Simulation of Temporal Correlation Detection using HfO2-Based ReRAM Arrays

As CMOS scaling approaches its limitation, the power consumption of computations performed using the von Neumann architecture have become an issue. As a promising alternative solution, Resistive Random Access Memory (ReRAM) overcomes this bottleneck by enabling computation-in-memory. In this work, arrays of HfO
₂
-based bipolar ReRAM are simulated to carry out one such computation, called temporal correlation detection in binary processes. The correlation detection algorithm is presented, and the ReRAM model of fabricated devices was used in a Python-based simulation. The correlated and uncorrelated processes were assigned to ReRAM devices in a 5x5 array, where the ReRAM with correlated process was driven to a high conductance over time. The results show that the correlated processes are successfully detected over time.