRAM-based Field Programmable Gate Arrays are increasingly deployed in the aerospace applications, due to their enhanced flexibility, high performance and run-time reconfiguration capabilities. The possibility to adapt on-the-fly the circuit functionality is made possible by the Internal Configuration Access Port (ICAP) that can be managed from the application through a dedicated controller. This feature enables the deployment of new optimized reconfigurable architectures for computationally intensive and fault-tolerant applications. In this context, a promising architecture is the Dynamically Reconfigurable Processing Module (DRPM), an FPGA-based modular system where the content of each reconfigurable module can be rewritten, overwritten or erased to perform performance optimization and functional modification at run-time. However, when these systems are adopted in avionic and space applications, SRAM configuration sensitivity to radiation induced soft-errors should be addressed. In this work, we evaluate the soft-error sensitivity of upsets in the configuration memory of two implementations of the ICAP controller within a DRPM system. We performed a radiation test campaign and a selective fault injection of upsets on the ICAP controller configuration memory to mimic the radiation profiles. The comparative analysis showed meaningful guidelines on the implementations of self-reconfigurable systems for the aerospace domain: the controller with distributed memory results the 28% more tolerant to low radiation environment compared to the integrated memory version, which in return results the 25% more robust considering radiation particles with higher energies.

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Correspondence to Ludovica Bozzoli .

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Bozzoli, L., Sterpone, L. (2020). Soft-Error Analysis of Self-reconfiguration Controllers for Safety Critical Dynamically Reconfigurable FPGAs. In: Rincón, F., Barba, J., So, H., Diniz, P., Caba, J. (eds) Applied Reconfigurable Computing. Architectures, Tools, and Applications. ARC 2020. Lecture Notes in Computer Science(), vol 12083. Springer, Cham. https://doi.org/10.1007/978-3-030-44534-8_7

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  • DOI: https://doi.org/10.1007/978-3-030-44534-8_7

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