Advancements in materials, devices, and integration schemes for a new generation of neuromorphic computers

The slowing pace of performance improvements in modern processors along with the breakdown of power scaling forecasts an imminent end to the traditional transistor scaling roadmap. Additionally, meeting the aggressive demands of proliferating applications in big-data processing, machine learning, artificial intelligence, and highly distributed edge computing requires radical advancements in materials, devices, and architectures for future processors. Neuromorphic computing has emerged as the most promising successor to conventional complementary metal oxide semiconductor (CMOS) devices and von Neumann architecture. This work reviews the status of neuromorphic research, compares the traditional CMOS approach with neuromorphic devices for implementing biologically inspired circuits, and provides an outlook into integration schemes for future brain-inspired computing hardware.

Automated summary

The slowing pace of performance improvements and the breakdown of power scaling in modern processors signals the imminent end of the traditional transistor scaling roadmap. Future processors require radical advancements in materials, devices, and architectures, with neuromorphic computing emerging as the most promising successor.