Add to ORKGInternational audienceWe characterize the fault models for Deep Neural Networks (DNNs) in GPUs exposed to neutron. We observe tolerable and critical errors, and show that ECC is not effective in reducing critical errors
Deep neural networks (DNNs) have been successfully deployed in widespread domains, including healthc...
In this work, a novel deep learning approach to unfold nuclear power reactor signals is proposed. It...
Recently, deep neural networks (DNNs) have been increasingly deployed in various healthcare applicat...
International audienceWe characterize the fault models for Deep Neural Networks (DNNs) in GPUs expos...
International audienceThe reliability evaluation of Deep Neural Networks (DNNs) executed on Graphic ...
Deep neural network (DNN) models are being deployed in safety-critical embedded devices for object i...
In this article, we investigate the reliability of Google’s coral tensor processing units (TPUs) to ...
Paper accepted on 28th IEEE IOLTS 2022International audienceRISC-V architectures have gained importa...
A new Machine Learning algorithm for shower-head identification in the NeuLAND neutron detector is p...
The resurgence of machine learning in various applications and it's inherent compute-intensive natur...
This work was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - ...
Deep Neural Networks (DNNs) have been widely applied in healthcare applications. DNN-based healthcar...
Graphics Processing Units (GPUs) have moved from being dedicated devices for multi media and gaming ...
International audienceGraphics Processing Units (GPUs) offer the possibility to execute floating-poi...
We investigate atmospheric neutron effects on floating-gate cells in NAND Flash memory devices. Char...
Deep neural networks (DNNs) have been successfully deployed in widespread domains, including healthc...
In this work, a novel deep learning approach to unfold nuclear power reactor signals is proposed. It...
Recently, deep neural networks (DNNs) have been increasingly deployed in various healthcare applicat...
International audienceWe characterize the fault models for Deep Neural Networks (DNNs) in GPUs expos...
International audienceThe reliability evaluation of Deep Neural Networks (DNNs) executed on Graphic ...
Deep neural network (DNN) models are being deployed in safety-critical embedded devices for object i...
In this article, we investigate the reliability of Google’s coral tensor processing units (TPUs) to ...
Paper accepted on 28th IEEE IOLTS 2022International audienceRISC-V architectures have gained importa...
A new Machine Learning algorithm for shower-head identification in the NeuLAND neutron detector is p...
The resurgence of machine learning in various applications and it's inherent compute-intensive natur...
This work was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - ...
Deep Neural Networks (DNNs) have been widely applied in healthcare applications. DNN-based healthcar...
Graphics Processing Units (GPUs) have moved from being dedicated devices for multi media and gaming ...
International audienceGraphics Processing Units (GPUs) offer the possibility to execute floating-poi...
We investigate atmospheric neutron effects on floating-gate cells in NAND Flash memory devices. Char...
Deep neural networks (DNNs) have been successfully deployed in widespread domains, including healthc...
In this work, a novel deep learning approach to unfold nuclear power reactor signals is proposed. It...
Recently, deep neural networks (DNNs) have been increasingly deployed in various healthcare applicat...