activity
20212025
most citedCharacterizing a Neutron-Induced Fault Model for Deep Neural Networks

3 citations · 4 across the 5 of their papers we have counts for

collaborators

6 papers

cs.DC2025

GPU Under Pressure: Estimating Application's Stress via Telemetry and Performance Counters

Giuseppe Esposito, Juan-David Guerrero-Balaguera, Josie Esteban Rodriguez Condia +3

Graphics Processing Units (GPUs) are specialized accelerators in data centers and high-performance computing (HPC) systems, enabling the fast execution of compute-intensive applica…

cs.NE2024

Evaluating Different Fault Injection Abstractions on the Assessment of DNN SW Hardening Strategies

Giuseppe Esposito, Juan David Guerrero-Balaguera, Josie Esteban Rodriguez Condia +1

The reliability of Neural Networks has gained significant attention, prompting efforts to develop SW-based hardening techniques for safety-critical scenarios. However, evaluating h…

cs.AR2023★ 1 cited

Understanding the Effects of Permanent Faults in GPU's Parallelism Management and Control Units

Juan-David Guerrero-Balaguera, Josie E. Rodriguez Condia, Fernando F. dos Santos +2

Graphics Processing Units (GPUs) are over-stressed to accelerate High-Performance Computing applications and are used to accelerate Deep Neural Networks in several domains where th…

cs.AR2022★ 3 cited

Characterizing a Neutron-Induced Fault Model for Deep Neural Networks

Fernando Fernandes dos Santos, Angeliki Kritikakou, Josie Esteban Rodriguez Condia +4

The reliability evaluation of Deep Neural Networks (DNNs) executed on Graphic Processing Units (GPUs) is a challenging problem since the hardware architecture is highly complex and…

cs.NE2022

Reliability Assessment of Neural Networks in GPUs: A Framework For Permanent Faults Injections

Juan-David Guerrero-Balaguera, Luigi Galasso, Robert Limas Sierra +1

Currently, Deep learning and especially Convolutional Neural Networks (CNNs) have become a fundamental computational approach applied in a wide range of domains, including some saf…

cs.AR2021

A Novel Compaction Approach for SBST Test Programs

Juan-David Guerrero-Balaguera, Josie E. Rodriguez Condia, Matteo Sonza Reorda

In-field test of processor-based devices is a must when considering safety-critical systems (e.g., in robotics, aerospace, and automotive applications). During in-field testing, di…