相关论文: Techniques for Fast Transient Fault Grading Based …

Rapidly shrinking technology node and voltage scaling increase the susceptibility of Soft Errors in digital circuits. Soft Errors are radiation-induced effects while the radiation particles such as Alpha, Neutrons or Heavy Ions, interact…

Neural Networks (NNs) are increasingly used in the last decade in several demanding applications, such as object detection and classification, autonomous driving, etc. Among different computing platforms for implementing NNs, FPGAs have…

The ever-expanding scale of integrated circuits has brought about a significant rise in the design risks associated with radiation-resistant integrated circuit chips. Traditional single-particle experimental methods, with their iterative…

A new field programmable gate array (FPGA)-based emulation platform is proposed to accelerate fault tolerance analysis of inference accelerators of convolutional neural networks (CNN). For a given CNN model, hardware accelerator…

Reliability has been a major concern in embedded systems. Higher transistor density and lower voltage supply increase the vulnerability of embedded systems to soft errors. A Single Event Upset (SEU), which is also called a soft error, can…

SRAM-based FPGAs are increasingly popular in the aerospace industry due to their field programmability and low cost. However, they suffer from cosmic radiation induced Single Event Upsets (SEUs). In safety-critical applications, the…

A single event upset (SEU) is a critical soft error that occurs in semiconductor devices on exposure to ionising particles from space environments. SEUs cause bit flips in the memory component of semiconductors. This creates a multitude of…

The advanced complex electronic systems increasingly demand safer and more secure hardware parts. Correspondingly, fault injection became a major verification milestone for both safety- and security-critical applications. However, fault…

Simulation-based fault injection is a widely adopted methodology for assessing circuit vulnerability to Single Event Upsets (SEUs); however, its computational cost grows significantly with circuit complexity. To address this limitation,…

In contemporary times, the increasing complexity of the system poses significant challenges to the reliability, trustworthiness, and security of the SACRES. Key issues include the susceptibility to phenomena such as instantaneous voltage…

Nanometer circuits are becoming increasingly susceptible to soft-errors due to alpha-particle and atmospheric neutron strikes as device scaling reduces node capacitances and supply/threshold voltage scaling reduces noise margins. It is…

Effects of radiation on electronic circuits used in extra-terrestrial applications and radiation prone environments need to be corrected. Since FPGAs offer flexibility, the effects of radiation on them need to be studied and robust methods…

Over past years, the easy accessibility to the large scale datasets has significantly shifted the paradigm for developing highly accurate prediction models that are driven from Neural Network (NN). These models can be potentially impacted…

Heavy ions induced single event upset (SEU) sensitivity of three-dimensional integrated SRAMs are evaluated by using Monte Carlo sumulation methods based on Geant4. The cross sections of SEUs and Multi Cell Upsets (MCUs) for 3D SRAM are…

The soft error rate (SER) of integrated circuits (ICs) operating in space environment may vary by several orders of magnitude due to the variable intensity of radiation exposure. To ensure the radiation hardness without compromising the…

This paper presents a detailed evaluation of the efficiency of software-only techniques to mitigate SEU and SET in microprocessors. A set of well-known rules is presented and implemented automatically to transform an unprotected program…

Neural Networks (NN) have recently emerged as backbone of several sensitive applications like automobile, medical image, security, etc. NNs inherently offer Partial Fault Tolerance (PFT) in their architecture; however, the biased PFT of NNs…

Deep neural networks (DNNs) are increasingly used in safety-critical applications. Reliable fault analysis and mitigation are essential to ensure their functionality in harsh environments that contain high radiation levels. This study…

A new physics-based model for analytical calculation of Soft Error Rate (SER) in digital memory circuits under the influence of heavy ions in space orbits is proposed. This method is based on parameters that are uniquely determined from the…

Many aerospace and automotive applications use FPGAs in their designs due to their low power and reconfigurability requirements. Meanwhile, such applications also pose a high standard on system reliability, which makes the early-stage…