Modeling Analog-Digital-Converter Energy and Area for Compute-In-Memory Accelerator Design

Analog Compute-in-Memory (CiM) accelerators use analog-digital converters (ADCs) to read the analog values they compute. This work presents an open-source architecture-level model to estimate ADC energy and area, enabling researchers to quickly and easily model key architecture-level tradeoffs in accelerators that use ADCs.