Publications Details

Reconfigurable Compute-In-Memory on Field-Programmable Ferroelectric Diodes

Liu, Xiwen; Ting, John; He, Yunfei; Fiagbenu, Merrilyn M.A.; Zheng, Jeffrey; Wang, Dixiong; Frost, Jonathan; Musavigharavi, Pariasadat; Esteves, Giovanni E.; Kisslinger, Kim; Anantharaman, Surendra B.; Stach, Eric A.; Olsson, Roy H.; Jariwala, Deep

The deluge of sensors and data generating devices has driven a paradigm shift in modern computing from arithmetic-logic centric to data-centric processing. Data-centric processing require innovations at the device level to enable novel compute-in-memory (CIM) operations. A key challenge in the construction of CIM architectures is the conflicting trade-off between the performance and their flexibility for various essential data operations. Here, we present a transistor-free CIM architecture that permits storage, search, and neural network operations on sub-50 nm thick Aluminum Scandium Nitride ferroelectric diodes (FeDs). Our circuit designs and devices can be directly integrated on top of Silicon microprocessors in a scalable process. By leveraging the field-programmability, nonvolatility, and nonlinearity of FeDs, search operations are demonstrated with a cell footprint <0.12 μm2when projected onto 45 nm node technology. We further demonstrate neural network operations with 4-bit operation using FeDs. Our results highlight FeDs as candidates for efficient and multifunctional CIM platforms.