Fig. 6: Investigation of the impacts of a non-selective memristor integrated into the passive CA on VMM operation accuracy. | Nature Communications

Fig. 6: Investigation of the impacts of a non-selective memristor integrated into the passive CA on VMM operation accuracy.

From: Purely self-rectifying memristor-based passive crossbar array for artificial neural network accelerators

Fig. 6

a DC I–V characteristics of a unit memristor device without selection functionality (left). Ten randomly chosen cells were measured over three cycles (total number of DC I–V curves: 30). The read current distributions of each state were extracted from the DC I–V curves (right). b DC I–V characteristics of an 8 × 8 CA integrated with the memristor. All cells in the CA were measured in one cycle in DC I–V sweep mode (graph). The read current distributions of each state were extracted from the DC I–V curve (right). c Programming scheme of the 8 × 8 CA. A total of 32 randomly chosen cells were programmed to the LRS (black), and the rest of the cells were maintained in the HRS (orange). d Resistance distribution of the 8 × 8 CA after the programming step. The programmed weight values of the CA were not coincident with the proposed programming scheme, indicating that programming and reading were not processed accurately owing to sneak current effects. e Results of VMM operations using the 8 × 8 CA. Nearly identical output currents were observed in each column, which implies that the VMM operation was not processed accurately because of significant interferences between integrated cells in the CA.

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