Fault Injectors for TensorFlow: Evaluation of the Impact of Random Hardware Faults on Deep CNNs

Understand

Today, Deep Learning (DL) enhances almost every industrial sector, including safety-critical areas.

• The next generation of safety standards will define appropriate verification techniques for DL-based applications and propose adequate fault tolerance mechanisms.
• DL-based applications, like any other software, are susceptible to common random hardware faults such as bit flips, which occur in RAM and CPU registers.
• Such faults can lead to silent data corruption.