  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.
