Cross-Layer Modeling and Design of Content Addressable Memories in Advanced Technology Nodes for Similarity Search

Abstract

In this article, we present a comprehensive design and benchmarking study of content addressable memory (CAM) at the 7-nm technology node in the context of similarity search applications. We design CAM cells based on static random access memory (SRAM), spin-orbit torque (SOT), and ferroelectric field effect transistor devices and from their layouts extract cell parasitics using state-of-the-art electronic design automation (EDA) tools. These parasitics are used to develop SPICE netlists to model search operations. We use a CAM-based dataset search and a sequential recommendation system (RS) to highlight the application-level performance degradation due to interconnect parasitics. We propose and evaluate two solutions to mitigate interconnect effects.