State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai, China.
School of Computer Science, Fudan University, Shanghai, China.
Nat Nanotechnol. 2020 Jul;15(7):545-557. doi: 10.1038/s41565-020-0724-3. Epub 2020 Jul 9.
Rapid digital technology advancement has resulted in a tremendous increase in computing tasks imposing stringent energy efficiency and area efficiency requirements on next-generation computing. To meet the growing data-driven demand, in-memory computing and transistor-based computing have emerged as potent technologies for the implementation of matrix and logic computing. However, to fulfil the future computing requirements new materials are urgently needed to complement the existing Si complementary metal-oxide-semiconductor technology and new technologies must be developed to enable further diversification of electronics and their applications. The abundance and rich variety of electronic properties of two-dimensional materials have endowed them with the potential to enhance computing energy efficiency while enabling continued device downscaling to a feature size below 5 nm. In this Review, from the perspective of matrix and logic computing, we discuss the opportunities, progress and challenges of integrating two-dimensional materials with in-memory computing and transistor-based computing technologies.
快速的数字技术进步导致计算任务的大量增加,这对下一代计算提出了严格的能效和面积效率要求。为了满足不断增长的数据驱动需求,基于内存的计算和基于晶体管的计算已经成为实现矩阵和逻辑计算的强大技术。然而,为了满足未来的计算需求,迫切需要新的材料来补充现有的硅互补金属氧化物半导体技术,并且必须开发新技术,以进一步使电子学及其应用多样化。二维材料丰富多样的电子特性使它们有可能在继续缩小器件尺寸至 5nm 以下的同时,提高计算能效。在这篇综述中,我们从矩阵和逻辑计算的角度,讨论了将二维材料与基于内存的计算和基于晶体管的计算技术集成的机遇、进展和挑战。