Artificial neural networks for space and safety-critical applications: Reliability issues and potential solutions

P Rech - IEEE Transactions on Nuclear Science, 2024‏ - ieeexplore.ieee.org
Machine learning is among the greatest advancements in computer science and
engineering and is today used to classify or detect objects, a key feature in autonomous …

A survey on deep learning resilience assessment methodologies

A Ruospo, E Sanchez, LM Luza, L Dilillo, M Traiola… - Computer, 2023‏ - ieeexplore.ieee.org
Deep learning (DL) reliability is becoming a growing concern, and efficient reliability
assessment approaches are required to meet safety constraints. This article presents a …

Assessment of the impact of the freshman engineering courses

D Budny, G Bjedov, W LeBold - … and Learning in an Era of …, 1997‏ - ieeexplore.ieee.org
This study is based on historical data for a 28 year period, from 1966 through 1993. The
study evaluates if the freshmen engineering courses supply the entering engineering …

A multi-level approach to evaluate the impact of gpu permanent faults on cnn's reliability

JER Condia, JD Guerrero-Balaguera… - 2022 IEEE …, 2022‏ - ieeexplore.ieee.org
Graphics processing units (GPUs) are widely used to accelerate Artificial Intelligence
applications, such as those based on Convolutional Neural Networks (CNNs). Since in …

Revealing gpus vulnerabilities by combining register-transfer and software-level fault injection

FF dos Santos, JER Condia, L Carro… - 2021 51st Annual …, 2021‏ - ieeexplore.ieee.org
The complexity of both hardware and software makes GPUs reliability evaluation extremely
challenging. A low level fault injection on a GPU model, despite being accurate, would take …

Availability evaluation and sensitivity analysis of a mobile backend‐as‐a‐service platform

I Costa, J Araujo, J Dantas, E Campos… - Quality and …, 2016‏ - Wiley Online Library
Performance evaluation of mobile applications has received considerable attention as a
prominent activity for improving services quality. Because many data stored on mobile …

A fast, flexible, and easy-to-develop FPGA-based fault injection technique

M Ebrahimi, A Mohammadi, A Ejlali… - Microelectronics …, 2014‏ - Elsevier
By technology down scaling in nowadays digital circuits, their sensitivity to radiation effects
increases, making the occurrence of soft errors more probable. As a consequence, soft error …

SCFIT: A FPGA-based fault injection technique for SEU fault model

A Mohammadi, M Ebrahimi, A Ejlali… - … Design, Automation & …, 2012‏ - ieeexplore.ieee.org
In this paper, we have proposed a fast and easy-to-develop FPGA-based fault injection
technique. This technique uses the Altera FPGAs debugging facilities in order to inject SEU …

Soft error mitigation for SRAM-based FPGAs

GH Asadi, MB Tahoori - 23rd IEEE VLSI Test Symposium (VTS' …, 2005‏ - ieeexplore.ieee.org
FPGA-based designs are more susceptible to single-event up-sets (SEUs) compared to
ASIC designs, since SEUs in configuration bits of FPGAs result in permanent errors in the …

Dependability analysis using a fault injection tool based on synthesizability of HDL models

HR Zarandi, SG Miremadi… - Proceedings 18th IEEE …, 2003‏ - ieeexplore.ieee.org
This paper presents a fault injection tool called SINJECT that supports several synthesizable
and non-synthesizable fault models for dependability analysis of digital systems modeled by …