Artificial Resilience in neuromorphic systems

Author:

Carpegna Alessio1,Di Carlo Stefano1,Savino Alessandro1

Affiliation:

1. Control and computer engineering, Politecnico di Torino, Italy

Publisher

ACM

Reference11 articles.

1. Hardware and Software Optimizations for Accelerating Deep Neural Networks: Survey of Current Trends, Challenges, and the Road Ahead

2. Simone Dutto , Alessandro Savino , and Stefano Di Carlo . 2021 . Exploring Deep Learning for In-Field Fault Detection in Microprocessors. In 2021 Design , Automation Test in Europe Conference Exhibition (DATE). 1456–1459 . Simone Dutto, Alessandro Savino, and Stefano Di Carlo. 2021. Exploring Deep Learning for In-Field Fault Detection in Microprocessors. In 2021 Design, Automation Test in Europe Conference Exhibition (DATE). 1456–1459.

3. Pierre Falez , Pierre Tirilly , Ioan Marius Bilasco , Philippe Devienne , and Pierre Boulet . 2019 . Multi-layered Spiking Neural Network with Target Timestamp Threshold Adaptation and STDP. In 2019 International Joint Conference on Neural Networks (IJCNN). IEEE, 1–8. Pierre Falez, Pierre Tirilly, Ioan Marius Bilasco, Philippe Devienne, and Pierre Boulet. 2019. Multi-layered Spiking Neural Network with Target Timestamp Threshold Adaptation and STDP. In 2019 International Joint Conference on Neural Networks (IJCNN). IEEE, 1–8.

4. Homeostatic Fault Tolerance in Spiking Neural Networks: A Dynamic Hardware Perspective

5. Darwin: A neuromorphic hardware co-processor based on spiking neural networks

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1. SpikingJET: Enhancing Fault Injection for Fully and Convolutional Spiking Neural Networks;2024 IEEE 30th International Symposium on On-Line Testing and Robust System Design (IOLTS);2024-07-03

2. Micro-Architectural features as soft-error markers in embedded safety-critical systems: preliminary study;2023 IEEE European Test Symposium (ETS);2023-05-22

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