Efficient Fault-Criticality Analysis for AI Accelerators using a Neural Twin ∗

Owing to the inherent fault tolerance of deep neural network (DNN) models used for classification, many structural faults in the processing elements (PEs) of a systolic array-based AI accelerator are functionally benign. Brute-force fault simulation for determining fault criticality is computationally expensive due to many potential fault sites in the accelerator array and the dependence of critic...