Resistive switching devices empower the AI era

In the era of intelligence, computational tasks are shifting from being “computation-intensive" to “data-intensive", posing significant challenges for the traditional von Neumann architecture in terms of computational power and energy efficiency. Resistive switching devices, with the advantages of high integration density, fast switching speed, and low switching energy, have shown tremendous potential in embedded memory, in-memory computing (IMC), and neuromorphic computing, providing innovative solutions to these challenges. In this work, we review the basic concepts, key electrical characteristics, and applications of resistive switching devices, analyzing their crucial role in advancing embedded memory, IMC, and neuromorphic computing at advanced process nodes. Specifically, we discuss the development status and challenges of resistive switching devices in empowering IMC and the core units of neuromorphic computing, such as neurons and synapses, unveiling their support for intelligent computing system evolution and forecasting future development prospects. In summary, resistive switching devices, with their unique advantages, offer transformative potential for traditional computing systems, contributing to the accelerated development of the AI era.