Designing Circuits for AiMC Based on Non-Volatile Memories: A Tutorial Brief on Trade-Off and Strategies for ADCs and DACs Co-Design

Analog In-Memory Computing (AiMC) based on Non-Volatile Memories (NVM) is a promising candidate to reduce latency and power consumption of neural network (NN) inference in edge-computing applications. This kind of computational accelerators allows both storing weights and performing in-situ analog computation inside the array. This tutorial explores trade-offs and strategies in the design of DACs and ADCs for this kind of systems, highlighting the strong interdependence between the two converters. Starting from an analysis of input and weights encoding techniques this tutorial will then propose a discussion aiming at exploring critical aspects that constrain the design of D-A and A-D converters drawing some co-design considerations.