The next generation of artificial intelligence systems is generally governed by a new electronic element called memristor. Memristor-based computational system is responsible for confronting memory wall issues in conventional system architecture in the big data era. Complementary Metal Oxide Semiconductor (CMOS) compatibility, nonvolatility and scalability are the important properties of memristor for designing such computing architecture. However, some of the concerns, such as analogue switching and stochasticity, need to be addressed for the use of memristor in novel architecture. Here, we reviewed a number of important scientific works on memristor materials, electrical performance and their integration. In addition, strategies to address the challenges of memristor integration in neuromorphic computing are also being investigated.

中文翻译：

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忆阻器：神经形态计算的理解、利用和升级

下一代人工智能系统通常由一种称为忆阻器的新电子元件控制。基于忆阻器的计算系统负责解决大数据时代传统系统架构中的内存墙问题。互补金属氧化物半导体 (CMOS) 兼容性、非易失性和可扩展性是忆阻器设计此类计算架构的重要特性。然而，在新型架构中使用忆阻器需要解决一些问题，例如模拟切换和随机性。在这里，我们回顾了一些关于忆阻器材料、电气性能及其集成的重要科学著作。此外，还在研究解决神经形态计算中忆阻器集成挑战的策略。