-A A +A
This chapter introduces various types of resistive memory devices (also named memristive devices) of current interest for brain-inspired computing. These memristive device technologies include a broad class of two-or threeterminal devices whose resistance can be modified upon electrical stimuli. The resistance changes can last for short-or long-time scales, leading to a volatile or nonvolatile memory effect, respectively. Memristive devices are based on a large variety of physical mechanisms, such as redox reactions and ion migration, phase transitions, spin-polarized tunneling, and ferroelectric polarization. The switching geometry can involve a volume, interfacial, or confined 1D filamentary regions [1À8]. Although these technologies have been mainly developed as nonvolatile memory devices for storage applications, recently, they have been receiving increasing interest for brain-inspired computing, and many exciting developments are underway in this direction [1, 9À23]. Today we are facing a revolution driven by the increasing amount of data generated each day, which need to be stored, classified, and processed, leading to the paradigm of datacentric-computing. On the other hand current computing systems are inherently limited in energy efficiency and data bandwidth by the physically separated memory and processing units (von Neumann bottleneck), as well as by the latency mismatch between the memory and processing units (memory wall)[9, 10, 13]. Memristive devices have the potential to meet the considerable demand for new devices that enable energy-efficient and area-efficient
Woodhead Publishing
Publication date: 
12 Jun 2020

Sabina Bipin Rajendran Spiga, Abu Sebastian, Damien Querlioz

Biblio References: 
Pages: 1
Memristive Devices for Brain-Inspired Computing: From Materials, Devices, and Circuits to Applications-Computational Memory, Deep Learning, and Spiking Neural Networks