3 citations · 5 across the 5 of their papers we have counts for
5 papers · 1 filter
TreeFI: Value-Aware Statistical Fault Injection for Deep Neural Networks
Noam Bires, Marcello Traiola, Angeliki Kritikakou +1
Reliability evaluation of deep neural networks under hardware faults commonly relies on fault injection, but exhaustive campaigns are intractable for modern models and datasets. St…
ENFOR-SA: End-to-end Cross-layer Transient Fault Injector for Efficient and Accurate DNN Reliability Assessment on Systolic Arrays
Rafael Billig Tonetto, Marcello Traiola, Fernando Fernandes dos Santos +1
Recent advances in deep learning have produced highly accurate but increasingly large and complex DNNs, making traditional fault-injection techniques impractical. Accurate fault an…
SWAPPER: Dynamic Operand Swapping in Non-commutative Approximate Circuits for Online Error Reduction
Marcello Traiola, Nazar Misyats, Silviu-Ioan Filip +2
Error-tolerant applications, such as multimedia processing, machine learning, signal processing, and scientific computing, can produce satisfactory outputs even when approximate co…
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…
Experimental evaluation of neutron-induced errors on a multicore RISC-V platform
Fernando Fernandes dos Santos, Angeliki Kritikakou, Olivier Sentieys
RISC-V architectures have gained importance in the last years due to their flexibility and open-source Instruction Set Architecture (ISA), allowing developers to efficiently adopt…