Robust Processing-In-Memory With Multibit ReRAM Using Hessian-Driven Mixed-Precision Computation

This article presents an algorithmic approach to design reliable deep neural networks (DNNs) in the presence of stochastic variations in the network parameters induced by process variations in the bit cells in a processing-in-memory (PIM) architecture. We propose and derive a Hessian-based sensitivity metric that can be computed without computing or storing the full Hessian to identify and protect...