A fully integrated reprogrammable memristor–CMOS system for efficient multiply–accumulate operations

摘要

Memristors and memristor crossbar arrays have been widely studied for neuromorphic and other in-memory computing applications.To achieve optimal system performance, however, it is essential to integrate memristor crossbars with peripheral andcontrol circuitry. Here, we report a fully functional, hybrid memristor chip in which a passive crossbar array is directly integratedwith custom-designed circuits, including a full set of mixed-signal interface blocks and a digital processor for reprogrammablecomputing. The memristor crossbar array enables online learning and forward and backward vector-matrix operations,while the integrated interface and control circuitry allow mapping of different algorithms on chip. The system supports chargedomainoperation to overcome the nonlinear I–V characteristics of memristor devices through pulse width modulation andcustom analogue-to-digital converters. The integrated chip offers all the functions required for operational neuromorphic computinghardware. Accordingly, we demonstrate a perceptron network, sparse coding algorithm and principal component analysiswith an integrated classification layer using the system.