Image processing is today employed in a variety of application fields, including safety-and mission-critical ones. In these scenarios it is vital to carefully analyse the reliability of the designed system before deployment and, if necessary, to adopt specific hardening techniques. Two are the techniques generally employed: circuit-level fault injection and application-level functional error simulation. In this paper we present a set of functional error models specific for a number of convolution-based filters that are the basic building blocks for a wide range of image processing applications. The presented error models, derived through a number of circuit-level fault injection experiments, may be integrated into application-level functional error simulators, bridging the gap between the two strategies. The presented error models are the first step towards combining the accuracy of fault injection and the flexibility of error simulation into a widely adopted reliability analysis tool.

Error Modeling for Image Processing Filters accelerated onto SRAM-based FPGAs

Bolchini C.;Cassano L.;Mazzeo A.;Miele A.
2020

Abstract

Image processing is today employed in a variety of application fields, including safety-and mission-critical ones. In these scenarios it is vital to carefully analyse the reliability of the designed system before deployment and, if necessary, to adopt specific hardening techniques. Two are the techniques generally employed: circuit-level fault injection and application-level functional error simulation. In this paper we present a set of functional error models specific for a number of convolution-based filters that are the basic building blocks for a wide range of image processing applications. The presented error models, derived through a number of circuit-level fault injection experiments, may be integrated into application-level functional error simulators, bridging the gap between the two strategies. The presented error models are the first step towards combining the accuracy of fault injection and the flexibility of error simulation into a widely adopted reliability analysis tool.
Proceedings - 2020 26th IEEE International Symposium on On-Line Testing and Robust System Design, IOLTS 2020
978-1-7281-8187-5
Error Modeling
Error Simulation
Fault Injection
Fault Tolerance
Image Processing
Reliability Analysis
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11311/1150419
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