The growth of connected intelligent devices in the Internet of Things has created a pressing need for real-time processing and understanding of large volumes of analogue data. The difficulty in boosting the computing speed renders digital computing unable to meet the demand for processing analogue information that is intrinsically continuous in magnitude and time. By utilizing a continuous data representation in a nanoscale crossbar array, parallel computing can be implemented for the direct processing of analogue information in real time. Here, we propose a scalable massively parallel computing scheme by exploiting a continuous-time data representation and frequency multiplexing in a nanoscale crossbar array. This computing scheme enables the parallel reading of stored data and the one-shot operation of matrix–matrix multiplications in the crossbar array. Furthermore, we achieve the one-shot recognition of 16 letter images based on two physically interconnected crossbar arrays and demonstrate that the processing and modulation of analogue information can be simultaneously performed in a memristive crossbar array.

物联网中互联智能设备的增长催生了对实时处理和理解大量模拟数据的迫切需求。计算速度难以提升，使得数字计算无法满足处理本质上在量级和时间上连续的模拟信息的需求。通过利用纳米级交叉阵列中的连续数据表示，可以实现并行计算以实时直接处理模拟信息。在这里，我们通过利用纳米级交叉阵列中的连续时间数据表示和频率复用，提出了一种可扩展的大规模并行计算方案。该计算方案支持并行读取存储数据和交叉阵列中的矩阵-矩阵乘法的一次性操作。此外，我们基于两个物理互连的交叉阵列实现了 16 个字母图像的一次性识别，并证明模拟信息的处理和调制可以在忆阻交叉阵列中同时执行。