Computing-in-Memory with Ferroelectric Materials and Beyond

Recent discovery of hafnium-based ferroelectric (FE) materials opens up numerous CMOS-compatible memory device opportunities: FE capacitors, FE-FETs, and FE tunnel junctions. These devices offer significant advantages in endurance, write speed, and power compared to today's flash. In this paper, we give a brief overview of FE materials/devices fundamentals, and its applicability towards computing-in-memory (CIM). We discuss CIM realized using FE-FinFET arrays with various possible configurations. Alternatively, FE capacitors in CMOS backend may be used in non-volatile SRAM cells to store contents of CIM-SRAM before powering off. We also present CIMulator, a simulation platform to account for device, circuit, and neural network aspects CIM macros with deep machine learning applications.