Fig. 3: Experimentally demonstrated NL-ADC on crossbar arrays. | Nature Communications

Fig. 3: Experimentally demonstrated NL-ADC on crossbar arrays.

From: Efficient nonlinear function approximation in analog resistive crossbars for recurrent neural networks

Fig. 3

a Calibration process for accurate NL-ADC programming. The left panel shows the ramp function of the ideal case, programming without bias calibration and with bias calibration. The case with bias calibration shows better INL performance. The right panel shows the actual conductance mapping on the crossbar arrays on two blocks of 8 arbitrary selected columns. The lower 5 conductances are for bias calibration while the top 32 are for the ramp generation. We show the cases when mapping of NL-ADC weights doesn’t have stuck-at-OFF devices and low programming error (left block), and the cases which have stuck-at-OFF devices and high programming error (right block). The results show that both cases can be calibrated by the additional 5 memristors. b Robustness of our proposed in-memory NL-ADC under Vread variations. We sweep the Vread from 0.15 V to 0.25 V to simulate noise induced variations in read voltage. Normal ADC has large variations while our in-memory NL-ADC can track the Vread.

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