Memristive Devices for New Computing Paradigms
In Hyuk Im, Seung Ju Kim, Ho Won Jang
Abstract
In complementary metal–oxide–semiconductor (CMOS)‐based von Neumann architectures, the intrinsic power and speed inefficiencies are worsened by the drastic increase in information with big data. With the potential to store numerous values in I – V pinched hysteresis, memristors (memory resistors) have emerged as alternatives to existing CMOS‐based computing systems. Herein, four types of memristive devices, namely, resistive switching, phase‐change, spintronics, and ferroelectric tunnel junction memristors, are explored. The application of these devices to a crossbar array (CBA), which is a novel concept of integrated architecture, is a step toward the realization of ultradense electronics. Exploiting the fascinating capabilities of memristive devices, computing systems can be developed with novel computing paradigms, in which large amounts of data can be stored and processed within CBAs. Looking further ahead, the ways in which memristors could be incorporated in neuromorphic computing systems along with various artificial intelligence algorithms are established. Finally, perspectives and challenges that memristor technology should address to provide excellent alternatives to existing computing systems are discussed. The infinite potential of memristors is the key to unlock new computing paradigms, which pave the way for next‐generation computing systems.