PCMO-Based RRAM and NPN Bipolar Selector as Synapse for Energy Efficient STDP

Abstract

Resistance random access memories (RRAMs) are widely explored to show spike time dependent plasticity (STDP) as a learning rule to show biological synaptic behavior, as these devices possess analog conductance change. To implement STDP, pre- and post-neuronal waveforms are superposed. Only the peak voltage changes the conductance of memory. But due to the remaining part of the waveform (which don’t affect the conductance change), there is a significant amount of inadvertent current flow leading to unnecessary energy consumption. In this letter, we experimentally demonstrate that, the PCMO-based RRAM, a memristor (1M) in series with the NPN selector can be used as a synapse to reduce the undesirable energy consumption. First, we propose the pre- and post-neuronal waveform engineering required for PCMO-based memristor + Selector (1S1M) to reduce energy consumption. Second, we demonstrate experimentally that 1S1M synapse gives $> \mathsf {4700} \times $ reduction in energy consumption compared with 1M synapse for a single neuronal waveform. Third, we implement and compare anti-STDP for 1M and 1S1M synapse to show no loss of generality. Thus, we experimentally demonstrate 1S1M-based energy efficient synapse for brain inspired computing.